Mutant Selecting According to the Nondominated Original Statements

Joint Authors

Zhang, Gongjie
Dong, Yongquan
Yu, Qiao
Xie, Chunli

Source

Scientific Programming

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

Mathematics

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