Quality Based Software Project Staffing and Scheduling with Cost Bound

Software project planning is becoming more complicated and important as the size of software project grows. Many approaches have been proposed to help project managers by providing optimal staffing and scheduling in terms of minimizing the cost (i.e., necessary expanse) or time (i.e., time span or duration) required for the software project. Unfortunately, the software quality, another critical factor in software project planning, is largely overlooked in previous work. In this paper, we propose the quality based software project staffing and scheduling approach using a genetic algorithm (GA). We define a quality score by considering practical issues in software project planning in addition to task severity and defect amplification model. Further, the cost is utilized as a cost-bound in the GA to consider not only quality but also cost. Case study shows that the proposed approach improves the quality while the cost is optimized as the same as the cost-based approach. In other words, we provide better software project plans considering both cost and quality for software project managers. Also, we show the relationship between the quality and the cost in terms of software project planning.