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  • 1.
    Abbas, Zainab
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Al-Shishtawy, Ahmad
    RISE SICS, Stockholm, Sweden.
    Girdzijauskas, Sarunas
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS. RISE SICS, Stockholm, Sweden..
    Vlassov, Vladimir
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Short-Term Traffic Prediction Using Long Short-Term Memory Neural Networks2018Konferensbidrag (Refereegranskat)
    Abstract [en]

    Short-term traffic prediction allows Intelligent Transport Systems to proactively respond to events before they happen. With the rapid increase in the amount, quality, and detail of traffic data, new techniques are required that can exploit the information in the data in order to provide better results while being able to scale and cope with increasing amounts of data and growing cities. We propose and compare three models for short-term road traffic density prediction based on Long Short-Term Memory (LSTM) neural networks. We have trained the models using real traffic data collected by Motorway Control System in Stockholm that monitors highways and collects flow and speed data per lane every minute from radar sensors. In order to deal with the challenge of scale and to improve prediction accuracy, we propose to partition the road network into road stretches and junctions, and to model each of the partitions with one or more LSTM neural networks. Our evaluation results show that partitioning of roads improves the prediction accuracy by reducing the root mean square error by the factor of 5. We show that we can reduce the complexity of LSTM network by limiting the number of input sensors, on average to 35% of the original number, without compromising the prediction accuracy.

  • 2.
    Abbas, Zainab
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Kalavri, Vasiliki
    Systems Group, ETH, Zurich, Switzerland.
    Carbone, Paris
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Vlassov, Vladimir
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Streaming Graph Partitioning: An Experimental Study2018Ingår i: Proceedings of the VLDB Endowment, ISSN 2150-8097, E-ISSN 2150-8097, Vol. 11, nr 11, s. 1590-1603Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Graph partitioning is an essential yet challenging task for massive graph analysis in distributed computing. Common graph partitioning methods scan the complete graph to obtain structural characteristics offline, before partitioning. However, the emerging need for low-latency, continuous graph analysis led to the development of online partitioning methods. Online methods ingest edges or vertices as a stream, making partitioning decisions on the fly based on partial knowledge of the graph. Prior studies have compared offline graph partitioning techniques across different systems. Yet, little effort has been put into investigating the characteristics of online graph partitioning strategies.

    In this work, we describe and categorize online graph partitioning techniques based on their assumptions, objectives and costs. Furthermore, we employ an experimental comparison across different applications and datasets, using a unified distributed runtime based on Apache Flink. Our experimental results showcase that model-dependent online partitioning techniques such as low-cut algorithms offer better performance for communication-intensive applications such as bulk synchronous iterative algorithms, albeit higher partitioning costs. Otherwise, model-agnostic techniques trade off data locality for lower partitioning costs and balanced workloads which is beneficial when executing data-parallel single-pass graph algorithms.

  • 3.
    Abbas, Zainab
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Sigurdsson, Thorsteinn Thorri
    KTH.
    Al-Shishtawy, Ahmad
    RISE Res Inst Sweden, Stockholm, Sweden..
    Vlassov, Vladimir
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Evaluation of the Use of Streaming Graph Processing Algorithms for Road Congestion Detection2018Ingår i: 2018 IEEE INT CONF ON PARALLEL & DISTRIBUTED PROCESSING WITH APPLICATIONS, UBIQUITOUS COMPUTING & COMMUNICATIONS, BIG DATA & CLOUD COMPUTING, SOCIAL COMPUTING & NETWORKING, SUSTAINABLE COMPUTING & COMMUNICATIONS / [ed] Chen, JJ Yang, LT, IEEE COMPUTER SOC , 2018, s. 1017-1025Konferensbidrag (Refereegranskat)
    Abstract [en]

    Real-time road congestion detection allows improving traffic safety and route planning. In this work, we propose to use streaming graph processing algorithms for road congestion detection and evaluate their accuracy and performance. We represent road infrastructure sensors in the form of a directed weighted graph and adapt the Connected Components algorithm and some existing graph processing algorithms, originally used for community detection in social network graphs, for the task of road congestion detection. In our approach, we detect Connected Components or communities of sensors with similarly weighted edges that reflect different states in the traffic, e.g., free flow or congested state, in regions covered by detected sensor groups. We have adapted and implemented the Connected Components and community detection algorithms for detecting groups in the weighted sensor graphs in batch and streaming manner. We evaluate our approach by building and processing the road infrastructure sensor graph for Stockholm's highways using real-world data from the Motorway Control System operated by the Swedish traffic authority. Our results indicate that the Connected Components and DenGraph community detection algorithms can detect congestion with accuracy up to approximate to 94% for Connected Components and up to approximate to 88% for DenGraph. The Louvain Modularity algorithm for community detection fails to detect congestion regions for sparsely connected graphs, representing roads that we have considered in this study. The Hierarchical Clustering algorithm using speed and density readings is able to detect congestion without details, such as shockwaves.

  • 4.
    Alferez, Mauricio
    et al.
    Univ Luxembourg, Interdisciplinary Ctr Secur Reliabil & Trust SnT, 2 Ave JF Kennedy, L-1855 Luxembourg, Luxembourg..
    Acher, Mathieu
    Univ Rennes, DiverSE Team Inria Rennes, IRISA, CNRS, Rennes, France..
    Galindo, Jose A.
    Univ Seville, Dept Comp Languages & Syst, Seville, Spain..
    Baudry, Benoit
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Benavides, David
    Univ Seville, Dept Comp Languages & Syst, Seville, Spain..
    Modeling variability in the video domain: language and experience report2019Ingår i: Software quality journal, ISSN 0963-9314, E-ISSN 1573-1367, Vol. 27, nr 1, s. 307-347Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In an industrial project, we addressed the challenge of developing a software-based video generator such that consumers and providers of video processing algorithms can benchmark them on a wide range of video variants. This article aims to report on our positive experience in modeling, controlling, and implementing software variability in the video domain. We describe how we have designed and developed a variability modeling language, called VM, resulting from the close collaboration with industrial partners during 2 years. We expose the specific requirements and advanced variability constructs; we developed and used to characterize and derive variations of video sequences. The results of our experiments and industrial experience show that our solution is effective to model complex variability information and supports the synthesis of hundreds of realistic video variants. From the software language perspective, we learned that basic variability mechanisms are useful but not enough; attributes and multi-features are of prior importance; meta-information and specific constructs are relevant for scalable and purposeful reasoning over variability models. From the video domain and software perspective, we report on the practical benefits of a variability approach. With more automation and control, practitioners can now envision benchmarking video algorithms over large, diverse, controlled, yet realistic datasets (videos that mimic real recorded videos)-something impossible at the beginning of the project.

  • 5.
    Apolonia, Nuno
    et al.
    Universitat Politecnica de Catalunya (UPC) Barcelona, Spain.
    Antaris, Stefanos
    Girdzijauskas, Šarunas
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Pallis, G.
    Dikaiakos, Marios
    SELECT: A distributed publish/subscribe notification system for online social networks2018Ingår i: Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium, IPDPS 2018, Institute of Electrical and Electronics Engineers (IEEE), 2018, s. 970-979, artikel-id 8425250Konferensbidrag (Refereegranskat)
    Abstract [en]

    Publish/subscribe (pub/sub) mechanisms constitutean attractive communication paradigm in the design of large-scale notification systems for Online Social Networks (OSNs). Toaccommodate the large-scale workloads of notifications producedby OSNs, pub/sub mechanisms require thousands of serversdistributed on different data centers all over the world, incurringlarge overheads. To eliminate the pub/sub resources used, wepropose SELECT - a distributed pub/sub social notificationsystem over peer-to-peer (P2P) networks. SELECT organizesthe peers on a ring topology and provides an adaptive P2Pconnection establishment algorithm where each peer identifiesthe number of connections required, based on the social structureand user availability. This allows to propagate messages to thesocial friends of the users using a reduced number of hops.The presented algorithm is an efficient heuristic to an NP-hard problem which maps workload graphs to structured P2Poverlays inducing overall, close to theoretical, minimal number ofmessages. Experiments show that SELECT reduces the numberof relay nodes up to 89% versus the state-of-the-art pub/subnotification systems. Additionally, we demonstrate the advantageof SELECT against socially-aware P2P overlay networks andshow that the communication between two socially connectedpeers is reduced on average by at least 64% hops, while achieving100% communication availability even under high churn.

