LLM approaches ExArch and ArTEMiS reach F1 scores of 0.86 and 0.81 for architecture entity recognition and traceability, matching or approaching baselines that require manual models.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
fields
cs.SE 3verdicts
UNVERDICTED 3representative citing papers
Describes a tool landscape (REST API, TraceView, TraceViz) that makes ARDoCo's four TLR pipelines publicly accessible with a preliminary study showing TraceViz improves developer comprehension.
Traditional documentation consistency checkers can detect stale code references in AI configuration artifacts, affecting 23% of a sample of 356 repositories.
citing papers explorer
-
Who's Who? LLM-assisted Software Traceability with Architecture Entity Recognition
LLM approaches ExArch and ArTEMiS reach F1 scores of 0.86 and 0.81 for architecture entity recognition and traceability, matching or approaching baselines that require manual models.
-
The ARDoCo Tool Landscape: REST API, TraceView, and TraceViz for Architecture Traceability
Describes a tool landscape (REST API, TraceView, TraceViz) that makes ARDoCo's four TLR pipelines publicly accessible with a preliminary study showing TraceViz improves developer comprehension.
-
Context Rot in AI-Assisted Software Development: Repurposing Documentation Consistency for AI Configuration Artifacts
Traditional documentation consistency checkers can detect stale code references in AI configuration artifacts, affecting 23% of a sample of 356 repositories.