Code Coverage Aware Test Generation Using Constraint Solver

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F20%3A00346427" target="_blank" >RIV/68407700:21230/20:00346427 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/978-3-030-67220-1_5" target="_blank" >https://doi.org/10.1007/978-3-030-67220-1_5</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-67220-1_5" target="_blank" >10.1007/978-3-030-67220-1_5</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Code Coverage Aware Test Generation Using Constraint Solver

Popis výsledku v původním jazyce

Code coverage has been used in the software testing context mostly as a metric to assess a generated test suite’s quality. Recently, code coverage analysis is used as a white-box testing technique for test optimization. Most of the research activities focus on using code coverage for test prioritization and selection within automated testing strategies. Less effort has been paid in the literature to use code coverage for test generation. This paper introduces a new Code Coverage-based Test Case Generation (CCTG) concept that changes the current practices by utilizing the code coverage analysis in the test generation process. CCTG uses the code coverage data to calculate the input parameters’ impact for a constraint solver to automate the generation of effective test suites. We applied this approach to a few real-world case studies. The results showed that the new test generation approach could generate effective test cases and detect new faults.

Název v anglickém jazyce

Code Coverage Aware Test Generation Using Constraint Solver

Popis výsledku anglicky

Code coverage has been used in the software testing context mostly as a metric to assess a generated test suite’s quality. Recently, code coverage analysis is used as a white-box testing technique for test optimization. Most of the research activities focus on using code coverage for test prioritization and selection within automated testing strategies. Less effort has been paid in the literature to use code coverage for test generation. This paper introduces a new Code Coverage-based Test Case Generation (CCTG) concept that changes the current practices by utilizing the code coverage analysis in the test generation process. CCTG uses the code coverage data to calculate the input parameters’ impact for a constraint solver to automate the generation of effective test suites. We applied this approach to a few real-world case studies. The results showed that the new test generation approach could generate effective test cases and detect new faults.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Software Engineering and Formal Methods. SEFM 2020 Collocated Workshops

ISBN

978-3-030-67219-5

ISSN

0302-9743

e-ISSN

1611-3349

Počet stran výsledku

9

Strana od-do

58-66

Název nakladatele

Springer Nature Switzerland AG

Místo vydání

Basel

Místo konání akce

Amsterdam

Datum konání akce

14. 9. 2020

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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