A Tool For Selecting Suitable Software Project Effort Estimation Model At Early Phases

Abstract

Effort estimation is one of the important factors affecting the success of software projects. In order to support this, many effort estimation methods have been developed from past to present. The reliability of the effort estimation of a project depends on the choice of the most appropriate method for the project characteristics and the estimation context. Even if a good performing method is used, the estimation results may remain to be inaccurate if an appropriate estimation method is not selected as appropriate to the project context. In this study, we proposed a tool for selecting the most suitable estimation method for a software project by considering the project characteristics and the stakeholder needs. To do this, first, an expert-opinion survey was prepared based on the key features of the commonly used estimation methods that have been frequently referred to in literature. The expert-opinion survey was answered by experts who carried out scientific studies in the field of software effort estimation. Then, a questionnaire was built for eliciting information about project characteristics from an estimator who wants to carry out effort estimation for his/her project. In this phase, firstly, a decision matrix was created in the light of experts’ opinions. With the decision matrix, the estimator can select the most suitable method for his/her estimation by answering the questionnaire. Secondly, another approach was created as a decision mechanism. The decision mechanism has two steps. First, prepared decision tree is run and second, multi-criteria decision analysis (MCDA) methodologies are used among the models that are the result of the first elimination with the estimator’s opinions. A tool was developed for the simpler use of this approach. Accordingly, estimator is provided to select the best-fit method using the tool without needing to know the calculation details of the selection. The tool proposes the most appropriate method by first following the decision tree mechanism and then calculating the method ranks. To investigate the validity of the proposed approach, sample studies were conducted and the questionnaire was answered using the ISBSG dataset. Also, we prepared a multiple-case study for the validation of the approach proposed. At the end of the study, the appropriateness of the proposed approach was discussed.