Apply Particle Swarm Optimization Algorithm to Measure the Software Quality

Al-Rafidain Journal of Computer Sciences and Mathematics

Ibrahim Saleh¹  Salha Mahammead¹ 

[1] College of Computer Sciences and Mathematics University of Mosul, Mosul, Iraq;

关键词: software defect;    particle swarm optimization;    neural network back propagation;    nasa;   

DOI  :  10.33899/csmj.2018.163572

来源: DOAJ

【 摘 要 】

The process of improvement software quality began from early stages of software engineering development. It uses multiple quality metrics which are very important in software development. To calculate the   standards quality of in software testing has been adopted.  The software testing is focusing on the Software defect. In this paper is proposed new methods which combine the particle swarm optimization (PSO) to handle the best features Extraction with back-propagation networks to  testing and evaluation of the data set . The paper depended database for NASA standards data.  The result and experiment method improved quality performance for all classification methods used in the research"Combining Particle Swarm Optimization based Feature Selection and Bagging for Software Defect Prediction ".

【 授权许可】

Unknown