Gesellschaft für Informatik e.V.

Lecture Notes in Informatics


Software Engineering 2016 P-252, 15-16 (2016).

Gesellschaft für Informatik, Bonn
2016


Copyright © Gesellschaft für Informatik, Bonn

Contents

Guiding random test generation with program analysis

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

Abstract


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.


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Gesellschaft für Informatik, Bonn
ISBN 978-3-88579-646-6


Last changed 25.02.2016 18:38:57