Abstract

[This abstract is based on the author's abstract.] Producing low-cost, high-quality software is a desirable goal in major software development projects. By predicting and monitoring quality early in the software development life cycle, managers can make decisions, plan, and allocate resources for the final stages, including maintenance. A study is presented here that had a goal of intuitively and empirically assessing the level of association between difficulty and selected software metrics that can be obtained relatively early in the software life cycle. It was intended to observe the statistical significance of possible relationships between design/code level metrics and difficulty so that design/code considerations could be made in the design and implementation phases in order to reduce difficulty and improve quality. The study demonstrated how a number of metrics had a statistically significant relationship with difficulty. The results can provide useful guidance to software developers to improve software quality from the early phases of software development.