Collabcrew—an intelligent tool for dynamic task allocation within a software development team

Abstract

Currently in the IT industry, the people factor has become very critical when determining the quality of a software project. It is highly important that the correct person performs the relevant task and proper human resource allocation happens within the software project team to obtain successful outcome. This often needs critical thinking, regular team meetings and discussions. Typically a software project manager needs to be highly experienced with the team for this purpose and can be really complex and time consuming with the limited project schedules. This research work introduces a task management tool - CollabCrew specially designed for the software development teams which dynamically allocate tasks based on the skills and previous work done by the team members. This uses historical data from its' own repository or from an external source to find useful information of the previous work done by the project team members to automatically allocate them for new tasks. This proposed system will be containing an Extract, Transform and Load (ETL) tool which will extract data from different data sources, a prediction model to predict the aptness of each team member for a given task and a peer review mining and summarization component to provide a viable way to extract features from peer reviews. Then based on the result, the task allocation component will do the allocations in the most optimal and the feasible way for the project. Even though there are several commercially available task management tools, none has an intelligent component to automatically delegate work within the team. The scope of this work extends beyond the IT domain and a similar procedure can be adopted to develop a task allocation framework in other fields as well.