Seventh International Workshop on Managing Technical Debt Collection
October 2015 • Presentation
This collection includes presentations from the Seventh International Workshop on Managing Technical Debt. Participants shared approaches to software maintenance and evolution.
Software Engineering Institute
Technical debt is a metaphor that software developers and managers increasingly use to communicate key trade-offs related to time planning and quality issues. The Managing Technical Debt workshop series has, since 2010, brought together practitioners and researchers to discuss and define issues related to technical debt and how they can be studied. This collection includes presenations about tools for measuring and managing technical debt, application of financial theories, source code analysis, code smells, refactoring, decision making, and empirical industrial studies.
The workshop summary was published as Technical Debt: Broadening Perspectives Report on the Seventh Workshop on Managing Technical Debt (MTD 2015), ACM SIGSOFT Software Engineering Notes, Volume 41, Issue 2, March 2016, pages 38-41.
The proceedings are available at IEEE Xplore.
Sessions and presentations included:
- A Contextualized Vocabulary Model for Identifying Technical Debt in Code Comments, Mário André, André Batista, Manoel Mendonça, and Rodrigo O. Spínola
- A Framework to Aid in Decision Making for Technical Debt Management, Carlos Fernández-Sánchez, Agustín Yagüe, and Juan Garbajosa
- Detecting and Quantifying Different Types of Self-Admitted Technical Debt, Everton da S. Maldonado and Emad Shihab
- Estimating the Breaking Point for Technical Debt, Alexander Chatzigeorgiou, Apostolos Ampatzoglou, Areti Ampatzoglou, and Theodoros Amanatidis
- Identifying and Visualizing Architectural Debt and Its Efficiency Interest in the Automotive Domain: A Case Study, Ulf Eliasson, Antonio Martini, Robert Kaufmann, and Sam Odeh
- Technical Debt of Standardized Test Software, Kristóf Szabados and Attila Kovács
- The Restructuring and Refinancing of Technical Debt, Raul Zablah and Chris Murphy
- Towards an Open-Source Tool for Measuring and Visualizing the Interest of Technical Debt, Davide Falessi and Andreas Reichel
- Towards a Prioritization of Code Debt: A Code Smell Intensity Index, Francesca Arcelli Fontana, Vincenzo Ferme, and Marco Zanoni