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Mutant Selecting According to the Nondominated Original Statements
Joint Authors
Zhang, Gongjie
Dong, Yongquan
Yu, Qiao
Xie, Chunli
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-11-03
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Mutation testing is a technique for evaluating the quality of a test suite.
However, the costly computation from a large number of mutants affects the practical application of mutation testing, and reducing the number of mutants is reasonably an efficient way for mutation testing.
We propose a new method for reducing mutants by analyzing dominance between statements in the program under test.
The proposed method only selects the mutants generated from the nondominated statements, and the mutants generated from the dominated statements are reduced.
After applying the proposed method to nine programs, the experimental results show that our method reduces over 75% mutants and well maintains the mutation adequacy.
American Psychological Association (APA)
Zhang, Gongjie& Xie, Chunli& Dong, Yongquan& Yu, Qiao. 2019. Mutant Selecting According to the Nondominated Original Statements. Scientific Programming،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1210738
Modern Language Association (MLA)
Zhang, Gongjie…[et al.]. Mutant Selecting According to the Nondominated Original Statements. Scientific Programming No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1210738
American Medical Association (AMA)
Zhang, Gongjie& Xie, Chunli& Dong, Yongquan& Yu, Qiao. Mutant Selecting According to the Nondominated Original Statements. Scientific Programming. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1210738
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1210738