Handling imprecision in inputs using fuzzy logic to predict effort in software development

Accurate, precise and reliable estimates of effort at early stages of project development holds great significance for the industry to meet the competitive demands of today's world. The inherent imprecision present in the inputs of the algorithmic models like constructive cost model (COCOMO) yields imprecision in the output, resulting in erroneous effort estimation. The development of software is characterized by parameters that possess certain level of fuzziness which requires that some degree of uncertainty be introduced in the models, in order to make the models realistic. Fuzzy logic based cost estimation models enable linguistic representation of the input and output of a model to address the vagueness and imprecision in the inputs, to make reliable and accurate estimates of effort. In this paper, we present an enhanced fuzzy logic based framework for software development effort prediction. The intermediate COCOMO is extended in the proposed study by incorporating the concept of fuzziness into the measurements of size, mode of development for projects and the cost drivers contributing to the overall development effort. The said framework tolerates imprecision, incorporates experts knowledge, explains prediction rationale through rules, offers transparency in the prediction system, and could adapt to changing environments with the availability of new data.