Earticle

Software defects prediction research is converging on the use of function point elements for software defect predictions. Studies on the nature and behavior of the function point elements are expanding. Previous studies have analyzed the correlation between the function point elements. This paper presents correlation analysis between function point elements and the software defects. It is observed that external input count and external inquiry count function point elements show some correlation with software defects. Different data subsets were analyzed, where 4GL projects shows strong correlation with defects over 3GL and ApG/other projects, while enhancement software projects show more correlation with defects over new software projects.

Function point elements are metrics to measure the size of software projects. This article investigates the relationship among function point elements using principle component analysis. Principle component analysis reveals the relationship of different function point elements such that they may be measuring the same attribute of a software project. Therefore, principle component analysis brings out the influence of a function point element over each other. Principle component analysis can help to integrate the function point elements.

This research work investigates the correlation of software function point elements using bootstrap simulation. The correlation of software function point elements plays an important role in understanding the software size; the correlation among function point elements suggests that they measure the same attribute of a software project. Bootstrapping is an effective method to study the statistical properties of correlation coefficients; bootstrap produces a histogram of the possible values of correlation coefficients, which helps to understand the range and spread of the correlation among different function point elements, rater then generating a single point estimate of the correlation.