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DUETS: A Dataset of Reproducible Pairs of Java Library-Clients
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.ORCID iD: 0000-0002-1996-6134
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.ORCID iD: 0000-0003-0541-6411
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.ORCID iD: 0000-0002-4015-4640
2021 (English)In: 2021 IEEE/Acm 18Th International Conference On Mining Software Repositories (MSR 2021), Institute of Electrical and Electronics Engineers (IEEE) , 2021, p. 545-549Conference paper, Published paper (Refereed)
Abstract [en]

Software engineering researchers look for software artifacts to study their characteristics or to evaluate new techniques. In this paper, we introduce DUETS, a new dataset of software libraries and their clients. This dataset can be exploited to gain many different insights, such as API usage, usage inputs, or novel observations about the test suites of clients and libraries. DUETS is meant to support both static and dynamic analysis. This means that the libraries and the clients compile correctly, they are executable and their test suites pass. The dataset is composed of open-source projects that have more than five stars on GitHub. The final dataset contains 395 libraries and 2;874 clients. Additionally, we provide the raw data that we use to create this dataset, such as 34;560 pom.xml files or the complete file list from 34;560 projects. This dataset can be used to study how libraries are used by their clients or as a list of software projects that successfully build. The client's test suite can be used as an additional verification step for code transformation techniques that modify the libraries.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2021. p. 545-549
Series
IEEE International Working Conference on Mining Software Repositories, ISSN 2160-1852
Keywords [en]
Mining software repositories, software reuse, Java, Maven
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:kth:diva-303381DOI: 10.1109/MSR52588.2021.00071ISI: 000693399500059Scopus ID: 2-s2.0-85108531256OAI: oai:DiVA.org:kth-303381DiVA, id: diva2:1602849
Conference
29th IEEE/ACM International Conference on Program Comprehension (ICPC) / 18th IEEE/ACM International Conference on Mining Software Repositories (MSR), MAY 22-30, 2021, ELECTR NETWORK
Note

Part of proceedings: ISBN 978-1-7281-8710-5, QC 20230117

Available from: 2021-10-13 Created: 2021-10-13 Last updated: 2023-01-17Bibliographically approved

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Durieux, ThomasSoto Valero, CésarBaudry, Benoit

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