文件名称:Software-Quality-Prediction-Using-Cuckoo-Search-O
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this work aims to investigate the quality of software products a n important attribute of computer programs it helps to decide the degree of trustworthiness a program has in accomplishing its specific functions. This done using the Software quality model(SQMs) through the estimation of their parameters. The parameters are estimated in this work based on the available failure data and with the search techniques of Swarm Intelligence, namely, the Cuckoo Search (CS) due to its efficiency, effectiveness and robustness. A number of SQMs is studied, and the results are compared to Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and extended ACO. Results show that CS outperformed both PSO and ACO in finding better parameters-this work aims to investigate the quality of software products as an important attribute of computer programs it helps to decide the degree of trustworthiness a program has in accomplishing its specific functions. This is done using the Software quality model(SQMs) through the estimation of their parameters. The parameters are estimated in this work based on the available failure data and with the search techniques of Swarm Intelligence, namely, the Cuckoo Search (CS) due to its efficiency, effectiveness and robustness. A number of SQMs is studied, and the results are compared to Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and extended ACO. Results show that CS outperformed both PSO and ACO in finding better parameters
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Software Quality Prediction Using Cuckoo Search Optimization.pdf