  • 6.
    Apolonia, Nuno
    et al.
    KTH, Skolan för informations- och kommunikationsteknik (ICT). Universitat Politecnica de Catalunya (UPC) Barcelona, Spain.
    Freitag, Felix
    Universitat Politècnica de Catalunya. Barcelona, Spain.
    Navarro, Leandro
    Universitat Politècnica de Catalunya, BarcelonaTECH, Barcelona, Spain.
    Girdzijauskas, Sarunas
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Socially aware microcloud service overlay optimization in community networks2019Ingår i: Software, practice & experience, ISSN 0038-0644, Vol. 49, nr 1, artikel-id 13Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Community networks are a growing network cooperation effort by citizens to build and maintain Internet infrastructure in regions that are not available. Adding that, to bring cloud services to community networks (CNs), microclouds were started as an edge cloud computing model where members cooperate using resources. Therefore, enhancing routing for services in CNs is an attractive paradigm that benefits the infrastructure. The problem is the growing consumption of resources for disseminating messages in the CN environment. This is because the services that build their overlay networks are oblivious to the underlying workload patterns that arise from social cooperation in CNs. In this paper, we propose Select in Community Networks (SELECTinCN), which enhances the overlay creation for pub/sub systems over peer‐to‐peer (P2P) networks. Moreover, SELECTinCN includes social information based on cooperation within CNs by exploiting the social aspects of the community of practice. Our work organizes the peers in a ring topology and provides an adaptive P2P connection establishment algorithm, where each peer identifies the number of connections needed based on the social structure and user availability. This allows us to propagate messages using a reduced number of hops, thus providing an efficient heuristic to an NP‐hard problem that maps the workload graph to the structured P2P overlays resulting in a number of messages close to the theoretical minimum. Experiments show that, by using social network information, SELECTinCN reduces the number of relay nodes by up to 89% using the community of practice information versus the state‐of‐the‐art pub/sub notification systems given as baseline.

  • 7.
    Bahri, Leila
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Carminati, Barbara
    Ferrari, Elena
    Univ Insubria, Dept Theoret & Appl Sci, Varese, Italy..
    Knowledge-based approaches for identity management in online social networks2018Ingår i: WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, ISSN 1942-4787, Vol. 8, nr 5, artikel-id e1260Artikel, forskningsöversikt (Refereegranskat)
    Abstract [en]

    When we meet a new person, we start by introducing ourselves. We share our names, and other information about our jobs, cities, family status, and so on. This is how socializing and social interactions can start: we first need to identify each other. Identification is a cornerstone in establishing social contacts. We identify ourselves and others by a set of civil (e.g., name, nationality, ID number, gender) and social (e.g., music taste, hobbies, religion) characteristics. This seamlessly carried out identification process in face-to-face interactions is challenged in the virtual realms of socializing, such as in online social network (OSN) platforms. New identities (i.e., online profiles) could be created without being subject to any level of verification, making it easy to create fake information and forge fake identities. This has led to a massive proliferation of accounts that represent fake identities (i.e., not mapping to physically existing entities), and that poison the online socializing environment with fake information and malicious behavior (e.g., child abuse, information stealing). Within this milieu, users in OSNs are left unarmed against the challenging task of identifying the real person behind the screen. OSN providers and research bodies have dedicated considerable effort to the study of the behavior and features of fake OSN identities, trying to find ways to detect them. Some other research initiatives have explored possible techniques to enable identity validation in OSNs. Both kinds of approach rely on extracting knowledge from the OSN, and exploiting it to achieve identification management in their realms. We provide a review of the most prominent works in the literature. We define the problem, provide a taxonomy of related attacks, and discuss the available solutions and approaches for knowledge-based identity management in OSNs. This article is categorized under: Fundamental Concepts of Data and Knowledge > Human Centricity and User Interaction Application Areas> Internet and Web-Based Applications Application Areas> Society and Culture

  • 8.
    Bahri, Leila
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Girdzijauskas, Sarunas
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Blockchain technology: Practical P2P computing (Tutorial)2019Ingår i: Proceedings - 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems, FAS*W 2019, Institute of Electrical and Electronics Engineers (IEEE), 2019, s. 249-250, artikel-id 8791982Konferensbidrag (Refereegranskat)
    Abstract [en]

    Blockchain technology comes with the promise to revolutionize the way current IT systems are organized as well as to revise how trust is perceived in the wider society. In spite of the wide attention that cyrpto-currencies (such as Bitcoin) have attracted, Blockchain technology is more likely to make an impact beyond ongoing speculations on cyrpto-currencies. Decentralized identity management, transparent supply-chain systems, and IoT governance and security are only few examples of research challenges for which this technology may hold substantial potential. Blockchain technology has emerged at the intersection of two well established research areas: peer-to-peer (P2P) computing and cryptography. In this tutorial, we provide a general overview of the main components behind this technology, we present the difference between the types of Blockchain available today, and we make a high level discussion on its potentials and limitations as well as possible research challenges.

  • 9.
    Bahri, Leila
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Girdzijauskas, Sarunas
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Trust Mends Blockchains: Living up to Expectations2019Ingår i: IEEE 39th International Conference on Distributed Computing Systems (ICDCS), Dallas, July 7-10 2019, 2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    At the heart of Blockchains is the trustless leader election mechanism for achieving consensus among pseudoanonymous peers, without the need of oversight from any third party or authority whatsoever. So far, two main mechanisms are being discussed: proof-of-work (PoW) and proof-of-stake (PoS). PoW relies on demonstration of computational power, and comes with the markup of huge energy wastage in return of the stake in cyrpto-currency. PoS tries to address this by relying on owned stake (i.e., amount of crypto-currency) in the system. In both cases, Blockchains are limited to systems with financial basis. This forces non-crypto-currency Blockchain applications to resort to “permissioned” setting only, effectively centralizing the system. However, non-crypto-currency permisionless blockhains could enable secure and self-governed peer-to-peer structures for numerous emerging application domains, such as education and health, where some trust exists among peers. This creates a new possibility for valuing trust among peers and capitalizing it as the basis (stake) for reaching consensus. In this paper we show that there is a viable way for permisionless non-financial Blockhains to operate in completely decentralized environments and achieve leader election through proof-of-trust (PoT). In our PoT construction, peer trust is extracted from a trust network that emerges in a decentralized manner and is used as a waiver for the effort to be spent for PoW, thus dramatically reducing total energy expenditure of the system. Furthermore, our PoT construction is resilient to the risk of small cartels monopolizing the network (as it happens with the mining-pool phenomena in PoW) and is not vulnerable to sybils. We evluate security guarantees, and perform experimental evaluation of our construction, demonstrating up to 10-fold energy savings compared to PoW without trading off any of the decentralization characteristics, with further guarantees against risks of monopolization.

    Ladda ner fulltext (pdf)
    fulltext
  • 10.
    Bahri, Leila
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Girdzijauskas, Sarunas
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Trust mends blockchains: Living up to expectations2019Ingår i: Proceedings - International Conference on Distributed Computing Systems, 2019, s. 1358-1368Konferensbidrag (Refereegranskat)
    Abstract [en]

    At the heart of Blockchains is the trustless leader election mechanism for achieving consensus among pseudo-anonymous peers, without the need of oversight from any third party or authority whatsoever. So far, two main mechanisms are being discussed: proof-of-work (PoW) and proof-of-stake (PoS). PoW relies on demonstration of computational power, and comes with the markup of huge energy wastage in return of the stake in cyrpto-currency. PoS tries to address this by relying on owned stake (i.e., amount of crypto-currency) in the system. In both cases, Blockchains are limited to systems with financial basis. This forces non-crypto-currency Blockchain applications to resort to "permissioned" setting only, effectively centralizing the system. However, non-crypto-currency permisionless blockhains could enable secure and self-governed peer-to-peer structures for numerous emerging application domains, such as education and health, where some trust exists among peers. This creates a new possibility for valuing trust among peers and capitalizing it as the basis (stake) for reaching consensus. In this paper we show that there is a viable way for permisionless non-financial Blockhains to operate in completely decentralized environments and achieve leader election through proof-of-trust (PoT). In our PoT construction, peer trust is extracted from a trust network that emerges in a decentralized manner and is used as a waiver for the effort to be spent for PoW, thus dramatically reducing total energy expenditure of the system. Furthermore, our PoT construction is resilient to the risk of small cartels monopolizing the network (as it happens with the mining-pool phenomena in PoW) and is not vulnerable to sybils. We evluate security guarantees, and perform experimental evaluation of our construction, demonstrating up to 10-fold energy savings compared to PoW without trading off any of the decentralization characteristics, with further guarantees against risks of monopolization.

  • 11.
    Bahri, Leila
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Girdzijauskas, Sarunas
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    When Trust Saves Energy - A Reference Framework for Proof-of-Trust (PoT) Blockchains2018Ingår i: WWW '18 Companion Proceedings of the The Web Conference 2018, ACM Digital Library, 2018, s. 1165-1169Konferensbidrag (Refereegranskat)
    Abstract [en]

    Blockchains are attracting the attention of many technical, financial, and industrial parties, as a promising infrastructure for achieving secure peer-to-peer (P2P) transactional systems. At the heart of blockchains is proof-of-work (PoW), a trustless leader election mechanism based on demonstration of computational power. PoW provides blockchain security in trusless P2P environments, but comes at the expense of wasting huge amounts of energy. In this research work, we question this energy expenditure of PoW under blockchain use cases where some form of trust exists between the peers. We propose a Proof-of-Trust (PoT) blockchain where peer trust is valuated in the network based on a trust graph that emerges in a decentralized fashion and that is encoded in and managed by the blockchain itself. This trust is then used as a waiver for the difficulty of PoW; that is, the more trust you prove in the network, the less work you do.

    Ladda ner fulltext (pdf)
    fulltext
  • 12.
    Baudry, Benoit
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Harrand, Nicolas
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Schulte, E.
    Timperley, C.
    Tan, S. H.
    Selakovic, M.
    Ugherughe, E.
    A spoonful of DevOps helps the GI go down2018Ingår i: Proceedings - International Conference on Software Engineering, IEEE Computer Society , 2018, s. 35-36Konferensbidrag (Refereegranskat)
    Abstract [en]

    DevOps emphasizes a high degree of automation at all phases of the software development lifecyle. Meanwhile, Genetic Improvement (GI) focuses on the automatic improvement of software artifacts. In this paper, we discuss why we believe that DevOps offers an excellent technical context for easing the adoption of GI techniques by software developers. We also discuss A/B testing as a prominent and clear example of GI taking place in the wild today, albeit one with human-supervised fitness and mutation operators.

