Supplementary Material for the Information Sciences Paper: An Experimental Study of Hyper-Heuristic Selection and Acceptance Mechanism for Combinatorial t-way Test Suite Generation

TL;DR

This paper evaluates a fuzzy inference hyperheuristic, FIS, for reducing redundant test cases in distributed software testing, enhancing efficiency in combinatorial t-way test suite generation.

Contribution

It introduces and experimentally assesses the FIS hyperheuristic for test redundancy reduction in distributed software testing environments.

Findings

FIS effectively reduces test redundancies.

Improves efficiency of test suite generation.

Outperforms existing methods in certain scenarios.

Abstract

Software testing relates to the process of accessing the functionality of a program against some defined specifications. To ensure conformance, test engineers often generate a set of test cases to validate against the user requirements. Owing to the growing complexity of software and its increasing diffusion into various application domains, it is no longer unusual for a software project to have testing teams in more than one location or even distributed over many continents. Owing to the intertwined dependencies of many software development activities and their geographical and temporal issues, there are potentially many overlapping test cases which can cause unwarranted redundancies across the shared modules (i.e. a test for one requirement may be covered by more than one test). In this paper, we explore the application of our newly developed hyperheuristic, called Fuzzy Inference Selection (FIS), for addressing test redundancy reduction problem. This paper presents the supplementary results for the paper : An Experimental Study of Hyper-Heuristic Selection and Acceptance Mechanism for Combinatorial t way Test Suite Generation published in Information Sciences.