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Do Automatically Generated Unit Tests Find Real Faults? An Empirical Study of Effectiveness and Challenges
Shamshiri, Sina; Just, Rene; Rojas, Jose Miguel et al.
2015In Proceedings of the 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)
Peer reviewed
 

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Abstract :
[en] Rather than tediously writing unit tests manually, tools can be used to generate them automatically — sometimes even resulting in higher code coverage than manual testing. But how good are these tests at actually finding faults? To answer this question, we applied three state-of-the art unit test generation tools for Java (Randoop, EvoSuite, and Agitar) to the 357 faults in the Defects4J dataset and investigated how well the generated test suites perform at detecting faults. Although 55.7% of the faults were found by automatically generated tests overall, only 19.9% of the test suites generated in our experiments actually detected a fault. By studying the performance and the problems of the individual tools and their tests, we derive insights to support the development of automated unit test generators, in order to increase the fault detection rate in the future. These include 1) improving coverage obtained so that defective statements are actually executed in the first instance, 2) techniques for propagating faults to the output, coupled with the generation of more sensitive assertions for detecting them, and 3) better simulation of the execution environment to detecting faults that are dependent on external factors, for example the date and time.
Disciplines :
Computer science
Author, co-author :
Shamshiri, Sina
Just, Rene
Rojas, Jose Miguel
Fraser, Gordon
McMinn, Phil
Arcuri, Andrea;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
External co-authors :
yes
Language :
English
Title :
Do Automatically Generated Unit Tests Find Real Faults? An Empirical Study of Effectiveness and Challenges
Publication date :
2015
Event name :
Proceedings of the 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)
Event date :
9-13 November 2015
Main work title :
Proceedings of the 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)
Publisher :
ACM
Peer reviewed :
Peer reviewed
Available on ORBilu :
since 25 July 2015

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