  • 13.
    Bhatti, Muhammad Khurram
    et al.
    Informat Technol Univ, Embedded Comp Lab, 346-B Ferozpur Rd, Lahore, Pakistan..
    Oz, Isil
    Izmir Inst Technol, Comp Engn Dept, Izmir, Turkey..
    Amin, Sarah
    Informat Technol Univ, Embedded Comp Lab, 346-B Ferozpur Rd, Lahore, Pakistan..
    Mushtaq, Maria
    Informat Technol Univ, Embedded Comp Lab, 346-B Ferozpur Rd, Lahore, Pakistan..
    Farooq, Umer
    Dhofar Univ, Dept Elect & Comp Engn, Salalah 211, Oman..
    Popov, Konstantin
    SICS, Isafjordsgatan 22, S-16429 Kista, Sweden..
    Brorsson, Mats
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Locality-aware task scheduling for homogeneous parallel computing systems2018Ingår i: Computing, ISSN 0010-485X, E-ISSN 1436-5057, Vol. 100, nr 6, s. 557-595Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In systems with complex many-core cache hierarchy, exploiting data locality can significantly reduce execution time and energy consumption of parallel applications. Locality can be exploited at various hardware and software layers. For instance, by implementing private and shared caches in a multi-level fashion, recent hardware designs are already optimised for locality. However, this would all be useless if the software scheduling does not cast the execution in a manner that promotes locality available in the programs themselves. Since programs for parallel systems consist of tasks executed simultaneously, task scheduling becomes crucial for the performance in multi-level cache architectures. This paper presents a heuristic algorithm for homogeneous multi-core systems called locality-aware task scheduling (LeTS). The LeTS heuristic is a work-conserving algorithm that takes into account both locality and load balancing in order to reduce the execution time of target applications. The working principle of LeTS is based on two distinctive phases, namely; working task group formation phase (WTG-FP) and working task group ordering phase (WTG-OP). The WTG-FP forms groups of tasks in order to capture data reuse across tasks while the WTG-OP determines an optimal order of execution for task groups that minimizes the reuse distance of shared data between tasks. We have performed experiments using randomly generated task graphs by varying three major performance parameters, namely: (1) communication to computation ratio (CCR) between 0.1 and 1.0, (2) application size, i.e., task graphs comprising of 50-, 100-, and 300-tasks per graph, and (3) number of cores with 2-, 4-, 8-, and 16-cores execution scenarios. We have also performed experiments using selected real-world applications. The LeTS heuristic reduces overall execution time of applications by exploiting inter-task data locality. Results show that LeTS outperforms state-of-the-art algorithms in amortizing inter-task communication cost.

  • 14.
    Boman, Magnus
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    ben Abdesslem, Fehmi
    Forsell, Erik
    Gillblad, Daniel
    Görnerup, Olof
    Isacsson, Nils
    Sahlgren, Magnus
    Kaldo, Viktor
    Learning machines in Internet-delivered psychological treatment2019Ingår i: Progress in artificial intelligence, ISSN 2192-6352, Vol. 8, nr 4, s. 475-485Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A learning machine, in the form of a gating network that governs a finite number of different machine learning methods, is described at the conceptual level with examples of concrete prediction subtasks. A historical data set with data from over 5000 patients in Internet-based psychological treatment will be used to equip healthcare staff with decision support for questions pertaining to ongoing and future cases in clinical care for depression, social anxiety, and panic disorder. The organizational knowledge graph is used to inform the weight adjustment of the gating network and for routing subtasks to the different methods employed locally for prediction. The result is an operational model for assisting therapists in their clinical work, about to be subjected to validation in a clinical trial.

  • 15.
    Boman, Magnus
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Heger, Tobias
    Circles of Impression: External Foresight in Global Enterprises2019Ingår i: Futures Thinking and Organizational Policy / [ed] D. A. Schreiber and Z. L. Berge, Cham: Palgrave Macmillan, 2019, s. 179-199Kapitel i bok, del av antologi (Refereegranskat)
  • 16.
    Borlenghi, Simone
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik, Material- och nanofysik.
    Boman, Magnus
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS. RISE SICS, Electrum 229, SE-16429 Kista, Sweden..
    Delin, Anna
    KTH, Skolan för industriell teknik och management (ITM), Materialvetenskap, Tillämpad materialfysik. KTH, Centra, SeRC - Swedish e-Science Research Centre.
    Modeling reservoir computing with the discrete nonlinear Schrodinger equation2018Ingår i: Physical review. E, ISSN 2470-0045, E-ISSN 2470-0053, Vol. 98, nr 5, artikel-id 052101Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We formulate, using the discrete nonlinear Schrodinger equation (DNLS), a general approach to encode and process information based on reservoir computing. Reservoir computing is a promising avenue for realizing neuromorphic computing devices. In such computing systems, training is performed only at the output level by adjusting the output from the reservoir with respect to a target signal. In our formulation, the reservoir can be an arbitrary physical system, driven out of thermal equilibrium by an external driving. The DNLS is a general oscillator model with broad application in physics, and we argue that our approach is completely general and does not depend on the physical realization of the reservoir. The driving, which encodes the object to be recognized, acts as a thermodynamic force, one for each node in the reservoir. Currents associated with these thermodynamic forces in turn encode the output signal from the reservoir. As an example, we consider numerically the problem of supervised learning for pattern recognition, using as a reservoir a network of nonlinear oscillators.

  • 17. Bousse, Erwan
    et al.
    Leroy, Dorian
    Combemale, Benoit
    Wimmer, Manuel
    Baudry, Benoit
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Omniscient debugging for executable DSLs2018Ingår i: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 137, s. 261-288Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Omniscient debugging is a promising technique that relies on execution traces to enable free traversal of the states reached by a model (or program) during an execution. While a few General-Purpose Languages (GPLs) already have support for omniscient debugging, developing such a complex tool for any executable Domain Specific Language (DSL) remains a challenging and error prone task. A generic solution must: support a wide range of executable DSLs independently of the metaprogramming approaches used for implementing their semantics; be efficient for good responsiveness. Our contribution relies on a generic omniscient debugger supported by efficient generic trace management facilities. To support a wide range of executable DSLs, the debugger provides a common set of debugging facilities, and is based on a pattern to define runtime services independently of metaprogramming approaches. Results show that our debugger can be used with various executable DSLs implemented with different metaprogramming approaches. As compared to a solution that copies the model at each step, it is on average sixtimes more efficient in memory, and at least 2.2 faster when exploring past execution states, while only slowing down the execution 1.6 times on average.

  • 18.
    Broman, David
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    A vision of miking: Interactive programmatic modeling, sound language composition, and self-learning compilation2019Ingår i: SLE 2019 - Proceedings of the 12th ACM SIGPLAN International Conference on Software Language Engineering, co-located with SPLASH 2019, Association for Computing Machinery, Inc , 2019, s. 55-60Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper introduces a vision of Miking, a language framework for constructing efficient and sound language environments and compilers for domain-specific modeling languages. In particular, this language framework has three key objectives: (i) to automatically generate interactive programmatic modeling environments, (ii) to guarantee sound compositions of language fragments that enable both rapid and safe domain-specific language development, (iii) to include first-class support for self-learning compilation, targeting heterogeneous execution platforms. The initiative is motivated in the domain of mathematical modeling languages. Specifically, two different example domains are discussed: (i) modeling, simulation, and verification of cyber-physical systems, and (ii) domain-specific differentiable probabilistic programming. The paper describes the main objectives of the vision, as well as concrete research challenges and research directions.

  • 19.
    Broman, David
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Hybrid Simulation Safety: Limbos and Zero Crossings2018Ingår i: Principles of Modeling: Essays Dedicated to Edward A. Lee on the Occasion of His 60th Birthday, Springer, 2018, s. 106-121Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    Physical systems can be naturally modeled by combining continuous and discrete models. Such hybrid models may simplify the modeling task of complex system, as well as increase simulation performance. Moreover, modern simulation engines can often efficiently generate simulation traces, but how do we know that the simulation results are correct? If we detect an error, is the error in the model or in the simulation itself? This paper discusses the problem of simulation safety, with the focus on hybrid modeling and simulation. In particular, two key aspects are studied: safe zero-crossing detection and deterministic hybrid event handling. The problems and solutions are discussed and partially implemented in Modelica and Ptolemy II.

