An effort re-estmation technique using defect analysis and risk assessment

Abstract

This paper describes a technique for an effort prediction using defect patterns based on defect data history. Most of the time, project managers waste effort in finding defects and reworks which consume a lot of expense and time. To improve the performance, productivity and quality, each project exploits the usage of test results information and defect summaries as statistical data. This statistical data is documented in order to create a metric measurement report. It is, however, insufficient for further project evaluations. Thus, historical defect information is needed. The proposed technique applies a data mining algorithm for finding the effects from defect patterns. Furthermore, the critical factors - for instance, project size, development technology, project progress and so forth - are applied for effort re-estimation. Using the proposed technique helps project managers make decisions whether the remaining effort is adequate for the overall project tasks. © 2012 AICIT.