Software Engineering Team Evaluation: Decision Support System to Predict the Monitor Team Activities

Due to rapid changes in user requirements (UR), it is a challenging task for software engineers to cope with the sudden software customization requirements (SSCR). The incremental process model (IPM) provides a dynamic approach for analysing, designing and implementing a particular software unit (SU), but the successful deployment requires customer satisfaction as per UR by following the SSCR. For example, during each phase every development team member (DTM) is assigned some particular tasks to accomplish, but it is difficult to determine the team members’ behaviour and performance (TMBP). A successful implementation of customized software would provide more opportunities for a particular company to attract a maximum number of users by using SSCR. Some very nice approaches have been seen over the past two decades to predict DTM to assess their accomplished activities TMBP. This paper proposes a system by offering three layered methodology where first layer is designed for data pre-processing and in the second layer construct the decision model by using ensemble machine-learning technique however the third layer used for result visualization. This paper contributes (a) a novel decision support system to understand the TMBP for the waterfall process model (b) IPM and (c) best classification accuracy 94.14%.