Quantifying the benefits of code hints for refactoring deprecated Java APIs

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Bibliografski detalji
Izdano u:arXiv.org (Dec 11, 2024), p. n/a
Glavni autor: Cristina, David
Daljnji autori: Kesseli, Pascal, Kroening, Daniel, Zhang, Hanliang
Izdano:
Cornell University Library, arXiv.org
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Online pristup:Citation/Abstract
Full text outside of ProQuest
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022 |a 2331-8422 
035 |a 3143450437 
045 0 |b d20241211 
100 1 |a Cristina, David 
245 1 |a Quantifying the benefits of code hints for refactoring deprecated Java APIs 
260 |b Cornell University Library, arXiv.org  |c Dec 11, 2024 
513 |a Working Paper 
520 3 |a When done manually, refactoring legacy code in order to eliminate uses of deprecated APIs is an error-prone and time-consuming process. In this paper, we investigate to which degree refactorings for deprecated Java APIs can be automated, and quantify the benefit of Javadoc code hints for this task. To this end, we build a symbolic and a neural engine for the automatic refactoring of deprecated APIs. The former is based on type-directed and component-based program synthesis, whereas the latter uses LLMs. We applied our engines to refactor the deprecated methods in the Oracle JDK 15. Our experiments show that code hints are enabling for the automation of this task: even the worst engine correctly refactors 71% of the tasks with code hints, which drops to at best 14% on tasks without. Adding more code hints to Javadoc can hence boost the refactoring of code that uses deprecated APIs. 
653 |a Application programming interface 
653 |a Error analysis 
653 |a Building codes 
700 1 |a Kesseli, Pascal 
700 1 |a Kroening, Daniel 
700 1 |a Zhang, Hanliang 
773 0 |t arXiv.org  |g (Dec 11, 2024), p. n/a 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3143450437/abstract/embedded/ZKJTFFSVAI7CB62C?source=fedsrch 
856 4 0 |3 Full text outside of ProQuest  |u http://arxiv.org/abs/2412.08041