Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/6256
Title: Semantic mutation testing
Authors: Clark, JA
Dan, H
Hierons, RM
Keywords: Mutation testing;Semantics;Misunderstandings
Issue Date: 2011
Publisher: Elsevier
Citation: Science of Computer Programming, 78(4): 345–363, Apr 2013
Abstract: Mutation testing is a powerful and flexible test technique. Traditional mutation testing makes a small change to the syntax of a description (usually a program) in order to create a mutant. A test suite is considered to be good if it distinguishes between the original description and all of the (functionally non-equivalent) mutants. These mutants can be seen as representing potential small slips and thus mutation testing aims to produce a test suite that is good at finding such slips. It has also been argued that a test suite that finds such small changes is likely to find larger changes. This paper describes a new approach to mutation testing, called semantic mutation testing. Rather than mutate the description, semantic mutation testing mutates the semantics of the language in which the description is written. The mutations of the semantics of the language represent possible misunderstandings of the description language and thus capture a different class of faults. Since the likely misunderstandings are highly context dependent, this context should be used to determine which semantic mutants should be produced. The approach is illustrated through examples with statecharts and C code. The paper also describes a semantic mutation testing tool for C and the results of experiments that investigated the nature of some semantic mutation operators for C.
Description: This is the Pre-print version of the Article. The official published version can be obtained from the link below - Copyright @ 2011 Elsevier
URI: http://www.sciencedirect.com/science/article/pii/S0167642311000992
http://bura.brunel.ac.uk/handle/2438/6256
DOI: http://dx.doi.org/10.1016/j.scico.2011.03.011
ISSN: 0167-6423
Appears in Collections:Publications
Computer Science
Dept of Computer Science Research Papers

Files in This Item:
File Description SizeFormat 
semantic_journal_revised.pdf621.79 kBUnknownView/Open


Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.