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DTSTART;TZID=America/New_York:20260420T100000
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 0260420T233000
URL;TYPE=URI:https://www.wpi.edu/news/calendar/events/syste
 ms-engineering-phd-dissertation-defense-zakaria-ouzzif-zoom
Systems Engineering, PhD Dissertation Defense, By: Zakaria Ouzzif, via Zoom
\n\nImage\n  \n\n\n\nTitle:\nA Technical Debt Management Framework for Aero
 space Systems Engineering: An AI-Driven Approach to Test and Evaluation Do
 cumentation Analysis\n\nAbstract:\nUnmanaged technical debt in aerospace s
 ystems engineering has produced consequences ranging from the Hubble Space
  Telescope's $629 million on-orbit correction to the Mars Climate Orbiter'
 s $327.6 million total mission loss. Despite three decades of growing rese
 arch attention, detection methods remain anchored in software-centric assu
 mptions that do not hold at the physical integration boundaries where aero
 space systems are most vulnerable. This dissertation develops and validate
 s a Technical Debt Management Framework (TDMF) for identifying, classifyin
 g, and prioritizing technical debt during the test and evaluation (T\&E) p
 hase of systems engineering projects. The framework is operationalized thr
 ough the Aerospace Technical-debt Learning and Assessment System (ATLAS), 
 a domain-specific AI tool that applies large language model classification
  to unstructured T\&E documentation.\n\nThe research follows a Design Scie
 nce Research methodology with three evaluation streams: ATLAS classifier p
 erformance on 141 aerospace T\&E documents (F1 = 0.82, κ = 0.84), retrosp
 ective validation against the HST and MCO programs, and an expert survey (
 n = 35) confirming 97% positive adoption intent and a 45% reduction in med
 ian review time.\n\nThis work contributes to the body of knowledge by:\n\n
 \nIntroducing a systems-engineering-specific technical debt taxonomy with 
 bidirectional leading-indicator mappings calibrated to aerospace practice.
 \nValidating an AI architecture demonstrating that few-shot LLM classifica
 tion achieves documentation-scale analysis in safety-critical domains with
 out task-specific fine-tuning.\nProviding empirical evidence that the fram
 ework resolves the asymmetric detection gap at hardware–software boundar
 ies where 78% of aerospace technical debt manifests.\n\n\nDepartment of Sy
 stems Engineering | Worcester Polytechnic Institute 100 Institute Road | W
 orcester, MA 01609-2280\n\nAdvisor:\nProf. Shamsnaz Bhada\nECE Department,
  WPI\n\nCommittee Members:\nProf. Jamie Monat\nECE Department, WPI\nBeth W
 ilson\nECE Department, WPI\nLarry Rosser\nRTX Corporation\n
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