Guiding random test generation with program analysis

Lei Ma, Cyrille Artho, Cheng Zhang, Hiroyuki Sato, Johannes Gmeiner, Rudolf Ramler

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

抄録

Random test generation is effective in creating method sequences for exercising the software under test. However, black-box approaches for random testing are known to suffer from low code coverage and limited defect detection ability. Analyzing the software under test and using the extracted knowledge to guide test generation can help to overcome these limitations. We developed a random test case generator augmented by a combination of six static and dynamic program analysis techniques. Our tool GRT (Guided Random Testing) has been evaluated on realworld software systems as well as Defects4J benchmarks. It outperformed related approaches in terms of code coverage, mutation score and detected faults. The results show a considerable improvement potential of random test generation when combined with advanced analysis techniques.

本文言語英語
ホスト出版物のタイトルSoftware Engineering 2016
編集者Jens Knoop, Uwe Zdun
出版社Gesellschaft fur Informatik (GI)
ページ15-16
ページ数2
ISBN(電子版)9783885796466
出版ステータス出版済み - 1 1 2016
外部発表はい
イベントSoftware Engineering-Konferenz, SE 2016 - Software Engineering Conference, SE 2016 - Wien, オーストリア
継続期間: 2 23 20162 26 2016

出版物シリーズ

名前Lecture Notes in Informatics (LNI), Proceedings - Series of the Gesellschaft fur Informatik (GI)
P252
ISSN(印刷版)1617-5468

会議

会議Software Engineering-Konferenz, SE 2016 - Software Engineering Conference, SE 2016
Countryオーストリア
CityWien
Period2/23/162/26/16

All Science Journal Classification (ASJC) codes

  • Computer Science Applications

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