Title: Software effort estimation using validated accuracy points for open-source packaged software

Authors: Anitha Gracy Jeyaram; Chandrakumar Thangavel; Parthasarathy Sudhaman; Vaishnavi Vijayaragavan; Premnitin Premkanth

Addresses: Department of Applied Mathematics and Computational Science, Thiagarajar College of Engineering, Madurai, Tamilnadu, India ' Department of Applied Mathematics and Computational Science, Thiagarajar College of Engineering, Madurai, Tamilnadu, India ' Department of Applied Mathematics and Computational Science, Thiagarajar College of Engineering, Madurai, Tamilnadu, India ' Department of Applied Mathematics and Computational Science, Thiagarajar College of Engineering, Madurai, Tamilnadu, India ' Department of Applied Mathematics and Computational Science, Thiagarajar College of Engineering, Madurai, Tamilnadu, India

Abstract: The current trend is open-source software (OSS), which organisations can use and change to fulfil product needs. This study introduces validated accuracy points (VAP) to properly estimate effort for open-source code-based packaged software, such as enterprise resource planning (ERP) that was built using agile methods. This study employed 14 software projects from one company. This research compares different software effort estimation methods using machine learning (ML) algorithms like extreme gradient boosting (XGB) to validate the package points (PP) and validated accuracy points (VAP) with mean squared error (MSE) for startup companies that use customised open-source packaged software packages.

Keywords: package points; function points; lines of code; object points; open source; agile method; machine learning; effort estimation; extreme gradient boosting; XGB.

DOI: 10.1504/IJPQM.2025.150888

International Journal of Productivity and Quality Management, 2025 Vol.46 No.4, pp.481 - 499

Received: 17 Feb 2023
Accepted: 12 Jul 2023
Published online: 05 Jan 2026 *

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