Improving Software Size Estimation Using Data Complexity (Case Study: Research and Community Service Monitoring Apps)

The Research and Community Service Monitoring Apps is an essential application for managing and evaluating research and community service activities. In research related to software size estimation, the complexity of data is often disregarded. Nevertheless, in the realm of software development, data is regarded as an integral complement to the system, thus its presence is inherently factored into size computations. This study employs a hybrid approach, combining the Common Software Measurement International Consortium (COSMIC) functional size measurement with the database complexity index (DBCI). With a focus on the “Research and Community Service Monitoring Apps,” the research delineates four essential stages: (1) the calculation of actual effort, (2) determining data movement complexity through COSMIC FSM, (3) assessing database complexity using DBCI, and (4) estimating the system's size. The outcomes reveal the data movement complexity based on COSMIC FSM to be 80, while the database complexity is 196. The comparison between estimated software size and actual effort expended yields 43.75%. However, the study is limited by the absence of source code calculation or alternative methods, leading to fluctuating comparisons between estimation and actual effort.