Approximating Deployment Metrics to Predict Field Defects and Plan Corrective Maintenance Activities

Corrective maintenance activities are a common cause of schedule delays in software development projects. Organizations frequently fail to properly plan the effort required to fix field defects. This study aims to provide relevant guidance to software development organizations on planning for these corrective maintenance activities by correlating metrics that are available prior to release with parameters of the selected software reliability model that has historically best fit the product´s field defect data. Many organizations do not have adequate historical data, especially historical deployment and field usage information. The study identifies a set of metrics calculable from available data to approximate these missing predictor categories. Two key metrics estimable prior to release surfaced with potentially useful correlations, (1) the number of periods until the next release and (2) the peak deployment percentage. Finally, these metrics were used in a case study to plan corrective maintenance efforts on current development releases.