Addressing Technical Debt in Software-Intensive Systems with Carnegie Mellon University Software Engineering Institute

  • 3/27/2024 1:00 - 2:00 pm ET
  • Event Type : Webinar
    Event Code : 4R04


During this presentation, Dr. Ipek Ozkaya and Brigid O'Hearn from Carnegie Mellon University’s Software Engineering Institute (SEI), will give insight into the challenges that DOD and defense industry face in addressing technical debt in software. Technical debt is defined as “an element of design or implementation that is expedient in the short term, but that would result in a technical context that can make a future change costlier or impossible.”

Dr. Ozkaya and Ms. O’ Hearn led SEI’s Congressionally-mandated Technical Debt Study, whose findings and recommendations were delivered to Congress in December 2023. The presentation after will provide a review of fundamental concepts in managing technical debt, will give details from the report which describes the conduct of the study, summarizes the technical trends observed, and presents the resulting recommendations for improving technical debt in Department of Defense software intensive-systems.

The study concludes that some DOD programs are aware of the importance of managing technical debt. Furthermore, a number of DoD programs have established practices to actively manage technical debt. During this study, the DoD published several guidance documents that begin to include technical debt and technical debt management as an essential practice for successful software development. Study recommendations include that the DoD must continue to update policy/guidance and empower programs to incorporate technical debt practices as part of their software development activities while enabling research in improved tool support and data collection.

Report to the Congressional Defense Committees on National Defense Authorization Act (NDAA) for Fiscal Year 2022 Section 835 Independent Study on Technical Debt in Software-Intensive Systems (


Undral Dalai
(703) 247-2582

Addressing Technical Debt in Software-Intensive Systems