用于自动代码更新的AI

2022 IEEE/ACM 44th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP) Pub Date : 2022-05-01 DOI:10.1145/3510457.3513073

Salwa Alamir, Petr Babkin, N. Navarro, Sameena Shah

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引用次数: 2

摘要

大多数现代代码库广泛依赖外部库来提供开箱即用的健壮功能。当这些库更新时，它们有时会在流程中引入破坏性的更改，这需要大量的开发人员维护。为了缓解这个问题，我们建议使用人工智能来解析发行说明的文本，以结构化的形式捕获代码弃用。反过来，这使我们能够开发一个IDE插件，它可以自动检测实时代码库中不推荐的库用法，甚至建议修复。我们在摩根大通的30多个内部项目中评估了我们的系统。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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AI for Automated Code Updates

Most modern code bases extensively rely on external libraries to provide robust functionality out of the box. When these libraries are updated they can sometimes introduce breaking changes in the process, which require extensive developer maintenance. To mitigate this we propose to use artificial intelligence to parse the text of release notes to capture code deprecations in structured form. This, in turn, enables us to develop an IDE plugin that can automatically detect deprecated library usages in live code bases and even suggest recommended fixes. We evaluated our system on over 30 internal projects within J.P. Morgan.

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2022 IEEE/ACM 44th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)

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