Welcome to the InfoSci Platform
Reference Hub3
Optimization of Favourable Test Path Sequences Using Bio-Inspired Natural River System Algorithm

Optimization of Favourable Test Path Sequences Using Bio-Inspired Natural River System Algorithm

Nisha Rathee, Rajender Singh Chhillar
Copyright: © 2021 |Volume: 14 |Issue: 2 |Pages: 21
ISSN: 1938-7857|EISSN: 1938-7865|EISBN13: 9781799860013|DOI: 10.4018/JITR.2021040105
Cite Article Cite Article

MLA

Rathee, Nisha, and Rajender Singh Chhillar. "Optimization of Favourable Test Path Sequences Using Bio-Inspired Natural River System Algorithm." JITR vol.14, no.2 2021: pp.85-105. http://doi.org/10.4018/JITR.2021040105

APA

Rathee, N. & Chhillar, R. S. (2021). Optimization of Favourable Test Path Sequences Using Bio-Inspired Natural River System Algorithm. Journal of Information Technology Research (JITR), 14(2), 85-105. http://doi.org/10.4018/JITR.2021040105

Chicago

Rathee, Nisha, and Rajender Singh Chhillar. "Optimization of Favourable Test Path Sequences Using Bio-Inspired Natural River System Algorithm," Journal of Information Technology Research (JITR) 14, no.2: 85-105. http://doi.org/10.4018/JITR.2021040105

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Testing of software requires a great amount of time and effort. The tester's main aim is to design optimized test sequences with a minimum amount of time, effort, and with less redundancy. Testers have used artificial intelligence meta-heuristic algorithms for optimization of test sequences. The model-driven approach is helpful in the generation of test sequences at early designing phase only. The model-driven approach uses UML diagram to represent the system's behavior and design test cases for the system at design stage of software development life cycle. The proposed approach uses natural river system for optimizing favourable non-redundant test path sequences using UML activity diagrams and sequence diagrams. The implementation of proposed approach has been done using python and results show that the proposed approach provides full coverage of test paths with less redundant test nodes compared to other meta heuristic algorithms.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.