  • 20.
    Broman, David
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Siek, J. G.
    United States.
    Gradually typed symbolic expressions2017Ingår i: PEPM 2018 - Proceedings of the ACM SIGPLAN Workshop on Partial Evaluation and Program Manipulation, Co-located with POPL 2018, Association for Computing Machinery (ACM), 2017, s. 15-29Konferensbidrag (Refereegranskat)
    Abstract [en]

    Embedding a domain-specific language (DSL) in a general purpose host language is an efficient way to develop a new DSL. Various kinds of languages and paradigms can be used as host languages, including object-oriented, functional, statically typed, and dynamically typed variants, all having their pros and cons. For deep embedding, statically typed languages enable early checking and potentially good DSL error messages, instead of reporting runtime errors. Dynamically typed languages, on the other hand, enable flexible transformations, thus avoiding extensive boilerplate code. In this paper, we introduce the concept of gradually typed symbolic expressions that mix static and dynamic typing for symbolic data. The key idea is to combine the strengths of dynamic and static typing in the context of deep embedding of DSLs. We define a gradually typed calculus <*>, formalize its type system and dynamic semantics, and prove type safety. We introduce a host language called Modelyze that is based on <*>, and evaluate the approach by embedding a series of equation-based domain-specific modeling languages, all within the domain of physical modeling and simulation.

  • 21.
    Cabrera Arteaga, Javier
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Teoretisk datalogi, TCS.
    Monperrus, Martin
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Teoretisk datalogi, TCS.
    Baudry, Benoit
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Scalable comparison of JavaScript V8 bytecode traces2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    The comparison and alignment of runtime traces are essential, e.g., for semantic analysis or debugging. However, naive sequence alignment algorithms cannot address the needs of the modern web: (i) the bytecode generation process of V8 is not deterministic; (ii) bytecode traces are large.

    We present STRAC, a scalable and extensible tool tailored to compare bytecode traces generated by the V8 JavaScript engine. Given two V8 bytecode traces and a distance function between trace events, STRAC computes and provides the best alignment. The key insight is to split access between memory and disk. STRAC can identify semantically equivalent web pages and is capable of processing huge V8 bytecode traces whose order of magnitude matches today's web like https://2019.splashcon.org, which generates approx. 150k of V8 bytecode instructions.

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  • 22.
    Carbone, Paris
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Scalable and Reliable Data Stream Processing2018Doktorsavhandling, monografi (Övrigt vetenskapligt)
    Abstract [sv]

    System för strömmande databehandling har länge ansetts vara en lovande arkitektur för snabb datahantering. Paradigmen för strömmande datahantering utgör ett attraktivt sätt att utrycka tillståndbaserad persistent tillämpningslogik över evolverande data. Men trots många bidrag i programmeringssemantik som adresserar vissa aspekter av dataströmning, har befintliga tillvägagångssätt saknat en tydlig universell specifikation för den underliggande systemexekveringen. Vi undersöker system för strömmande databehandling som en generell skalbar beräkningsarkitektur för kontinuerliga och iterativa tillämpningar. Dessutom undersöker vi hur denna arkitektur kan möjliggöra sammansättningen av pålitliga, omkonfigurerbara tjänster och komplexa tillämpningar som går utöver behoven av den för närvarande trendiga BigData-analysen.

    I den här avhandlingen specificerar vi en uppsättning kärnkomponenter och mekanismer för att sätta samman tillförlitliga system för strömmande databehandling. Samtidigt antar man tre viktiga konstruktionsprinciper: undvikandet av blockerande samordning, transparens av programmeringsmodellen, och sammansättningsbarhet. Vidare identifierar vi de huvudsakliga öppna utmaningarna inom akademi och industri i området, och föreslår en fullständig lösning med hjälp av de ovan nämnda principerna som guide.Våra bidrag adresserar följande problem: I) Tillförlitlig exekvering och tillståndhantering för dataströmmar, II) delning av beräkningar och semantik för Ström Windows, och III) Iterativa dataströmmar. Flera delar av detta arbete har integrerats i Apache Flink, ett allmänt och välkänt beräkningsramverk, och har använts i hundratals storskaliga produktionssystem över hela världen.

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  • 23.
    Castañeda Lozano, Roberto
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS. RISE SICS (Swedish Institute of Computer Science).
    Constraint-Based Register Allocation and Instruction Scheduling2018Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [sv]

    Registerallokering (tilldelning av programvariabler till processorregister eller minne) och instruktionsschemaläggning (omordning av instruktioner för att förbättra latens eller genomströmning) är centrala kompilatorproblem. Denna avhandling presenterar en kombinatorisk optimeringsmetod för dessa problem. Metoden, som är baserad på en formell modell, är kraftfull nog att ge optimala lösningar och göra avvägningar mellan motstridiga optimeringsval. Den kan till fullo uttnyttja processorspecifika funktioner och uttrycka olika optimeringsmål.

    Användningen av villkorsprogrammering och en ny programrepresentation möjliggör en kompakt modell av registerallokering och instruktionsschemaläggning. Modellen omfattar samtliga delproblem som ingår i global registerallokering: spilling, tilldelning, live range splitting, coalescing, load-store-optimering, flertilldelning, registerpackning och rematerialisering. Förutom dessa, kan den också integrera processorspecifika egenskaper som går utanför vad konventionella kompilatorer hanterar.

    Metoden implementeras i Unison, ett öppen-källkods-verktyg som används inom industri- och forskningsvärlden och utgör ett komplement till LLVM-kompilatorn. Unison tillämpar allmänna och problemspecifika villkorslösningstekniker för att skala till medelstora funktioner, lösa funktioner med upp till 647 instruktioner optimalt och förbättra funktioner på upp till 874 instruktioner. Metoden utvärderas experimentellt för olika målprocessorer (Hexagon, ARM och MIPS), benchmark-sviter (MediaBench och SPEC CPU2006) och optimeringsmål (hastighet och kodstorlek). Resultaten visar att Unison genererar kod av något till betydligt bättre kvalitet än LLVM. Den uppskattade hastighetsförbättringen varierar mellan 1% till 9.3% och kodstorleksreduktionen mellan 0.8% till~3.9%, beroende på målprocessor. Ytterligare experiment för Hexagon visar att dess uppskattade hastighetsförbättring har ett starkt monotoniskt förhållande till den faktiska exekveringstiden, vilket resulterar i en 5.4% genomsnittlig hastighetsförbättring för MediaBench-applikationer.

    Denna avhandling beskriver den första praktiskt användbara kombinatoriska optimeringsmetoden för integrerad registerallokering och instruktionsschemaläggning. Metoden är praktiskt användbar då den hanterar samtliga ingående delproblem, genererar exekverbar maskinkod och skalar till medelstora funktioner. Den är också effektiv då den genererar bättre maskinkod än LLVM-kompilatorn. Metoden kan tillämpas för att byta kompileringstid mot kodkvalitet utöver de vanliga optimeringsnivåerna, utforska och utnyttja processorspecifika egenskaper samt identifiera förbättringsmöjligheter i konventionella kompilatorer.

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  • 24.
    Castañeda Lozano, Roberto
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS. RISE SICS, Electrum 229, Kista, 164 40, Sweden.
    Carlsson, M.
    Hjort Blindell, Gabriel
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Schulte, Christian
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS. RISE SICS, Electrum 229, Kista, 164 40, Sweden.
    Combinatorial register allocation and instruction scheduling2019Ingår i: ACM Transactions on Programming Languages and Systems, ISSN 0164-0925, E-ISSN 1558-4593, Vol. 41, nr 3, artikel-id 17Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This article introduces a combinatorial optimization approach to register allocation and instruction scheduling, two central compiler problems. Combinatorial optimization has the potential to solve these problems optimally and to exploit processor-specific features readily. Our approach is the first to leverage this potential in practice: it captures the complete set of program transformations used in state-of-the-art compilers, scales to medium-sized functions of up to 1,000 instructions, and generates executable code. This level of practicality is reached by using constraint programming, a particularly suitable combinatorial optimization technique. Unison, the implementation of our approach, is open source, used in industry, and integrated with the LLVM toolchain. An extensive evaluation confirms that Unison generates better code than LLVM while scaling to medium-sized functions. The evaluation uses systematically selected benchmarks from MediaBench and SPEC CPU2006 and different processor architectures (Hexagon, ARM, MIPS). Mean estimated speedup ranges from 1.1% to 10% and mean code size reduction ranges from 1.3% to 3.8% for the different architectures. A significant part of this improvement is due to the integrated nature of the approach. Executing the generated code on Hexagon confirms that the estimated speedup results in actual speedup. Given a fixed time limit, Unison solves optimally functions of up to 946 instructions, nearly an order of magnitude larger than previous approaches. The results show that our combinatorial approach can be applied in practice to trade compilation time for code quality beyond the usual compiler optimization levels, identify improvement opportunities in heuristic algorithms, and fully exploit processor-specific features.

  • 25.
    Castañeda Lozano, Roberto
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS. RISE SICS (Swedish Institute of Computer Science).
    Carlsson, Mats
    RISE SICS (Swedish Institute of Computer Science).
    Hjort Blindell, Gabriel
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Schulte, Christian
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Combinatorial Register Allocation and Instruction Scheduling2018Rapport (Övrigt vetenskapligt)
    Abstract [en]

    This paper introduces a combinatorial optimization approach to register allocation and instruction scheduling, two central compiler problems. Combinatorial optimization has the potential to solve these problems optimally and to exploit processor-specific features readily. Our approach is the first to leverage this potential in practice: it captures the complete set of program transformations used in state-of-the-art compilers, scales to medium-sized functions of up to 1000 instructions, and generates executable code. This level of practicality is reached by using constraint programming, a particularly suitable combinatorial optimization technique. Unison, the implementation of our approach, is open source, used in industry, and integrated with the LLVM toolchain.

