Title: Intelligent Software Testing Framework: Integrating Genetic Algorithms with Reliability Growth Models
Authors: Mohammad Nasar and Mohammad Abu Kausar
Volume: 9
Issue: 8
Pages: 63-69
Publication Date: 2025/08/28
Abstract:
Software reliability is a cornerstone of software engineering as undetected bugs can have severe consequences. In this paper, We propose to use GA and SRGM to be our intelligent model which is to schedule the testing process to get maximum faults with minimal testing time. The proposed framework dynamically schedules testing efforts along with SRGM parameters, exploring GAs' optimization potential by extending basic models including the Jelinski-Moranda and the Goel-Okumoto models and further developments having covered to testing and adaptive test generation. The methodology is cost efficient and reliability oriented. Based on theoretical analysis and simulated case studies, we present that fault detection and resource allocation can be enhanced. This paper combines old and new results to answer open questions on complex software systems