Models for Maintenance Effort Prediction with Object-Oriented Cognitive Complexity Metrics

Software maintenance is the most desired, but most elusive and difficult task in software engineering. The cost of maintenance is as high as 60% to 80% of the total cost of the software. So, plenty of researches are going on in software maintenance. Though, object-oriented paradigm has made it easier, it remains the critical hotspot of research. One way of grappling with the maintenance problem, is to use the complexity metrics. Many studies were made to understand the relationship among complexity metrics, cognition, and maintenance. This paper wrestles with four newly proposed object-oriented cognitive complexity metrics to develop maintenance effort prediction models through various statistical techniques. Empirical study designs are made with hypotheses and experimented. Discussion on results prove the maintenance effort prediction models are more robust, more accurate, and can be employed to estimate the maintenance effort.