Software Defects Identification Using Principles of Data Gathering and Pareto Analysis.

Several organizations want to predict the number of defects (faults) in software systems, before they are deployed , to gauge the likely delivered qaulity and maintenance software. Finding defects in software is a challenging and time and budget consuming task. Minimizing these adverse effects using software defect prediction models via guiding testers with defective parts of software system is an attractive research area. This paper examines software defect prediction and aims to improve prediction results using information gathering and Pareto analysis. Software development organization collects information on errors and defects for a period of one year. Some quality problems are uncovered as software is being developed. Others are encountered after the software has been released to its end user. Although hundreds of different errors are uncovered, all can be traced and estimated its phase index and defective index. [ABSTRACT FROM AUTHOR]