Assuring Software Quality using data mining methodology: A literature study

Software Quality is the very popular and a very important topic for researchers within the software engineering communities, most probably everyone has an opinion about the meaning of quality. However, many disagreements and conflicts are very often leaded between peoples whose involve in software development, when they implement to it in the real world. This has been highly notable in the case of customer´s complaints about faults in the software products. It is well known that many organizations or individuals are relishing many challenges to preserve software product quality, whenever they develop any types of software product. Appearance of defects is the very much contributor to reduce the product quality and prominently increases in development costs and completion time due to amendment and rework time. The success and demand of a software system is not only pivot on cost and proceedings, but also on software quality. In between many software quality features, to identify the vestigial defects in the product has become the actual industry standard. This paper is a study about software quality, software defect and how both are relate to each other and also discuss defect prediction is batter approach in compare defect correction to assure software product quality. We also discuss some data mining methodologies in brief; they are used to build defect prediction models to ensure the level of defect density of target program modules of software product.