Quantitative and qualitative analyses of requirements elaboration for early software size estimation

Software size is one of the most influential inputs of a software cost estimation model. Improving the accuracy of size estimates is, therefore, instrumental in improving the accuracy of cost estimates. Moreover, software size and cost estimates have the highest utility at the time of inception. This is the time when most important decisions e.g. budget allocation, personnel allocation, etc. are taken. The dilemma, however, is that only high-level requirements for a project are available at this stage. Leveraging this high-level information to produce an accurate estimate of software size is an extremely challenging task.;Requirements for a software project are expressed at multiple levels of detail during its life cycle. At inception, requirements are expressed as high-level goals. With the passage of time, goals are refined into shall statements and shall statements into use cases. This process of progressive refinement of a project's requirements, referred to as requirements elaboration, continues till source code is obtained. This research analyzes the quantitative and qualitative aspects of requirements elaboration to address the challenge of early size estimation.;A series of four empirical studies is conducted to obtain a better understanding of requirements elaboration. The first one lays the foundation for the quantitative measurement of this abstract process by defining the appropriate metrics. It, however, focuses on only the first stage of elaboration. The second study builds on the foundation laid by the first. It examines the entire process of requirements elaboration looking at each stage of elaboration individually. A general process for collecting and processing multi-level requirements to obtain elaboration data useful for early size estimation is described. Application of this general process to estimate the size of a new project is also illustrated.;The third and fourth empirical studies are designed to tease out the factors determining the variation in each stage of elaboration. The third study focuses on analyzing the efficacy of COCOMO II cost drivers in predicting these variations. The fourth study performs a comparative analysis of the elaboration data from two different sources i.e. small real-client e-services projects and multiple versions of an industrial process management tool.