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A snowballing literature study on test amplification
INRIA, Lille, France..
INRIA, Rennes, France..
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Theoretical Computer Science, TCS.
Delft Univ Technol, Delft, Netherlands..
Show others and affiliations
2019 (English)In: Journal of Systems and Software, ISSN 0164-1212, E-ISSN 1873-1228, Vol. 157, article id UNSP 110398Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Elsevier, 2019. Vol. 157, article id UNSP 110398
Keywords [en]
Test amplification, Test augmentation, Test optimization, Test regeneration, Automatic testing
National Category
Computer and Information Sciences
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:kth:diva-262765DOI: 10.1016/j.jss.2019.110398ISI: 000488137500009Scopus ID: 2-s2.0-85070967135OAI: oai:DiVA.org:kth-262765DiVA, id: diva2:1363140
Funder
Wallenberg AI, Autonomous Systems and Software Program (WASP)
Note

QC 20191022

Available from: 2019-10-22 Created: 2019-10-22 Last updated: 2019-11-26Bibliographically approved

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Monperrus, MartinBaudry, Benoit

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