UMP Institutional Repository

Fuzzy adaptive teaching learning-based optimization strategy for pairwise testing

Din, Fakhrud and Kamal Z., Zamli (2017) Fuzzy adaptive teaching learning-based optimization strategy for pairwise testing. In: 7th IEEE International Conference on System Engineering and Technology (ICSET 2017), 2-3 October 2017 , Shah Alam; Malaysia. pp. 17-22.. ISBN 978-153860383-3

[img] Pdf
Fuzzy adaptive teaching learning-based optimization strategy for pairwise testing.pdf
Restricted to Repository staff only

Download (1MB) | Request a copy
[img]
Preview
Pdf
Fuzzy adaptive teaching learning-based optimization strategy for pairwise testing.pdf

Download (107kB) | Preview

Abstract

Pairwise strategies have tested effectively a range of software and hardware systems. These testing strategies offer solutions that can substitute exhaustive testing. In simple terms, a pairwise testing strategy significantly minimizes large input parameter values (or configuration options) of a system into a smaller set based on pairwise interaction (or combination). Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm is an improved form of Teaching Learning-based Optimization (TLBO) algorithm. ATLBO employs Mamdani fuzzy inference system to select adaptively either teacher phase or learner phase based on performance instead of blind sequential application as in original TLBO. In this paper, two pairwise testing strategies based on ATLBO and TLBO are proposed. Experimental results suggest that the proposed strategies are capable to be part of testers’ toolkit as they outperformed competing meta-heuristic based pairwise testing strategies and tools on many pairwise benchmarks. Moreover, ATLBO based strategy generated optimal pairwise test suites than the one based on TLBO.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Indexed by SCOPUS
Uncontrolled Keywords: Fuzzy inference system; Pariwise testing; Software testing; Teaching learning-based optimization
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty/Division: Faculty of Computer System And Software Engineering
Depositing User: Prof. Dr. Kamal Zuhairi Zamli
Date Deposited: 10 Jun 2019 02:19
Last Modified: 10 Jun 2019 02:19
URI: http://umpir.ump.edu.my/id/eprint/22594
Download Statistic: View Download Statistics

Actions (login required)

View Item View Item