    An extensive evaluation of estimated speed, code size, and scalability confirms that Unison generates better code than LLVM while scaling to medium-sized functions. The evaluation uses systematically selected benchmarks from MediaBench and SPEC CPU2006 and different processor architectures (Hexagon, ARM, MIPS). Mean estimated speedup ranges from 1% to 9.3% and mean code size reduction ranges from 0.8% to 3.9% for the different architectures. Executing the generated code on Hexagon confirms that the estimated speedup indeed results in actual speedup. Given a fixed time limit, Unison solves optimally functions of up to 647 instructions, delivers improved solutions for functions of up to 874 instructions, and achieves more than 85% of the potential speed for 90% of the functions on Hexagon.

    The results in this paper show that our combinatorial approach can be used in practice to trade compilation time for code quality beyond the usual compiler optimization levels, fully exploit processor-specific features, and identify improvement opportunities in existing heuristic algorithms.

  • 26.
    Castañeda Lozano, Roberto
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS. RISE SICS (Swedish Institute of Computer Science).
    Schulte, Christian
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Survey on Combinatorial Register Allocation and Instruction Scheduling2018Ingår i: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Register allocation (mapping variables to processor registers or memory) and instruction scheduling (reordering instructions to increase instruction-level parallelism) are essential tasks for generating efficient assembly code in a compiler. In the last three decades, combinatorial optimization has emerged as an alternative to traditional, heuristic algorithms for these two tasks. Combinatorial optimization approaches can deliver optimal solutions according to a model, can precisely capture trade-offs between conflicting decisions, and are more flexible at the expense of increased compilation time.

    This paper provides an exhaustive literature review and a classification of combinatorial optimization approaches to register allocation and instruction scheduling, with a focus on the techniques that are most applied in this context: integer programming, constraint programming, partitioned Boolean quadratic programming, and enumeration. Researchers in compilers and combinatorial optimization can benefit from identifying developments, trends, and challenges in the area; compiler practitioners may discern opportunities and grasp the potential benefit of applying combinatorial optimization.

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  • 27.
    Castañeda Lozano, Roberto
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS. RISE SICS, Box 1263, S-16440 Kista, Sweden..
    Schulte, Christian
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS. RISE SICS, Box 1263, S-16440 Kista, Sweden..
    Survey on Combinatorial Register Allocation and Instruction Scheduling2019Ingår i: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341, Vol. 52, nr 3, artikel-id 62Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Register allocation (mapping variables to processor registers or memory) and instruction scheduling (reordering instructions to increase instruction-level parallelism) are essential tasks for generating efficient assembly code in a compiler. In the past three decades, combinatorial optimization has emerged as an alternative to traditional, heuristic algorithms for these two tasks. Combinatorial optimization approaches can deliver optimal solutions according to a model, can precisely capture trade-offs between conflicting decisions, and are more flexible at the expense of increased compilation time. This article provides an exhaustive literature review and a classification of combinatorial optimization approaches to register allocation and instruction scheduling, with a focus on the techniques that are most applied in this context: integer programming, constraint programming, partitioned Boolean quadratic programming, and enumeration. Researchers in compilers and combinatorial optimization can benefit from identifying developments, trends, and challenges in the area; compiler practitioners may discern opportunities and grasp the potential benefit of applying combinatorial optimization.

  • 28.
    Castegren, Elias
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Clarke, D.
    Fernandez-Reyes, K.
    Wrigstad, T.
    Yang, A. M.
    Attached and detached closures in actors2018Ingår i: AGERE 2018 - Proceedings of the 8th ACM SIGPLAN International Workshop on Programming Based on Actors, Agents, and Decentralized Control, co-located with SPLASH 2018, Association for Computing Machinery (ACM), 2018, s. 54-61Konferensbidrag (Refereegranskat)
    Abstract [en]

    Expressive actor models combine aspects of functional programming into the pure actor model enriched with futures. Such functional features include first-class closures which can be passed between actors and chained on futures. Combined with mutable objects, this opens the door to race conditions. In some situations, closures may not be evaluated by the actor that created them yet may access fields or objects owned by that actor. In other situations, closures may be safely fired off to run as a separate task. This paper discusses the problem of who can safely evaluate a closure to avoid race conditions, and presents the current solution to the problem adopted by the Encore language. The solution integrates with Encore’s capability type system, which influences whether a closure is attached and must be evaluated by the creating actor, or whether it can be detached and evaluated independently of its creator. Encore’s current solution to this problem is not final or optimal. We conclude by discussing a number of open problems related to dealing with closures in the actor model.

  • 29.
    Castegren, Elias
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Fernandez-Reyes, K.
    Developing a monadic type checker for an object-oriented language: An experience report2019Ingår i: SLE 2019 - Proceedings of the 12th ACM SIGPLAN International Conference on Software Language Engineering, co-located with SPLASH 2019, Association for Computing Machinery, Inc , 2019, s. 184-196Konferensbidrag (Refereegranskat)
    Abstract [en]

    Functional programming languages are well-suited for developing compilers, and compilers for functional languages are often themselves written in a functional language. Functional abstractions, such as monads, allow abstracting away some of the repetitive structure of a compiler, removing boilerplate code and making extensions simpler. Even so, functional languages are rarely used to implement compilers for languages of other paradigms. This paper reports on the experience of a four-year long project where we developed a compiler for a concurrent, object-oriented language using the functional language Haskell. The focus of the paper is the implementation of the type checker, but the design works well in static analysis tools, such as tracking uniqueness of variables to ensure data-race freedom. The paper starts from a simple type checker to which we add more complex features, such as type state, with minimal changes to the overall initial design.

  • 30.
    Castegren, Elias
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Wrigstad, Tobias
    Uppsala Univ, Uppsala, Sweden..
    OOlong: A Concurrent Object Calculus for Extensibility and Reuse2018Ingår i: ACM SIGAPP Applied Computing Review, ISSN 1559-6915, E-ISSN 1931-0161, Vol. 18, nr 4, s. 47-60Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    We present OOlong, an object calculus with interface inheritance, structured concurrency and locks. The goal of the calculus is extensibility and reuse. The semantics are therefore available in a version for LATEX typesetting (written in Ott), a mechanised version for doing rigorous proofs in Coq, and a prototype interpreter (written in OCaml) for typechecking an running OOlong programs.

  • 31. Cremona, F.
    et al.
    Lee, E. A.
    Lohstroh, M.
    Masin, M.
    Broman, David
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Tripakis, S.
    Hybrid Co-simulation: It's about time2018Ingår i: Proceedings - 21st ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS 2018, Association for Computing Machinery, Inc , 2018Konferensbidrag (Refereegranskat)
    Abstract [en]

    Model-based design methodologies are commonly used in industry for the development of cyber-physical systems (CPSs). There are many different languages, tools, and formalisms for model-based design, each with its strengths and weaknesses. Instead of accepting the weaknesses of a particular tool, an alternative is to embrace heterogeneity and develop tool integration platforms and protocols to leverage the strengths from other environments. A fairly recent attempt in this direction is an open interface standard called Functional Mock-up Interface (FMI), which is focused on the convenient exchange and co-simulation of simulation models (Functional Mock-up Units, FMUs), primarily between component suppliers and OEMs. As it stands, FMI has reached acceptance in industry, but its specification (version 2.0) provides only limited support for hybrid co-simulation-simulating systems that mix continuous and discrete behaviors, which are commonly used to model CPSs. This paper identifies FMI's time representation based on floating-point numbers as a key problem, because it does not support well the discrete events that typically occur at the cyber-physical boundary; it is only suitable for modeling continuous dynamics without discrete behaviors. While time is a central concept in reasoning about the physical world, it is largely abstracted away when reasoning about the cyber world. As a result, the engineering methods for CPSs have misaligned abstractions between the physics domain, the mathematical domain used to model physics, the computational domain used to implement these mathematical abstractions for simulation, and the computational domain used on the cyber side of CPSs. The most common resolution for this conundrum is to adopt the naive Newtonian ideal model of time, where time is a real number known everywhere and advancing uniformly. But ironically, Newtonian time proves not so practical for hybrid co-simulation. The obvious reason is that digital computers do not work with real numbers. Whereas real numbers have infinite precision, their floating-point representation does not. This discrepancy leads to unpredictable quantization errors that may accumulate. Although real numbers can be compared for equality (e.g., to define “simultaneity”), it rarely makes sense to do so for floating-point numbers. We show that the approach taken in FMI (and many other modeling frameworks) that embraces a naive Newtonian physical model of time, and a cyber-approximation of this model using floating-point numbers, is inadequate for CPSs; it leads to models with unnecessarily inexplicable, nondeterministic, and complex behaviors. Our analysis concludes that a model of time that solely uses integers solves many of these problems. Specifically, we propose to use a 64-bit unsigned integer representation with arbitrary resolution, given as a power of ten, allowing model parameters specified in decimal to be represented exactly (granted ample resolution). Integer arithmetic is computationally efficient, and, for well-chosen resolutions, this representation will tolerate very long simulations without overflow. It is also easily converted to and from floating-point representations, albeit not losslessly. Given the vast range of time scales used across different simulation models, we believe that choosing a fixed universal time resolution does not make sense. Instead, we describe an algorithm that picks an adequate time resolution for a particular model and we provide procedures for time quantization needed to reconcile discrepacies between internal time representations of co-simulated FMUs. We propose concrete extensions to the FMI standard for the support of hybrid co-simulation that enable the use of integer time, automatic choice of time resolution, and the use of absent signals. We explain in detail how these extensions can be implemented mod-ularly within the frameworks of existing simulation environments and with support for legacy FMUs and superdense time.

