Characterizing Technical Debt and Antipatterns in AI-Based Systems: A Systematic Mapping Study
收藏NIAID Data Ecosystem2026-03-12 收录
下载链接：
https://zenodo.org/record/4457215
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资源简介：
All artifacts related to a systematic mapping study on technical debt and antipatterns in AI-based systems; the data consists of an Excel file (00-all-data.xlsx) which includes a tab for all important constructs plus a separate CSV file per construct:
List of primary studies (01-primary-studies.csv)
Established types of technical debt (02-established-td-types.csv)
New types of technical debt (03-new-td-types.csv)
Affected software quality attributes (04-affected-qas.csv)
Identified antipatterns (05-antipatterns.csv)
Reported solutions to address technical debt or antipatterns (06-solutions.csv)
创建时间：
2021-03-10
