사전 정보를 이용한 소프트웨어 개발노력 추정 신경망 구조 결정 = Decision of Neural Network Architecture for Software Development Effort Estimation using Prior Information

다국어 초록 (Multilingual Abstract)

An increasingly important facet of software development is the ability to estimate the associate cost and effort of development early in the development life cycle. Most of the proposed models are based upon a combination of intuition, expert judgement, and regression analysis of empirical data. Overall, the work has failed to produce any single model that can be applied with a reasonable degree of success to a variety of environments. This paper presents a neural network (NN) model that related software development effort to software size measured in function element types. The heuristic approach is applied to decide the number of hidden neurons in NN from the relationship between input-output pairs. The research describes appropriate NN modeling in the context of a case study for 24 software development projects. Also, this paper compared the NN model with a regression analysis model and found the NN model has better accuracy.