Achieving scalable mutation-based generation of whole test suites-Reference-Cited by-同舟云学术

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Achieving scalable mutation-based generation of whole test suites

Published:2014-02-09 Issue:3 Volume:20 Page:783-812
ISSN:1382-3256
Container-title:Empirical Software Engineering
language:en
Short-container-title:Empir Software Eng

Author:

Fraser Gordon,Arcuri Andrea

Publisher

Springer Science and Business Media LLC

Subject

Software

Link

http://link.springer.com/content/pdf/10.1007/s10664-013-9299-z.pdf

Reference56 articles.

1. Acree AT (1980) On mutation. Phd thesis, Georgia Institute of Technology, Atlanta, Georgia

2. Adamopoulos K, Harman M, Hierons RM (2004) How to overcome the equivalent mutant problem and achieve tailored selective mutation using co-evolution. In: Genetic and evolutionary computation conference (GECCO). Seattle, Washington, pp 1338–1349

3. Andrews JH, Briand LC, Labiche Y (2005) Is mutation an appropriate tool for testing experiments? In: Proceedings of the 27th international conference on software engineering, ICSE 05. ACM, pp 402–411

4. Arcuri A (2013) It really does matter how you normalize the branch distance in search-based software testing. Softw Test Verification Reliab (STVR) 23(2):119–147

5. Arcuri A, Briand L (2012) A hitchhiker’s guide to statistical tests for assessing randomized algorithms in software engineering. In: Software testing verification and reliability (STVR). doi: 10.1002/stvr.1486

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