Technical Debt Assessment
Technical Debt Assessment is a systematic evaluation method used in software engineering and cloud migration contexts to identify, quantify, and prioritize accumulated deviations from optimal design, implementation, or architectural practices that may impede future system maintainability, scalability, or evolution.
247
Publications
11.7K
Citations
501
Authors
229
Institutions
Publications per year
2017–2026
140
Variants
Technical Debt Evaluation
247
Technical Debt: From Metaphor to Theory and Practice
Philippe Kruchten, Robert L. Nord, İpek Özkaya · IEEE Software · 2012 · 691 citations
The ML test score: A rubric for ML production readiness and technical debt reduction
Eric Breck, Shanqing Cai, Eric Nielsen et al. · 2017 · 256 citations
1–5 of 247
501
University of Maryland, Baltimore County, United States
25 publications · 1.8K citations
18
h-index
18
h-index
15
h-index
15
h-index
15
h-index
1–5 of 501
229

Universidade Federal da Bahia
Salvador, Brazil
17 h-index
50 publications
2.9K citations

University of Macedonia
Thessaloniki, Greece
17 h-index
49 publications
2.4K citations

Universidade Salvador
Salvador, Brazil
16 h-index
24 publications
2.1K citations
University of Maryland, Baltimore County
Baltimore, United States
14 h-index
19 publications
1.3K citations
Montana State University
Bozeman, United States
14 h-index
28 publications
977 citations
Chalmers University of Technology
Gothenburg, Sweden
14 h-index
34 publications
1.7K citations

University of British Columbia
Vancouver, Canada
13 h-index
16 publications
1.6K citations

University of Groningen
Groningen, The Netherlands
13 h-index
40 publications
3.5K citations
1–8 of 229
JSS · 18 publications · 1.7K citations
17
h-index
14 publications · 1.2K citations
14
h-index
13 publications · 1.4K citations
13
h-index
10 publications · 458 citations
10
h-index
SEN · 8 publications · 246 citations
8
h-index
1–5