A new mutant generation algorithm based on basic path coverage for mutant reduction

Abstract

Mutation testing is a fault-based testing technique that can be used to measure the adequacy of a test set, but its application usually incurs a high cost due to the necessity of generating and executing a great number of mutants. How to reduce the cost still remains a challenge for research. In this paper, we present a new mutant generation algorithm based on a basic path coverage that can help reduce mutants. The algorithm is characterized by implementing a basic path segments identification criterion for determining appropriate program points at which faults are inserted and a mutant generation priority criterion for selecting proper mutant operators to make a fault for insertion. We discuss the algorithm by analysing how the two criteria are realized based on analysing the control flow graph of the program and applying effective mutation operators on the appropriate statements in the relevant path segments. We also present an automated mutation testing tool that supports the proposed approach, and a small experiment to evaluate our tool by comparing it with a traditional mutation testing method on six programs. The result of the experiment suggests that the proposed method can significantly reduce the number of mutants and improve the efficiency of mutation testing.