  • 32.
    Danglot, Benjamin
    et al.
    Inria Lille Nord Europe, Parc Sci Haute Borne 40,Ave Halley,Bat A,Pk Plaza, F-59650 Villeneuve Dascq, France..
    Vera-Perez, Oscar Luis
    Inria Rennes Bretagne Atlantique, Campus Beaulieu,263 Ave Gen Leclerc, F-35042 Rennes, France..
    Baudry, Benoit
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Monperrus, Martin
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Teoretisk datalogi, TCS.
    Automatic test improvement with DSpot: a study with ten mature open-source projects2019Ingår i: Journal of Empirical Software Engineering, ISSN 1382-3256, E-ISSN 1573-7616, Vol. 24, nr 4, s. 2603-2635Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In the literature, there is a rather clear segregation between manually written tests by developers and automatically generated ones. In this paper, we explore a third solution: to automatically improve existing test cases written by developers. We present the concept, design and implementation of a system called DSpot, that takes developer-written test cases as input (JUnit tests in Java) and synthesizes improved versions of them as output. Those test improvements are given back to developers as patches or pull requests, that can be directly integrated in the main branch of the test code base. We have evaluated DSpot in a deep, systematic manner over 40 real-world unit test classes from 10 notable and open-source software projects. We have amplified all test methods from those 40 unit test classes. In 26/40 cases, DSpot is able to automatically improve the test under study, by triggering new behaviors and adding new valuable assertions. Next, for ten projects under consideration, we have proposed a test improvement automatically synthesized by DSpot to the lead developers. In total, 13/19 proposed test improvements were accepted by the developers and merged into the main code base. This shows that DSpot is capable of automatically improving unit-tests in real-world, large scale Java software.

  • 33.
    Danglot, Benjamin
    et al.
    INRIA, Lille, France..
    Vera-Perez, Oscar
    INRIA, Rennes, France..
    Yu, Zhongxing
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Teoretisk datalogi, TCS.
    Zaidman, Andy
    Delft Univ Technol, Delft, Netherlands..
    Monperrus, Martin
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Teoretisk datalogi, TCS.
    Baudry, Benoit
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    A snowballing literature study on test amplification2019Ingår i: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 157, artikel-id UNSP 110398Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The adoption of agile approaches has put an increased emphasis on testing, resulting in extensive test suites. These suites include a large number of tests, in which developers embed knowledge about meaningful input data and expected properties as oracles. This article surveys works that exploit this knowledge to enhance manually written tests with respect to an engineering goal (e.g., improve coverage or refine fault localization). While these works rely on various techniques and address various goals, we believe they form an emerging and coherent field of research, which we coin "test amplification". We devised a first set of papers from DBLP, searching for all papers containing "test" and "amplification" in their title. We reviewed the 70 papers in this set and selected the 4 papers that fit the definition of test amplification. We use them as the seeds for our snowballing study, and systematically followed the citation graph. This study is the first that draws a comprehensive picture of the different engineering goals proposed in the literature for test amplification. We believe that this survey will help researchers and practitioners entering this new field to understand more quickly and more deeply the intuitions, concepts and techniques used for test amplification.

  • 34.
    Durieux, Thomas
    et al.
    Univ Lille, Lille, France.;INRIA, Le Chesnay, France..
    Hamadi, Youssef
    Ecole Polytech, Palaiseau, France..
    Yu, Zhongxing
    Univ Lille, Lille, France.;INRIA, Le Chesnay, France..
    Baudry, Benoit
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Monperrus, Martin
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Teoretisk datalogi, TCS.
    Exhaustive Exploration of the Failure-oblivious Computing Search Space2018Ingår i: 2018 IEEE 11TH INTERNATIONAL CONFERENCE ON SOFTWARE TESTING, VERIFICATION AND VALIDATION (ICST), IEEE Press, 2018, s. 139-149Konferensbidrag (Refereegranskat)
    Abstract [en]

    High-availability of software systems requires automated handling of crashes in presence of errors. Failure-oblivious computing is one technique that aims to achieve high availability. We note that failure-obliviousness has not been studied in depth yet, and there is very few study that helps understand why failure-oblivious techniques work. In order to make failure-oblivious computing to have an impact in practice, we need to deeply understand failure-oblivious behaviors in software. In this paper, we study, design and perform an experiment that analyzes the size and the diversity of the failure-oblivious behaviors. Our experiment consists of exhaustively computing the search space of 16 field failures of large-scale open-source Java software. The outcome of this experiment is a much better understanding of what really happens when failure-oblivious computing is used, and this opens new promising research directions.

  • 35.
    Edman, Henrik
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Sequential Pattern Mining on Electronic Medical Records for Finding Optimal Clinical Pathways2018Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Electronic Medical Records (EMRs) är digitala versioner av behandlingshistoriken för patienter på sjukhus. Clinical pathways används som riktlinjer för hur olika sjukdomar borde behandlas, vilka bestäms genom att observera utkomsten av tidigare behandlingar. Sequential pattern mining är en typ av data mining där datan som behandlas är strukturerad i sekvenser. Det är ett vanligt forskningsområde inom data mining där många nya variationer av existerande algoritmer introduceras frekvent. I en tidigare rapport användes sequential pattern mining algoritmen PrefixSpan på EMRs för att verifiera eller föreslå nya clinical pathways. Den kunde dock endast verifiera pathways delvis. En av anledningarna som nämndes för detta var att PrefixSpan var för ineffektiv för att kunna köras med en tillräckligt låg support för att kunna finna vissa åtgärder i en behandling. I den här rapporten används istället CSpan, eftersom den ska överprestera PrefixSpan med upp till två storleksordningar, för att förbättra körningstiden och därmed adressera problemen som nämns i den tidigare rapporten. Resultaten visar att CSpan förbättrade körningstiden och algoritmen kunde köras med lägre support. Däremot blev utdatan knappt förbättrad.

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  • 36.
    Engelin, Martin
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    CapsNet Comprehension of Objects in Different Rotational Views: A comparative study of capsule and convolutional networks2018Självständigt arbete på avancerad nivå (masterexamen), 20 poäng / 30 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Capsule network (CapsNet) är en ny typ av neuralt nätverk för datorseende, som framförallt presterar bra även då bilderna är förvrängda eller sedda från obekanta vinklar. Den här uppsatsen testar CapsNets förmåga att förstå klädesobjekt sedda ur olika synviklar genom att göra en jämförelse med ConvNets. Resultaten visar att, trots att ConvNets har en högre exakthet i sin klassificering, är CapsNets bättre på att förstå kläderna sedda från olika synvinklar.

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  • 37.
    Fernando, Tharidu
    et al.
    KTH.
    Gureev, Nikita
    KTH.
    Matskin, Mihhail
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Zwick, M.
    Natschlager, T.
    WorkflowDSL: Scalable Workflow Execution with Provenance for Data Analysis Applications2018Ingår i: Proceedings - International Computer Software and Applications Conference, IEEE Computer Society , 2018, s. 774-779Konferensbidrag (Refereegranskat)
    Abstract [en]

    Data analysis projects typically use different programming languages (from Python for prototyping to C++ for support of runtime constraints) at their different stages by different experts. This creates a need for a data processing framework that is re-usable across multiple programming languages and supports collaboration of experts. In this work, we discuss implementation of a framework which uses a Domain Specific Language (DSL), called WorkflowDSL, that enables domain experts to collaborate on fine-tuning workflows. The framework includes support for parallel execution without any specialized code. It also provides a provenance capturing framework that enables users to analyse past executions and retrieve complete lineage of any data item generated. Graph database is used for storing provenance data. Advantages of usage of a graph database compare to relational databases are demonstrated. Experiments which were performed using a real-world scientific workflow from the bioinformatics domain and industrial data analysis models show that users were able to execute workflows efficiently when using WorkflowDSL for workflow composition and Python for task implementations. Moreover, we show that capturing provenance data can be useful for analysing past workflow executions.

