The WyCash portfolio management system
OOPSLA '92 Addendum to the proceedings on Object-oriented programming systems, languages, and applications (Addendum)
Managerial Use of Metrics for Object-Oriented Software: An Exploratory Analysis
IEEE Transactions on Software Engineering
Journal of Systems and Software - Special issue on Evaluation and assessment in software engineering
Does Code Decay? Assessing the Evidence from Change Management Data
IEEE Transactions on Software Engineering
Evaluating the Impact of Object-Oriented Design on Software Quality
METRICS '96 Proceedings of the 3rd International Symposium on Software Metrics: From Measurement to Empirical Results
A Practical Model for Measuring Maintainability
QUATIC '07 Proceedings of the 6th International Conference on Quality of Information and Communications Technology
Managing technical debt in software-reliant systems
Proceedings of the FSE/SDP workshop on Future of software engineering research
VALID '10 Proceedings of the 2010 Second International Conference on Advances in System Testing and Validation Lifecycle
Deriving metric thresholds from benchmark data
ICSM '10 Proceedings of the 2010 IEEE International Conference on Software Maintenance
ACM SIGSOFT Software Engineering Notes
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Cunningham introduced the metaphor of technical debt as guidance for software developers that must trade engineering quality against short-term goals. We revisit the technical debt metaphor, and translate it into terms that can help IT executives better understand their IT investments. An approach is proposed to quantify debts (cost to fix technical quality issues) and interest (extra cost spent on maintenance due to technical quality issues). Our approach is based on an empirical assessment method of software quality developed at the Software Improvement Group (SIG). The core part of the technical debt calculation is constructed on the basis of empirical data of 44 systems that are currently being monitored by SIG. In a case study, we apply the approach to a real system, and discuss how the results provide useful insights on important questions related to IT investment such as the return on investment (ROI) in software quality improvement.