Adaptive Test Suits Generation for Self-Adaptive Systems Using SPEA2 Algorithm

Author:

Jamil Muhammad Abid1ORCID,Nour Mohamed K.1,Alotaibi Saud S.2ORCID,Hussain Mohammad Jabed2,Hussaini Syed Mutiullah1,Naseer Atif3ORCID

Affiliation:

1. Department of Computer Science, College of Computers and Information Systems, Umm Al Qura University, Makkah 21955, Saudi Arabia

2. Department of Information Systems, College of Computers and Information Systems, Umm Al Qura University, Makkah 21955, Saudi Arabia

3. Science and Technology Unit, Umm Al Qura University, Makkah 21955, Saudi Arabia

Abstract

Self-adaptive systems are capable of reconfiguring themselves while in use to reduce the risks forced by environments for which they may not have been specifically designed. Runtime validation techniques are required because complex self-adaptive systems must consistently offer acceptable behavior for important services. The runtime testing can offer further confidence that a self-adaptive system will continue to act as intended even when operating in unknowable circumstances. This article introduces an evolutionary framework that supports adaptive testing for self-adaptive systems. The objective is to ensure that the adaptive systems continue to operate following its requirements and that both test plans and test cases continuously stay relevant to shifting operational conditions. The proposed approach using the Strength Pareto Evolutionary Algorithm 2 (SPEA2) algorithm facilitates both the execution and adaptation of runtime testing operations.

Funder

Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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1. A Methodology for Efficient Data Processing in AI Applications Using Adaptive Sampling and Automated Testing;2024 4th International Conference on Computer Communication and Artificial Intelligence (CCAI);2024-05-24

2. Enhancing AI Data Management: Combining Reservoir Sampling and Self-Adaptive Testing for Efficiency;2024 International Conference on Intelligent Systems for Cybersecurity (ISCS);2024-05-03

3. Enhancing Efficiency in Large Scale Data Processing: Optimizing Cluster Compute and Storage Resources;2024 2nd International Conference on Advancement in Computation & Computer Technologies (InCACCT);2024-05-02

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