Abstract
With the extensive development and application of software technology tools and software technology collaboration environments in business, the current focus of software technology research has shifted from the scale and scale of software technology to how to analyze and improve it. The purpose of this work is to study the optimization and application of swarm particle optimization in software technology. A new fitness construction method is proposed and implemented to automatically create multiple test cases based on the MPRPSO algorithm. Creating a larger test set improves the efficiency of creating test cases to a certain extent. The experimental results show that the improved MPRPSO algorithm has about 10 iterations, which is better than the comparison algorithm. The advanced MPRPSO is not only more efficient in creating software technical tests, but also has better algorithm performance and is more suitable for various system-based software. The test method determines the case algorithm.
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Chen, J. (2022). Optimization and Application of Particle Swarm Algorithm in Software Engineering. In: Sugumaran, V., Sreedevi, A.G., Xu , Z. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. ICMMIA 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 138. Springer, Cham. https://doi.org/10.1007/978-3-031-05484-6_77
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DOI: https://doi.org/10.1007/978-3-031-05484-6_77
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