Refining the Use Case Classification for Use Case Point Method for Software Effort Estimation

Software cost estimation is a key open issue for the software industry, which suffers from cost overruns frequently. As the most popular technique for object-oriented software cost estimation is Use Case Points (UCP) method, however, it has two major drawbacks: the uncertainty of the cost factors and the abrupt classification. To address these two issues, refined the use case complexity classification using fuzzy logic theory which mitigate the uncertainty of cost factors and improve the accuracy of classification. Software estimation is a crucial task in software engineering. Software estimation encompasses cost, effort, schedule, and size. The importance of software estimation becomes critical in the early stages of the software life cycle when the details of software have not been revealed yet. Several commercial and non-commercial tools exist to estimate software in the early stages. Most software effort estimation methods require software size as one of the important metric inputs and consequently, software size estimation in the early stages becomes essential. The proposed method presents a techniques using fuzzy logic theory to improve the accuracy of the use case points method by refining the use case classification.