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QUANTUM COMPUTING-BASED TEST OPTIMIZATION FOR SAFETY-CRITICAL SYSTEMS AND APPLICATIONS


Article Information

Title: QUANTUM COMPUTING-BASED TEST OPTIMIZATION FOR SAFETY-CRITICAL SYSTEMS AND APPLICATIONS

Authors: Syed Zaffar Iqbal, Dr. Kashif Saghar

Journal: Spectrum of Engineering Sciences

HEC Recognition History
Category From To
Y 2024-10-01 2025-12-31

Publisher: Sociology Educational Nexus Research Institute

Country: Pakistan

Year: 2025

Volume: 3

Issue: 3

Language: en

Keywords: QUANTUM COMPUTING-BASEDTEST OPTIMIZATION FOR SAFETYCRITICAL SYSTEMS AND APPLICATIONS

Categories

Abstract

The exponential growth in software complexity, particularly in safety-critical systems such as aerospace and automotive domains, has significantly increased the need for efficient software testing. Traditional test optimization techniques often struggle to balance fault detection capabilities with computational resource constraints. This research explores the integration of quantum computing—an emerging computational paradigm—into software test optimization, aiming to reduce test suite size while maintaining or improving fault detection effectiveness. We propose a quantum-assisted test case prioritization and selection framework leveraging key quantum algorithms, including Grover’s Search and the Quantum Approximate Optimization Algorithm (QAOA). The methodology integrates classical fault-based testing techniques with quantum computational power to enhance the efficiency of test case selection, prioritization, and execution. Experiments are conducted using benchmark datasets such as the Siemens suite, with implementations tested on simulators like Qiskit Aer and actual quantum backends from IBM Q. We compare the proposed quantum approaches against traditional methods such as greedy, genetic algorithms, and random prioritization. Evaluation metrics include fault detection rate, test suite reduction percentage, and execution time. Initial results indicate that quantum methods achieve comparable or superior fault coverage with reduced test suite size and significant computational efficiency in some cases, particularly in larger or more complex test spaces. Statistical analyses, including t-tests and ANOVA, confirm the significance of observed improvements. While current quantum hardware imposes limitations such as qubit noise and gate depth restrictions, the results suggest that quantum computing holds strong potential as a complementary approach for optimizing software testing in high-assurance systems. The paper concludes with a discussion on current limitations, future improvements, and the anticipated impact of near-term quantum advancements on software quality assurance practices.


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