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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

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • 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