Software Process Improvement Diagnostic: A Snowballing Systematic Literature Review

Abstract

Software Process Improvement (SPI) consists of a set of changes in a software development company, introducing new and improved methods, techniques, and tools. We call SPI Diagnostic, the process to know the organization current status. Typically, these SPI Diagnostic processes are manually performed, thus demanding consultant practitioner and a high effort from the organization under analysis. Based on this we propose the following question: “What solutions have been proposed to SPI Diagnostic?” We looked for other Systematic Literature Reviews with the same goal and the found studies do not answer our question. Hence, we performed a Systematic Literature Review (SLR) to investigate solutions to the SPI Diagnostic process. We executed an SLR, based on snowballing technique. This SLR characterizes 14 solutions aiming at systematizing the SPI Diagnostic process through a method, model, or framework. As a result, we advocate that Artificial Intelligence (AI) based solutions should be more explored in research to deal with SPI Diagnostic complexity and, therefore helping the SPI Diagnostic.