Involving Data Complexity in Software Size Estimation Based on Conceptual Data Model (Case Study: Catering Management Information System)

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Renny Sari Dewi, Ivory Inggri Mahadewi, Ayu Febrini Putri, Najmi Khairunnisa Gunawan, Tria Rizki Rosmalia, Adillah Rodiah, Aura Diva Nadira, Hafizah Aryani

2024 ICECOS 2024 - 4th International Conference on Electrical Engineering and Computer Science, Proceeding Conference paper Cited by 1 Quartile

Abstract

This research focuses on software size estimation, which often ignores aspects of data complexity. Software estimation generally only considers the difficulty of source code development and the experience of the development team. Ideally, software development should consider the difficulty of source code development and data in a balanced way. However, in practice, data is often considered an integral part of the system so it is included in the size estimation. This research uses a combination method between COSMIC Function Point Analysis (CFP) and Database Complexity Index (DBCI). The combination of CFP and DBCI is used as the main method to estimate the size of the Catering Management Information System. This research consists of four main stages: (1) actual business calculation, (2) database complexity calculation using DBCI, (3) data movement complexity calculation using COSMIC FSM, and (4) calculation of the estimated size. The results show that the data complexity is 32, while the database complexity is 221. The comparison between the estimated software size and the actual effort shows a difference of 31.68 percent. The limitation of this research is the absence of source code calculation or other methods, so the comparison between estimation and actual effort becomes unstable. © 2024 IEEE.

Affiliations

Universitas Negeri Surabaya, Department of Digital Business, Surabaya, Indonesia