Predicting Software Size Based on Conceptual Data Model (Case Study: Shrimp Pond System Management)

Farming application requires precise software size estimation. This work suggests a combination technique employing the database complexity index (DBCI) and COSMIC Functional Size Measurement (COSMIC FSM) to assess the size of a prawn farming management system, whereas existing methods frequently ignore data complexity. There are four steps in the suggested method: (1) determining the real effort; (2) utilising DBCI to calculate database complexity; (3) utilising COSMIC FSM to calculate data movement complexity; and (4) assessing the amount of estimated size toward actual size. The findings of this research is 57.5 percent deviation between actual effort and estimated size using DBCI and COSMIC FSM. This study emphasises how crucial it is to take data complexity into account when estimating the size of software, especially for systems that largely rely on data, like shrimp ponds management systems. The suggested technique offers a more thorough and precise means of calculating programme size, which helps to improve project planning, resource allocation, and overall software development efficiency.