Abstract
AbstractThe prediction of software defects in a software project has recently attracted the attention of many researchers. Prediction of defect density indicator (DDI) in each phase of software development life cycle (SDLC) is desirable for effective decision support and trade-off analysis during software development, and also, it improves the reliability of software project and helps software manager to achieve reliable software product within time and costs. The reliability-relevant software metrics impose major impact on the quality of software project at each software development stage. However, software metrics are associated with uncertainty and can be assessed in linguistic terms. Therefore, in this paper, a multistage model for software DDI is proposed using the topmost reliability-relevant metrics and fuzzy inference system (FIS).The predictive accuracy of proposed model is validated using real software projects data. Validation results are satisfactory.KeywordsSoftware metricsFuzzy logicFuzzy inference systemDefect density indicatorQualitative value of metric
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