Fuzzy definition for tasks and resources categorization in Software projects

Abstract

Risk in software development process is an event that if allowed to occur can cause a major hazard in the development process and subsequently, deterioration in software quality. Risk reduction has been a major concern to software project stakeholders. A major way of preventing risks is to get the tasks and resource combination / allocation right from onset in software development. Otherwise, it could lead to major bottleneck; one that can either halt project temporarily, extending delivery date or cause a total stoppage of the project. To forestall such occurrence, this work looked into tasks and resources combination for software projects by remodeling the risk identification procedure of an existing risk model (the Riskit model)- introduced by Kontio and Basili.

A typical project process to depict the risk identification procedure of the original riskit model was arranged, the risk identification stage was then redesigned and broken down into different parts; the total RAG time (RAG_T) was generated in the process. The main task-resource fuzzification then took place in Part C and project information update took place in Part D of the system. Pointer setting to risky task was estimated from the difficulty level of the task-hours (X_t) and the required resources (X_h) and categorized using trapezoidal membership function in fuzzy logic. The resulting system later named ERAM was compared with Brainstorming and Riskit Analysis Graph technique (BRAG) using runtime and task segments performed by both models.

Applying the task –resource combination, the result showed that the original model BRAG took 88 minutes while ERAM generated a faster advisory output in 3 seconds with X_tX_h coordinate W between 0.9 -1.0. Again, the study revealed that time saving is not the only benefit if resource (X_h) and Task (or task hour (X_t)) combination and categorization is properly done. BRAG yearly runtime estimate was 237 hours at overhead cost of ₦3,051,612 while ERAM was 2.6 hours at overhead cost of ₦37,078.

The study concluded that ERAM is adequate in speedy classification of software project constituents, early risk identification, reduction in delivery time and cost. Therefore, it is recommended that software risks experts and project managers adopt ERAM to increase speed in risk identification, gain ample time for other project activities and reduced overhead cost.