.png){kind=icon}
.png){kind=icon}
Return
Should software testers use mutation analysis to augment a test set?
.png){kind=icon}
PRE
AI
DOI：10.1016/j.jss.2009.06.031.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Mutation testing has historically been used to assess the fault-finding effectiveness of a test suite or other verification technique. Mutation analysis, rather, entails augmenting a test suite to detect all killable mutants. Concerns about the time efficiency of mutation analysis may prohibit its widespread, practical use. The goal of our research is to assess the effectiveness of the mutation analysis process when used by software testers to augment a test suite to obtain higher statement coverage scores. We conducted two empirical studies and have shown that mutation analysis can be used by software testers to effectively produce new test cases and to improve statement coverage scores in a feasible amount of time. Additionally, we find that our user study participants view mutation analysis as an effective but relatively expensive technique for writing new test cases. Finally, we have shown that the choice of mutation tool and operator set can play an important role in determining how efficient mutation analysis is for producing new test cases. (C) 2009 Elsevier Inc. All rights reserved.
Keywords:
Mutation testing
Empirical effectiveness
User study
Mutation analysis
Test adequacy
Web application
Open source
Unit testing
Mutation testing tool
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.1
Papers:
5.4K
Citations:
8.4K