DEVELOPMENT OF AGILE PRODUCTIVITY METRICS OF INDIVIDUAL EXPERT JAVASCRIPT DEVELOPERS FOR SOFTWARE PROJECT MANAGERS

Abstract

Software Project Managers require metrics to measure productivity in team work. Since agile software development require continuous improvement, metrics helps in identifying bottlenecks and inefficiencies thereby enabling teams to refine their processes iteratively. Productivity metrics also helps in effective resource allocation and optimization to ensure timely delivery of software products by Software Project Managers. Although metrics have been developed for traditional software programmers little work has been done in developing metrics for Agile Software Project Managers specifically for JavaScript Program. In this work, metrics for Individual Expert agile software programmers and specifically for JavaScript was developed. Programs in JavaScript was designed and developed to record the time spent in correcting deliberate errors introduced. Experiment was conducted among one hundred programmers' group of Individual Expert pairs with the aim of recording time spent in debugging the codes, The curve fit regression models of time spent in debugging a number of bugs in agile software written in JavaScript programming language for project managers revealed that Cubic model had the highest R squared value of 0.996 which is closely followed by the quadratic model with a value of 0.980 while the compound, growth and exponential models have the least value of 0.868.