SEFeb 15, 2017

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

arXiv:1702.04501v177 citations
AI Analysis

This addresses test redundancy issues for software testing teams, but it is incremental as it builds on prior work with supplementary results.

The paper tackles the problem of test redundancy reduction in software testing by applying a newly developed hyper-heuristic called Fuzzy Inference Selection (FIS), presenting supplementary experimental results.

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.

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