Test Case Generation using Mutation Operators and Fault Classification

TL;DR

This paper proposes a mutation testing-based approach for automatic test case generation from program execution traces, aiming to improve testing efficiency and reliability in software development.

Contribution

It introduces a novel mutation testing technique for generating test cases post-coding, enhancing testing effectiveness and reducing manual effort.

Findings

Demonstrated the mutation-based test case generation algorithm on an example

Showed potential for early and automated test case creation from specifications and traces

Improved test coverage and reliability through mutation techniques

Abstract

Software testing is the important phase of software development process. But, this phase can be easily missed by software developers because of their limited time to complete the project. Since, software developers finish their software nearer to the delivery time; they dont get enough time to test their program by creating effective test cases. . One of the major difficulties in software testing is the generation of test cases that satisfy the given adequacy criterion Moreover, creating manual test cases is a tedious work for software developers in the final rush hours. A new approach which generates test cases can help the software developers to create test cases from software specifications in early stage of software development (before coding) and as well as from program execution traces from after software development (after coding). Heuristic techniques can be applied for creating quality test cases. Mutation testing is a technique for testing software units that has great potential for improving the quality of testing, and to assure the high reliability of software. In this paper, a mutation testing based test cases generation technique has been proposed to generate test cases from program execution trace, so that the test cases can be generated after coding. The paper details about the mutation testing implementation to generate test cases. The proposed algorithm has been demonstrated for an example.