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

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A Static Analysis Framework for Data Science Notebooks 数据科学笔记本的静态分析框架
Pavle Suboti'c, Lazar Miliki'c, M. Stojic
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引用次数: 11
Mining Idioms in the Wild 野外采矿习语
Aishwarya Sivaraman, Rui Abreu, Andrew C. Scott, Tobi Akomolede, S. Chandra
{"title":"Mining Idioms in the Wild","authors":"Aishwarya Sivaraman, Rui Abreu, Andrew C. Scott, Tobi Akomolede, S. Chandra","doi":"10.1145/3510457.3513046","DOIUrl":"https://doi.org/10.1145/3510457.3513046","url":null,"abstract":"Existing code repositories contain numerous instances of code patterns that are idiomatic ways of accomplishing a particular programming task. Sometimes, the programming language in use supports specific operators or APIs that can express the same idiomatic imperative code much more succinctly. However, those code patterns linger in repositories because the developers may be unaware of the new APIs or have not gotten around to them. Detection of idiomatic code can also point to the need for new APIs. We share our experiences in mining imperative idiomatic patterns from the Hack repo at Facebook. We found that existing techniques either cannot identify meaningful patterns from syntax trees or require test-suite-based dynamic analysis to incorporate semantic properties to mine useful patterns. The key insight of the approach proposed in this paper – Jezero – is that semantic idioms from a large codebase can be learned from canonicalized dataflow trees. We propose a scalable, lightweight static analysis-based approach to construct such a tree that is well suited to mine semantic idioms using nonparametric Bayesian methods. Our experiments with Jezero on Hack code show a clear advantage of adding canonicalized dataflow information to ASTs: Jezero was significantly more effective in finding new refactoring opportunities from unannotated legacy code than a baseline that did not have the dataflow augmentation.","PeriodicalId":119790,"journal":{"name":"2022 IEEE/ACM 44th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)","volume":"116 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131236011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Improving Code Autocompletion with Transfer Learning 用迁移学习改进代码自动完成
Wenjie Zhou, Seohyun Kim, V. Murali, Gareth Ari Aye
{"title":"Improving Code Autocompletion with Transfer Learning","authors":"Wenjie Zhou, Seohyun Kim, V. Murali, Gareth Ari Aye","doi":"10.1145/3510457.3513061","DOIUrl":"https://doi.org/10.1145/3510457.3513061","url":null,"abstract":"Software language models have achieved promising results predicting code completion usages, and several industry studies have described successful IDE integration. Recently, accuracy in autocompletion prediction improved 12.8%[2] from training on a real-world dataset collected from programmers’ IDE activities. But what if the number of examples of IDE autocompletion in the target programming language is inadequate for model training? In this paper, we highlight practical reasons for this inadequacy, and make a call to action in using transfer learning to overcome the issue.","PeriodicalId":119790,"journal":{"name":"2022 IEEE/ACM 44th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117266478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
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