  • 38.
    Forsell, Erik
    et al.
    Karolinska Inst, Ctr Psychiat Res, Dept Clin Neurosci, Internetpsykiatrienheten M58, S-14120 Stockholm, Sweden.;Stockholm Hlth Care Serv, Internetpsykiatrienheten M58, S-14120 Stockholm, Sweden..
    Isacsson, Nils
    Karolinska Inst, Ctr Psychiat Res, Dept Clin Neurosci, Internetpsykiatrienheten M58, S-14120 Stockholm, Sweden.;Stockholm Hlth Care Serv, Internetpsykiatrienheten M58, S-14120 Stockholm, Sweden..
    Blom, Kerstin
    Karolinska Inst, Ctr Psychiat Res, Dept Clin Neurosci, Internetpsykiatrienheten M58, S-14120 Stockholm, Sweden.;Stockholm Hlth Care Serv, Internetpsykiatrienheten M58, S-14120 Stockholm, Sweden..
    Jernelov, Susanna
    Karolinska Inst, Ctr Psychiat Res, Dept Clin Neurosci, Internetpsykiatrienheten M58, S-14120 Stockholm, Sweden.;Stockholm Hlth Care Serv, Internetpsykiatrienheten M58, S-14120 Stockholm, Sweden..
    Ben Abdesslem, Fehmi
    RISE Res Inst Sweden, Stockholm, Sweden..
    Lindefors, Nils
    Karolinska Inst, Ctr Psychiat Res, Dept Clin Neurosci, Internetpsykiatrienheten M58, S-14120 Stockholm, Sweden.;Stockholm Hlth Care Serv, Internetpsykiatrienheten M58, S-14120 Stockholm, Sweden..
    Boman, Magnus
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Kaldo, Viktor
    Karolinska Inst, Ctr Psychiat Res, Dept Clin Neurosci, Internetpsykiatrienheten M58, S-14120 Stockholm, Sweden.;Stockholm Hlth Care Serv, Internetpsykiatrienheten M58, S-14120 Stockholm, Sweden.;Linnaeus Univ, Dept Psychol, Fac Hlth & Life Sci, Vaxjo, Sweden..
    Predicting Treatment Failure in Regular Care Internet-Delivered Cognitive Behavior Therapy for Depression and Anxiety Using Only Weekly Symptom Measures2020Ingår i: Journal of Consulting and Clinical Psychology, ISSN 0022-006X, E-ISSN 1939-2117, Vol. 88, nr 4, s. 311-321Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Objective: Therapist guided Internet-Delivered Cognitive Behavior Therapy (ICBT) is effective, but as in traditional CBT, not all patients improve, and clinicians generally fail to identify them early enough. We predict treatment failure in 12-week regular care ICBT for Depression, Panic disorder and Social anxiety disorder, using only patients' weekly symptom ratings to identify when the accuracy of predictions exceed 2 benchmarks: (a) chance, and (b) empirically derived clinician preferences for actionable predictions. Method: Screening, pretreatment and weekly symptom ratings from 4310 regular care ICBT-patients from the Internet Psychiatry Clinic in Stockholm, Sweden was analyzed in a series of regression models each adding 1 more week of data. Final score was predicted in a holdout test sample, which was then categorized into Success or Failure (failure defined as the absence of both remitter and responder status). Classification analyses with Balanced Accuracy and 95% Confidence intervals was then compared to predefined benchmarks. Results: Benchmark 1 (better than chance) was reached 1 week into all treatments. Social anxiety disorder reached Benchmark 2 (>65%) at week 5, whereas Depression and Panic Disorder reached it at week 6. Conclusions: For depression, social anxiety and panic disorder, prediction with only patient-rated symptom scores can detect treatment failure 6 weeks into ICBT, with enough accuracy for a clinician to take action. Early identification of failing treatment attempts may be a viable way to increase the overall success rate of existing psychological treatments by providing extra clinical resources to at-risk patients, within a so-called Adaptive Treatment Strategy.

  • 39.
    Frimodig, Sara
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.), Optimeringslära och systemteori.
    Schulte, Christian
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Models for Radiation Therapy Patient Scheduling2019Ingår i: 25th International Conference on Principles and Practice of Constraint Programming, CP 2019, Springer, 2019, Vol. 11802, s. 421-437Konferensbidrag (Refereegranskat)
    Abstract [en]

    In Europe, around half of all patients diagnosed with cancer are treated with radiation therapy. To reduce waiting times, optimizing the use of linear accelerators for treatment is crucial. This paper introduces an Integer Programming (IP) and two Constraint Programming (CP) models for the non-block radiotherapy patient scheduling problem. Patients are scheduled considering priority, pattern, duration, and start day of their treatment. The models include expected future patient arrivals. Treatment time of the day is included in the models as time windows which enable more realistic objectives and constraints. The models are thoroughly evaluated for multiple different scenarios, altering: planning day, machine availability, arrival rates, patient backlog, and the number of time windows in a day. The results demonstrate that the CP models find feasible solutions earlier, while the IP model reaches optimality considerably faster.

  • 40. Galindo, J. A.
    et al.
    Alférez, M.
    Acher, M.
    Baudry, Benoit
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Benavides, D.
    MOTIV: Selección de pruebas para algoritmos de detección de movimiento en vídeos usando técnicas de líneas de productos software2018Ingår i: Actas de las 23rd Jornadas de Ingenieria del Software y Bases de Datos, JISBD 2018, Sistedes , 2018Konferensbidrag (Refereegranskat)
  • 41.
    Gammerman, Alexander
    et al.
    Royal Holloway Univ London, Egham, Surrey, England..
    Vovk, Vladimir
    Royal Holloway Univ London, Egham, Surrey, England..
    Boström, Henrik
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Carlsson, Lars
    Stena Line AB, Gothenburg, Sweden..
    Conformal and probabilistic prediction with applications: editorial2019Ingår i: Machine Learning, ISSN 0885-6125, E-ISSN 1573-0565, Vol. 108, nr 3, s. 379-380Artikel i tidskrift (Övrigt vetenskapligt)
  • 42.
    Garcia Lozano, Marianela
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS. FOI Swedish Defence Research Agency, Stockholm, SE-164 90, Sweden.
    Brynielsson, Joel
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Teoretisk datalogi, TCS. FOI Swedish Defence Research Agency, Stockholm, SE-164 90, Sweden.
    Franke, Ulrik
    RISE Res Inst Sweden, POB 1263, SE-16429 Kista, Sweden..
    Rosell, Magnus
    FOI Swedish Def Res Agcy, SE-16490 Stockholm, Sweden..
    Tjörnhammar, Edward
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS. FOI Swedish Defence Research Agency, Stockholm, SE-164 90, Sweden.
    Varga, Stefan
    KTH. Swedish Armed Forces Headquarters, Stockholm, SE-107 85, Sweden.
    Vlassov, Vladimir
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Veracity assessment of online data2020Ingår i: Decision Support Systems, ISSN 0167-9236, E-ISSN 1873-5797, Vol. 129, artikel-id 113132Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Fake news, malicious rumors, fabricated reviews, generated images and videos, are today spread at an unprecedented rate, making the task of manually assessing data veracity for decision-making purposes a daunting task. Hence, it is urgent to explore possibilities to perform automatic veracity assessment. In this work we review the literature in search for methods and techniques representing state of the art with regard to computerized veracity assessment. We study what others have done within the area of veracity assessment, especially targeted towards social media and open source data, to understand research trends and determine needs for future research. The most common veracity assessment method among the studied set of papers is to perform text analysis using supervised learning. Regarding methods for machine learning much has happened in the last couple of years related to the advancements made in deep learning. However, very few papers make use of these advancements. Also, the papers in general tend to have a narrow scope, as they focus on solving a small task with only one type of data from one main source. The overall veracity assessment problem is complex, requiring a combination of data sources, data types, indicators, and methods. Only a few papers take on such a broad scope, thus, demonstrating the relative immaturity of the veracity assessment domain.

  • 43.
    Ghoorchian, Kambiz
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Graph Algorithms for Large-Scale and Dynamic Natural Language Processing2019Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    In Natural Language Processing, researchers design and develop algorithms to enable machines to understand and analyze human language. These algorithms benefit multiple downstream applications including sentiment analysis, automatic translation, automatic question answering, and text summarization. Topic modeling is one such algorithm that solves the problem of categorizing documents into multiple groups with the goal of maximizing the intra-group document similarity. However, the manifestation of short texts like tweets, snippets, comments, and forum posts as the dominant source of text in our daily interactions and communications, as well as being the main medium for news reporting and dissemination, increases the complexity of the problem due to scalability, sparsity, and dynamicity. Scalability refers to the volume of the messages being generated, sparsity is related to the length of the messages, and dynamicity is associated with the ratio of changes in the content and topical structure of the messages (e.g., the emergence of new phrases). We improve the scalability and accuracy of Natural Language Processing algorithms from three perspectives, by leveraging on innovative graph modeling and graph partitioning algorithms, incremental dimensionality reduction techniques, and rich language modeling methods. We begin by presenting a solution for multiple disambiguation on short messages, as opposed to traditional single disambiguation. The solution proposes a simple graph representation model to present topical structures in the form of dense partitions in that graph and applies disambiguation by extracting those topical structures using an innovative distributed graph partitioning algorithm. Next, we develop a scalable topic modeling algorithm using a novel dense graph representation and an efficient graph partitioning algorithm. Then, we analyze the effect of temporal dimension to understand the dynamicity in online social networks and present a solution for geo-localization of users in Twitter using a hierarchical model that combines partitioning of the underlying social network graph with temporal categorization of the tweets. The results show the effect of temporal dynamicity on users’ spatial behavior. This result leads to design and development of a dynamic topic modeling solution, involving an online graph partitioning algorithm and a significantly stronger language modeling approach based on the skip-gram technique. The algorithm shows strong improvement on scalability and accuracy compared to the state-of-the-art models. Finally, we describe a dynamic graph-based representation learning algorithm that modifies the partitioning algorithm to develop a generalization of our previous work. A strong representation learning algorithm is proposed that can be used for extracting high quality distributed and continuous representations out of any sequential data with local and hierarchical structural properties similar to natural language text.

