TestSelector: Automatic Test Suite Selection for Student Projects
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F22%3A00364213" target="_blank" >RIV/68407700:21730/22:00364213 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-031-17196-3_17" target="_blank" >https://doi.org/10.1007/978-3-031-17196-3_17</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-17196-3_17" target="_blank" >10.1007/978-3-031-17196-3_17</a>
Alternative languages
Result language
angličtina
Original language name
TestSelector: Automatic Test Suite Selection for Student Projects
Original language description
Computer Science course instructors routinely have to create comprehensive test suites to assess programming assignments. The creation of such test suites is typically not trivial as it involves selecting a limited number of tests from a set of (semi-)randomly generated ones. Manual strategies for test selection do not scale when considering large testing inputs needed, for instance, for the assessment of algorithms exercises. To facilitate this process, we present TESTSELECTOR, a new framework for automatic selection of optimal test suites for student projects. The key advantage of TESTSELECTOR over existing approaches is that it is easily extensible with arbitrarily complex code coverage measures, not requiring these measures to be encoded into the logic of an exact constraint solver. We demonstrate the flexibility of TESTSELECTOR by extending it with support for a range of classical code coverage measures and using it to select test suites for a number of real-world algorithms projects, further showing that the selected test suites outperform randomly selected ones in finding bugs in students’ code.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LL1902" target="_blank" >LL1902: Powering SMT Solvers by Machine Learning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Runtime Verification 22nd International Conference, RV 2022, Tbilisi, Georgia, September 28–30, 2022, Proceedings
ISBN
978-3-031-17195-6
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
10
Pages from-to
283-292
Publisher name
Springer
Place of publication
Cham
Event location
Tbilisi
Event date
Sep 28, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000866539700017