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2025 | OriginalPaper | Buchkapitel

An Automated Approach to Identify Source Code Files Affected by Architectural Technical Debt

verfasst von : Armando Sousa, Lincoln Rocha, Ricardo Britto, Guilherme Avelino

Erschienen in: Product-Focused Software Process Improvement. Industry-, Workshop-, and Doctoral Symposium Papers

Verlag: Springer Nature Switzerland

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Abstract

Architectural Technical Debt (ATD) is a persistent challenge in software development, often hindered by the absence of comprehensive architectural documentation. This research presents an automated approach to detect source code files indicative of ATD within a version control system. By analyzing code metrics, change history, and architectural smells, we identify files exhibiting signs of increasing complexity and maintenance effort. Our method was applied to the Apache Cassandra repository and validated through interviews with Ericsson developers. Results indicate a strong correlation between files with specific architectural smells, frequent modifications, and growing complexity, and the presence of ATD. This study demonstrates the feasibility of using source code analysis to systematically identify potential architectural issues, aiding developers in prioritizing refactoring efforts and improving software quality.

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Vorheriges Kapitel Adopting Continuous Deployment in a Public Administration Project: An Industrial Case Study

Nächstes Kapitel On the Derivation of Quality Assurance Plans from Process Model Descriptions

https://cassandra.apache.org.

https://www.sonarqube.org.

https://www.hello2morrow.com/products/sonargraph.

https://www.intooitus.com/products/infusion.

https://github.com/apache/cassandra.

Replication kit: https://anonymous.4open.science/r/mycassandra-32D3.

https://github.com/ishepard/pydriller.

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Titel: An Automated Approach to Identify Source Code Files Affected by Architectural Technical Debt
verfasst von: Armando Sousa
Lincoln Rocha
Ricardo Britto
Guilherme Avelino
Verlag: Springer Nature Switzerland
Buch: Product-Focused Software Process Improvement. Industry-, Workshop-, and Doctoral Symposium Papers
Print ISBN: 978-3-031-78391-3

Electronic ISBN: 978-3-031-78392-0

Copyright-Jahr: 2025
DOI: https://doi.org/10.1007/978-3-031-78392-0_7

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