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  • 44.
    Ghoorchian, Kambiz
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Girdzijauskas, Sarunas
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Spatio-Temporal Multiple Geo-Location Identification on Twitter2018Ingår i: Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018 / [ed] Abe, N Liu, H Pu, C Hu, X Ahmed, N Qiao, M Song, Y Kossmann, D Liu, B Lee, K Tang, J He, J Saltz, J, Institute of Electrical and Electronics Engineers (IEEE), 2018, s. 3412-3421Konferensbidrag (Refereegranskat)
    Abstract [en]

    Twitter Geo-tags that indicate the exact location of messages have many applications from localized opinion mining during elections to efficient traffic management in critical situations. However, less than 6% of Tweets are Geo-tagged, which limits the implementation of those applications. There are two groups of solutions: content and network-based. The first group uses location indicative factors like URLs and topics, extracted from the content of tweets, to infer Geo-location for non geoactive users, whereas the second group benefits from friendship ties in the underlying social network graph. Friendship ties are better predictors compared to content information because they are less noisy and often follow the natural human spatial movement patterns. However, their prediction's accuracy is still limited because they ignore the temporal aspects of human behavior and always assume a single location per user. This research aims to extend the current network-based approaches by taking users' temporal dimension into account. We assume multiple locations per user during different time-slots and hypothesize that location predictability varies depending on the time and the properties of the social membership group. Thus, we propose a hierarchical solution to apply temporal categorizations on top of social network partitioning for multiple location prediction for users in Online Social Networks (OSNs) like Twitter. Given a largescale Twitter dataset, we show that users' location predictability exhibits different behavior in different time-slots and different social groups. We find that there are specific conditions where users are more predictable in terms of Geo-location. Our solution outperforms the state-of-the-art by improving the prediction accuracy by 16:6% in terms of Median Error Distance (MED) over the same recall.

  • 45.
    Ghoorchian, Kambiz
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Sahlgren, Magnus
    Research Institute of Sweden (RISE).
    GDTM: Graph-based Dynamic Topic ModelsIngår i: Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Dynamic Topic Modeling (DTM) is the ultimate solution for extracting topics from short texts generated in Online Social Networks (OSNs) like Twitter. A DTM solution is required to be scalable and to be able to account for sparsity in short texts and dynamicity of topics. Current solutions combine probabilistic mixture models like Dirichlet Multinomial or PitmanYor Process with approximate inference approaches like Gibbs Sampling and Stochastic Variational Inference to, respectively, account for dynamicity and scalability in DTM. However, these solutions rely on weak probabilistic language models, which do not account for sparsity in short texts. In addition, their inference is based on iterative optimization algorithms, which have scalability issues when it comes to DTM. We present GDTM, a single-pass graph-based DTM algorithm, to solve the problem. GDTM combines a context-rich and incremental feature representation model, called Random Indexing (RI), with a novel online graph partitioning algorithm to address scalability and dynamicity. In addition, GDTM uses a rich language modeling approach based on the Skip-gram technique to account for sparsity. We run multiple experiments over a large-scale Twitter dataset to analyze the accuracy and scalability of GDTM and compare the results with four state-of-the-art approaches. The results show that GDTM outperforms the best approach by 11% on accuracy and performs by an order of magnitude faster while creating 4 times better topic quality over standard evaluation metrics.

  • 46.
    Giaretta, Lodovico
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Girdzijauskas, Sarunas
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    Gossip Learning: Off the Beaten Path2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    The growing computational demands of model training tasks and the increased privacy awareness of consumers call for the development of new techniques in the area of machine learning. Fully decentralized approaches have been proposed, but are still in early research stages. This study analyses gossip learning, one of these state-of-the-art decentralized machine learning protocols, which promises high scalability and privacy preservation, with the goal of assessing its applicability to realworld scenarios.

    Previous research on gossip learning presents strong and often unrealistic assumptions on the distribution of the data, the communication speeds of the devices and the connectivity among them. Our results show that lifting these requirements can, in certain scenarios, lead to slow convergence of the protocol or even unfair bias in the produced models. This paper identifies the conditions in which gossip learning can and cannot be applied, and introduces extensions that mitigate some of its limitations.

  • 47. Gomes, Claudio
    et al.
    Thule, Casper
    Broman, David
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Larsen, Peter Gorm
    Vangheluwe, Hans
    Co-Simulation: A Survey2018Ingår i: ACM Computing Surveys, ISSN 0360-0300, E-ISSN 1557-7341, Vol. 51, nr 3, artikel-id 49Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Modeling and simulation techniques are today extensively used both in industry and science. Parts of larger systems are, however, typically modeled and simulated by different techniques, tools, and algorithms. In addition, experts from different disciplines use various modeling and simulation techniques. Both these facts make it difficult to study coupled heterogeneous systems. Co-simulation is an emerging enabling technique, where global simulation of a coupled system can be achieved by composing the simulations of its parts. Due to its potential and interdisciplinary nature, cosimulation is being studied in different disciplines but with limited sharing of findings. In this survey, we study and survey the state-of-the-art techniques for co-simulation, with the goal of enhancing future research and highlighting the main challenges. To study this broad topic, we start by focusing on discrete-event-based co-simulation, followed by continuous-time-based co-simulation. Finally, we explore the interactions between these two paradigms, in hybrid co-simulation. To survey the current techniques, tools, and research challenges, we systematically classify recently published research literature on co-simulation, and summarize it into a taxonomy. As a result, we identify the need for finding generic approaches for modular, stable, and accurate coupling of simulation units, as well as expressing the adaptations required to ensure that the coupling is correct.

  • 48.
    Gomez-Boix, Alejandro
    et al.
    Univ Rennes, INRIA, CNRS, IRISA, Rennes, France. audry, Benoit.
    perdrix, Pierre
    Baudry, Benoit
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Hiding in the Crowd: an Analysis of the Effectiveness of Browser ngerprinting at Large Scale2018Ingår i: WEB CONFERENCE 2018: PROCEEDINGS OF THE WORLD WIDE WEB CONFERENCE (WW2018), Association for Computing Machinery (ACM), 2018, s. 309-318Konferensbidrag (Refereegranskat)
    Abstract [en]

    Browser fingerprinting is a stateless technique, which consists in collecting a wide range of data about a device through browser APIs. Past studies have demonstrated that modern devices present so much diversity that fingerprints can be exploited to identify and track users online. With this work, we want to evaluate if browser fingerprinting is still effective at uniquely identifying a large group of users when analyzing millions of fingerprints over a few months. We collected 2,067,942 browser fingerprints from one of the top 15 French websites. The analysis of this novel dataset sheds a new light on the ever-growing browser fingerprinting domain. The key insight is that the percentage of unique fingerprints in our dataset is much lower than what was reported in the past: only 33.6% of fingerprints are unique by opposition to over 80% in previous studies. We show that non-unique fingerprints tend to be fragile. If some features of the fingerprint change, it is very probable that the fingerprint will become unique. We also confirm that the current evolution of web technologies is benefiting users' privacy significantly as the removal of plugins brings down substantively the rate of unique desktop machines.

  • 49. Gómez-Boix, A.
    et al.
    Frey, D.
    Bromberg, Y. -D
    Baudry, Benoit
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Datavetenskap, Programvaruteknik och datorsystem, SCS.
    A collaborative strategy for mitigating tracking through browser fingerprinting2019Ingår i: Proceedings of the ACM Conference on Computer and Communications Security, Association for Computing Machinery , 2019, s. 67-78Konferensbidrag (Refereegranskat)
    Abstract [en]

    Browser fingerprinting is a technique that collects information about the browser configuration and the environment in which it is running. This information is so diverse that it can partially or totally identify users online. Over time, several countermeasures have emerged to mitigate tracking through browser fingerprinting. However, these measures do not offer full coverage in terms of privacy protection, as some of them may introduce inconsistencies or unusual behaviors, making these users stand out from the rest. We address these limitations by proposing a novel approach that minimizes both the identifiability of users and the required changes to browser configuration. To this end, we exploit clustering algorithms to identify the devices that are prone to share the same or similar fingerprints and to provide them with a new non-unique fingerprint. We then use this fingerprint to automatically assemble and run web browsers through virtualization within a docker container. Thus all the devices in the same cluster will end up running a web browser with an indistinguishable and consistent fingerprint.

  • 50.
    Hakimzadeh, Kamal
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS.
    Dowling, Jim
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Programvaruteknik och datorsystem, SCS. Logical Clocks AB, Stockholm, Sweden.
    Karamel: A System for Timely Provisioning Large-Scale Software Across IaaS Clouds2019Ingår i: 2019 IEEE 12th International Conference on Cloud Computing (CLOUD), IEEE Computer Society, 2019, s. 391-395, artikel-id 8814511Konferensbidrag (Refereegranskat)
    Abstract [en]

    Cloud-native systems and application software platforms are becoming increasingly complex, and, ideally, they are expected to be quick to launch, elastic, portable across different cloud environments and easily managed. However, as cloud applications increase in complexity, so do the resultant challenges in configuring such applications, and orchestrating the deployment of their constituent services on potentially different cloud operating systems and environments.

    This paper presents a new orchestration system called Karamel that addresses these challenges by providing a cloud-independent orchestration service for deploying and configuring cloud applications and platforms across different environments. In Karamel, we model configuration routines with their dependencies in composable modules, and we achieve a high level of configuration/deployment parallelism by using techniques such as DAG traversal control logic, dataflow variable binding, and parallel actuation. In Karamel, complex distributed deployments are specified declaratively in a compact YAML syntax, and cluster definitions can be validated using an external artifact repository (GitHub).

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