Automated Compatibility Testing Method for Distributed Software Systems in Cloud Computing
Weike Ding, Huiming Zhou, Hao Tan, Zihan Li, Chao Fan
Abstract
In order to avoid the conflict between software systems and improve the overall coordination performance of software, an automatic detection method of distributed software system compatibility in cloud computing is proposed. Build the basic architecture of cloud computing and explore various service modes provided by cloud computing in software compatibility detection; The basic particle swarm optimization model is established, and the weights and learning factors are adjusted. This article explores the challenges of ensuring software compatibility for distributed systems in a cloud computing environment and describes methods for integrating particle swarm optimization algorithms for compatibility testing. Based on the analysis of distributed software system characteristics, existing compatibility testing methods and distributed system compatibility testing tools, a collaborative application of TLA+ and Jepsen methods is proposed to improve the compatibility testing practice in cloud computing environment. The methodology of integrated particle swarm optimization is described in detail, including initialization, fitness evaluation, particle updating, convergence detection, dispersion adjustment and fitness function modification, and the effectiveness of the algorithm in improving compatibility coverage, efficiency and robustness is verified by experimental results. Finally, the role of integrated particle swarm optimization algorithm in optimizing software performance and reliability in cloud computing environment is summarized, and its importance to improve the seamless and compatibility of software operation is emphasized.