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AMRerank: A Framework for Library Migration Recommendations Using Multi‐Agent Analysis and Data‐Driven Reranking.

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Název: AMRerank: A Framework for Library Migration Recommendations Using Multi‐Agent Analysis and Data‐Driven Reranking.
Autoři: Luo, Jie, Huang, Zijie, Gao, Jianhua, Sarwar, Nadeem
Zdroj: IET Software (Wiley-Blackwell); 1/6/2026, Vol. 2026, p1-18, 18p
Témata: SOFTWARE libraries (Computer programming), SOFTWARE engineering, RECOMMENDER systems, INFERENCE (Logic), MAINTENANCE costs, DATA analysis
Abstrakt: Open‐source libraries are indispensable for modern software development but can create substantial maintenance burdens when they become deprecated or unmaintained. Selecting an appropriate replacement among many candidates remains challenging, since methods relying only on historical mining or similarity metrics often miss subtle differences in meaning. We propose AMRerank, a novel framework that integrates multi‐agent qualitative analysis with a data‐driven, interpretable reranking model. AMRerank first deploys specialized agents to examine and classify semantic relationships between libraries, generating evidence‐backed labels and concise summaries. An interpretable reranking framework then fuses these qualitative signals with heuristic and semantic features to produce a fine‐grained, explainable ranking. Evaluated on the GT2014 benchmark against competitive baselines (LMG, MMR, MMRLC), AMRerank achieves Precision@1 of 0.899 and mean reciprocal rank (MRR) of 0.928. As our case studies show, the system provides actionable, human‐readable evidence that helps developers make more reliable migration choices. [ABSTRACT FROM AUTHOR]
Copyright of IET Software (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Databáze: Complementary Index
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  Data: AMRerank: A Framework for Library Migration Recommendations Using Multi‐Agent Analysis and Data‐Driven Reranking.
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  Data: IET Software (Wiley-Blackwell); 1/6/2026, Vol. 2026, p1-18, 18p
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  Data: Open‐source libraries are indispensable for modern software development but can create substantial maintenance burdens when they become deprecated or unmaintained. Selecting an appropriate replacement among many candidates remains challenging, since methods relying only on historical mining or similarity metrics often miss subtle differences in meaning. We propose AMRerank, a novel framework that integrates multi‐agent qualitative analysis with a data‐driven, interpretable reranking model. AMRerank first deploys specialized agents to examine and classify semantic relationships between libraries, generating evidence‐backed labels and concise summaries. An interpretable reranking framework then fuses these qualitative signals with heuristic and semantic features to produce a fine‐grained, explainable ranking. Evaluated on the GT2014 benchmark against competitive baselines (LMG, MMR, MMRLC), AMRerank achieves Precision@1 of 0.899 and mean reciprocal rank (MRR) of 0.928. As our case studies show, the system provides actionable, human‐readable evidence that helps developers make more reliable migration choices. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of IET Software (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1049/sfw2/2169889
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        Text: English
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              Text: 1/6/2026
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