ImReMuDF: Redundant Mutants Identification Method Based on Definition and Reference of Variables

Zhenpeng Liu,Xianwei Yang,Yi Liu,Yonggang Zhao,Xiaofei Li,Roberto Natella

doi:10.1155/2021/7543896

Zhenpeng Liu, Xianwei Yang + Show 4 more

Open Access

https://doi.org/10.1155/2021/7543896

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Abstract

Mutation testing is an effective defect-based software testing method, but a large number of mutants lead to expensive testing costs, which hinders the application of variation testing in industrial engineering. To solve this problem and enable mutation testing to be applied in industrial engineering, this paper improves the method of identifying redundant mutants based on data flow analysis and proposes the inclusion relationship between redundant mutants, so that the redundancy rate of mutants is reduced. In turn, the cost of mutation testing can be reduced. The redundant mutants identification method based on definition and reference of variables (ImReMuDF) was validated and evaluated using 8 C programs. The minimum improvement in redundant mutant identification rate was 34.0%, and the maximum improvement was 71.3% in the 8 C programs tested, and the verification results showed that the method is feasible and effective and has been improved in reducing redundant mutants and effectively reducing the execution time of mutation testing.

Highlights

Mutation testing is a fault-based software testing technique [1] that has received a great deal of attention in program analysis, defect detection, and test case generation [2]
E concept of mutation testing was first proposed by Demillo [8], which refers to the execution of mutation operations on the original program to generate a new program, and the new program is called a mutant
E redundant mutants identified by the program for different experimental subjects were summed and counted, and the statistical results are shown in Table 2. e redundancy rate of their mutants was used to verify the effectiveness of the algorithm in reducing the execution time of the mutation testing, and the redundancy rate was calculated by the formula shown in equation (1): R NRVI ×100%, (3)

Summary

Introduction

Mutation testing is a fault-based software testing technique [1] that has received a great deal of attention in program analysis, defect detection, and test case generation [2]. Sun et al [12] proposed a method for identifying redundant mutants based on data flow analysis. E method proposed by Sun et al reduces the mutants caused by variables very well. It reduces the execution time of mutation testing by reducing the number of mutants, but it does not extend well to the identification of redundant mutants of multiple variables. In order to increase the recognition rate of redundant mutants and reduce redundant mutants, this paper proposes a redundant mutants identification method based on definition and reference of variables (ImReMuDF). (1) e definition and reference of two variables are proposed to increase the recognition rate of redundant mutants in the test. Compared with the definition and reference of one variable, the ImReMuDF method can be extended to the definition and reference of multiple variables to identify redundant mutants

Identification of Redundant Mutants

Identification Rules of Redundant Mutant

Experimental Analysis

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