Open Access

ARTICLE

Individual Software Expertise Formalization and Assessment from Project Management Tool Databases

Traian-Radu Ploscă^1,*, Alexandru-Mihai Pescaru², Bianca-Valeria Rus¹, Daniel-Ioan Curiac^1,*

1 Department of Automation and Applied Informatics, Politehnica University of Timisoara, V. Parvan 2, Timisoara, 300223, Romania
2 Department of Computer and Information Technology, Politehnica University of Timisoara, V. Parvan 2, Timisoara, 300223, Romania

* Corresponding Authors: Traian-Radu Ploscă. Email: ; Daniel-Ioan Curiac. Email:

(This article belongs to the Special Issue: Emerging Machine Learning Methods and Applications)

Computers, Materials & Continua 2026, 86(1), 1-23. https://doi.org/10.32604/cmc.2025.069707

Received 29 June 2025; Accepted 13 October 2025; Issue published 10 November 2025

Abstract

Objective expertise evaluation of individuals, as a prerequisite stage for team formation, has been a long-term desideratum in large software development companies. With the rapid advancements in machine learning methods, based on reliable existing data stored in project management tools’ datasets, automating this evaluation process becomes a natural step forward. In this context, our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems. For this, we mathematically formalize two categories of expertise: technology-specific expertise, which denotes the skills required for a particular technology, and general expertise, which encapsulates overall knowledge in the software industry. Afterward, we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers (BERT)-like transformers to handle the unique characteristics of project tool datasets effectively. Finally, our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives. The method was experimentally validated, yielding promising results.

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Keywords

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