Effort Estimation Model for Function Point Measurement

Software Cost Estimation is a practical process that is applied to find out basically the effort and development time requirements for a software product, which is going to be developed. The process starts with the planning phase activities and refined throughout the development. Various cost estimation models and methods are available to be used for software development process. The COCOMO, an algorithmic model is one example. Although it is hard to predict the exact size especially in terms of lines of code (LOC) of the project at the early stage, the COCOMO model takes LOC as an input to compute the project’s effort. Nowadays, software developers recognize the importance of the realistic estimates of effort to success management of software projects and having a realistic estimates at an early stage of a project life cycle which allow project managers and development organizations to manage resource effectively. This research work has generated an algorithmic effort estimation model for function points measurement. The function-point measurement metric, invented by Allan Albrecht of IBM in the middle of the 1970s was intended to help all the practitioners measure the size of a computerized business information system. Such sizes are needed as a component of a measurement of productivity in system development and maintenance activities and as a component of estimating the effort needed for such activities. Generally, most of the algorithmic models were generated based on historical projects, and therefore, the same methodology has been applied in this research work. The total of 2265 historical business information systems collected by International Software Benchmarking Standard Groups (ISBSG) has been used to generate and validate the model using statistical technique, known as linear regression analysis. We proposed that a project’s functionality in the terms of function points has an approximately linear relationship to the final effort computation. The investigation had carried out on between the functionality and final effort before the model was generated. Results show that there is an approximately linear relationship between the project’s functionality and final effort that is required in the development. On the other hand, the limits with 95% level of confidence have been attached together with the model to ensure that the actual effort always falls within the predicted boundary. However, we suggest that further investigation should be carried on for the technical complexity factors in function point analysis in order to increase the accuracy of the forecasted project’s effort.

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