A Systematic Review on Software Project Scheduling and Task Assignment Approaches

Abstract

Software Project Scheduling and Task Assignment are important integral aspects of software project management and contributes to the overall success of software projects. Key objective of Task scheduling/ assignment is to minimize the cost and time of the project. This article i.e. a systematic literature review, is in-fact the first of its kind, conducted in the context of task scheduling and assignment in software industry. This study specifically elaborates the models used in task assignment and summarizes the techniques/ machine learning algorithms to solve the software project scheduling problem (SPSP). Our Initial search brought out 1100 research articles. However, after applying the inclusion and exclusion criteria, 23 most relevant researches were segregated and thereafter thoroughly reviewed. The review revealed that there are 2 types of basic models of Task Scheduling i.e. static and dynamic, however, static models are most widely used. For Task Scheduling, evolutionary algorithms, whereas, for Task Assignment, Support Vector Machine (SVM) algorithms are most widely used. Due to lack of real-world data in software projects, most of the researches utilized synthetic data sets for Task Assignment. Exploring the Task Assignment tools during the course of review process, 7 tools were identified, however, TAMRI has been graded as most efficient.