NDLI: Multi Objective Higher Order Mutation Testing with Genetic Programming

Content Provider	IEEE Xplore Digital Library
Author	Langdon, W.B. Harman, M. Yue Jia
Copyright Year	2009
Abstract	In academic empirical studies, mutation testing has been demonstrated to be a powerful technique for fault finding.However, it remains very expensive and the few valuable traditional mutants that resemble real faults are mixed in with many others that denote unrealistic faults.These twin problems of expense and realism have been a significant barrier to industrial uptake of mutation testing.Genetic programming is used to search the space of complex faults (higher order mutants). The space is much larger than the traditional first order mutation space of simple faults.However, the use of a search based approach makes this scalable, seeking only those mutants that challenge the tester,while the consideration of complex faults addresses the problem of fault realism; it is known that 90% of real faults are complex (i.e. higher order).We show that we are able to find examples that pose challenges totesting in the higher order space that cannot be represented in thefirst order space.
Starting Page	21
Ending Page	29
File Size	1213325
Page Count	9
File Format	PDF
ISBN	9780769538204
DOI	10.1109/TAICPART.2009.18
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-04
Publisher Place	United Kingdom
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Performance evaluation Heart genetic programming Genetic mutations Educational institutions mutation testing Programming profession triangle Computer science schedule higher order mutation Genetic programming tcas Benchmark testing Pareto optimality Computer industry Arithmetic
Content Type	Text
Resource Type	Article

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