Testing Software Using Swarm Intelligence: A Bee Colony Optimization Approach

El Ariss, Omar and Bou ghosn, Steve and Xu, Weifeng (2016) Testing Software Using Swarm Intelligence: A Bee Colony Optimization Approach. Testing Software Using Swarm Intelligence: A Bee Colony Optimization Approach, 2 (8). e1. ISSN 2312-8623

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Abstract

Software testing is a critical activity in increasing our confidence of a system under test and improving its quality. The key idea for testing a software application is to minimize the number of faults found in the system. Software verification through testing is a crucial step in the application's development life cycle. This process can be regarded as expensive and laborious, and its automation is valuable. We propose a multi-objective search based test generation technique that is based on both functional and structural testing. Our Search Based Software Testing (SBST) technique is based on a bee colony optimization algorithm that integrates adaptive random testing from the functional side and condition/decision and multiple condition coverage from the structural side. The constructive approach that the bee colony algorithm uses for solution generation allows our SBST to address the limitations of previous approaches relying on fully random initial solutions and single objective evaluation. We perform extensive experimental testing to justify the effectiveness of our approach.

Item Type: Article
Uncontrolled Keywords: swarm intelligence, unit testing, automated test generation, branch coverage, search based testing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor IV
Date Deposited: 01 Jul 2021 11:55
Last Modified: 01 Jul 2021 11:55
URI: https://eprints.eudl.eu/id/eprint/4328

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