Software development effort estimation

Abstract: Accurate project effort prediction is an important goal for the software engineering community. To date most work has focused upon building algorithmic models of effort, for example COCOMO. These can be calibrated to local environments. We describe an alternative approach to estimation based upon the use of analogies. The underlying principle is to characterize projects in terms of features (for example, the number of interfaces, the development method or the size of the functional requirements document). Completed projects are stored and then the problem becomes one of finding the most similar projects to the one for which a prediction is required. Similarity is defined as Euclidean distance in n-dimensional space where n is the number of project features. Each dimension is standardized so all dimensions have equal weight. The known effort values of the nearest neighbors to the new project are then used as the basis for the prediction. The process is automated using a PC-based tool known as ANGEL. The method is validated on nine different industrial datasets (a total of 275 projects) and in all cases analogy outperforms algorithmic models based upon stepwise regression. From this work we argue that estimation by analogy is a viable technique that, at the very least, can be used by project managers to complement current estimation techniques.

Abstract: Practitioners have expressed concern over their inability to accurately estimate costs associated with software development. This concern has become even more pressing as costs associated with development continue to increase. As a result, considerable research attention is now directed at gaining a better understanding of the software-development process as well as constructing and evaluating software cost estimating tools. This paper evaluates four of the most popular algorithmic models used to estimate software costs (SLIM, COCOMO, Function Points, and ESTIMACS). Data on 15 large completed business data-processing projects were collected and used to test the accuracy of the models' ex post effort estimation. One important result was that Albrecht's Function Points effort estimation model was validated by the independent data provided in this study [3]. The models not developed in business data-processing environments showed significant need for calibration. As models of the software-development process, all of the models tested failed to sufficiently reflect the underlying factors affecting productivity. Further research will be required to develop understanding in this area.

Abstract: This paper aims to provide a basis for the improvement of software-estimation research through a systematic review of previous work. The review identifies 304 software cost estimation papers in 76 journals and classifies the papers according to research topic, estimation approach, research approach, study context and data set. A Web-based library of these cost estimation papers is provided to ease the identification of relevant estimation research results. The review results combined with other knowledge provide support for recommendations for future software cost estimation research, including: 1) increase the breadth of the search for relevant studies, 2) search manually for relevant papers within a carefully selected set of journals when completeness is essential, 3) conduct more studies on estimation methods commonly used by the software industry, and 4) increase the awareness of how properties of the data sets impact the results when evaluating estimation methods

Abstract: Application software development has been an area of organizational effort that has not been amenable to the normal managerial and cost controls. Instances of actual costs of several times the initial budgeted cost, and a time to initial operational capability sometimes twice as long as planned are more often the case than not.