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Dayang N. A. Jawawi
Researcher at Universiti Teknologi Malaysia
Publications - 182
Citations - 1791
Dayang N. A. Jawawi is an academic researcher from Universiti Teknologi Malaysia. The author has contributed to research in topics: Software development & Component-based software engineering. The author has an hindex of 15, co-authored 173 publications receiving 1367 citations. Previous affiliations of Dayang N. A. Jawawi include Information Technology University.
Papers
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Electromagnetic field optimization: A physics-inspired metaheuristic optimization algorithm
TL;DR: The proposed algorithm is inspired by the behavior of electromagnets with different polarities and takes advantage of a nature-inspired ratio, known as the golden ratio, which determines the ratio between attraction and repulsion forces to help particles converge quickly and effectively.
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Test case prioritization approaches in regression testing: A systematic literature review
TL;DR: This review examines and classify the current test case prioritization approaches in TCP based on the articulated research questions and found that variations in the starting point of TCP process among the approaches provide a different timeline and benefit to project manager to choose which approaches suite with the project schedule and available resources.
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Quality of service approaches in cloud computing
TL;DR: In this paper, the authors conducted a systematic mapping study to find the related literature, and 67 articles were selected as primary studies that are classified in relation to the focus, research type and contribution type.
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Effective Regression Test Case Selection: A Systematic Literature Review
TL;DR: This systematic literature review presents state-of-the-art research in effective regression test case selection techniques and observed that 70% of the studies being analyzed used cost as the effectiveness measure compared to 31% that use fault-detection capability and 16% that used coverage.
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A PSO-based model to increase the accuracy of software development effort estimation
TL;DR: A hybrid estimation model based on a combination of a particle swarm optimization (PSO) algorithm and ABE to increase the accuracy of software development effort estimation and to accurate identification of projects that are similar is proposed.