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Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings最新文献

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SimilarAPI
Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings Pub Date : 2020-06-27 DOI: 10.1145/3377812.3382140
Chunyang Chen
{"title":"SimilarAPI","authors":"Chunyang Chen","doi":"10.1145/3377812.3382140","DOIUrl":"https://doi.org/10.1145/3377812.3382140","url":null,"abstract":"Establishing API mappings between libraries is a prerequisite step for library migration tasks. Manually establishing API mappings is tedious due to the large number of APIs to be examined, and existing methods based on supervised learning requires unavailable already-ported or functionality similar applications. Therefore, we propose an unsupervised deep learning based approach to embed both API usage semantics and API description (name and document) semantics into vector space for inferring likely analogical API mappings between libraries. We implement a proof-of-concept website SimilarAPI (https://similarapi.appspot.com) which can recommend analogical APIs for 583,501 APIs of 111 pairs of analogical Java libraries with diverse functionalities. Video: https://youtu.be/EAwD6l24vLQ","PeriodicalId":421517,"journal":{"name":"Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116005766","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: 1
Phoenix 凤凰城
Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings Pub Date : 2020-06-27 DOI: 10.2307/j.ctvss3zpb.5
H. Yoshida, Rohan Bavishi, Keisuke Hotta, Yusuke Nemoto, M. Prasad, Shinji Kikuchi
{"title":"Phoenix","authors":"H. Yoshida, Rohan Bavishi, Keisuke Hotta, Yusuke Nemoto, M. Prasad, Shinji Kikuchi","doi":"10.2307/j.ctvss3zpb.5","DOIUrl":"https://doi.org/10.2307/j.ctvss3zpb.5","url":null,"abstract":"","PeriodicalId":421517,"journal":{"name":"Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124599813","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: 0
Open-vocabulary models for source code 源代码的开放词汇表模型
Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings Pub Date : 2020-06-27 DOI: 10.1145/3377812.3390806
Rafael-Michael Karampatsis, Hlib Babii, R. Robbes, Charles Sutton, Andrea Janes
{"title":"Open-vocabulary models for source code","authors":"Rafael-Michael Karampatsis, Hlib Babii, R. Robbes, Charles Sutton, Andrea Janes","doi":"10.1145/3377812.3390806","DOIUrl":"https://doi.org/10.1145/3377812.3390806","url":null,"abstract":"Statistical language modeling techniques have successfully been applied to large source code corpora, yielding a variety of new software development tools, such as tools for code suggestion, improving readability, and API migration. A major issue with these techniques is that code introduces new vocabulary at a far higher rate than natural language, as new identifier names proliferate. Both large vocabularies and out-of-vocabulary issues severely affect Neural Language Models (NLMs) of source code, degrading their performance and rendering them unable to scale. In this paper, we address this issue by: 1) studying how various modelling choices impact the resulting vocabulary on a large-scale corpus of 13,362 projects; 2) presenting an open vocabulary source code NLM that can scale to such a corpus, 100 times larger than in previous work, and outperforms the state of the art. To our knowledge, this is the largest NLM for code that has been reported.","PeriodicalId":421517,"journal":{"name":"Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121396289","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: 2
TimeTracer
Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings Pub Date : 2020-06-27 DOI: 10.1145/3377812.3382141
Christoph Mayr-Dorn, Michael Vierhauser, Felix Keplinger, Stefan Bichler, Alexander Egyed
{"title":"TimeTracer","authors":"Christoph Mayr-Dorn, Michael Vierhauser, Felix Keplinger, Stefan Bichler, Alexander Egyed","doi":"10.1145/3377812.3382141","DOIUrl":"https://doi.org/10.1145/3377812.3382141","url":null,"abstract":"Ensuring correct trace links between different types of artifacts (requirements, architecture, or code) is crucial for compliance in safety-critical domains, for consistency checking, or change impact assessment. The point in time when trace links are created, however, (i.e., immediately during development or weeks/months later) has a significant impact on its quality. Assessing quality thus relies on obtaining a historical view on artifacts and their trace links at a certain point in the past which provides valuable insights on when, how, and by whom, trace links were created. This work presents TimeTracer, a tool that allows engineers to go back in time – not just to view the history of artifacts but also the history of trace links associated with these artifacts. TimeTracer allows easy integration with different development support tools such as Jira; and it stores artifacts, traces, and changes thereof in a unified artifact model.","PeriodicalId":421517,"journal":{"name":"Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116115086","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: 6
GeekyNote
Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings Pub Date : 2020-06-27 DOI: 10.1145/3377812.3382136
Yung-Pin Cheng, Wei-Nien Hsiung, Yu-Shan Wu, Li-Hsuan Chen
{"title":"GeekyNote","authors":"Yung-Pin Cheng, Wei-Nien Hsiung, Yu-Shan Wu, Li-Hsuan Chen","doi":"10.1145/3377812.3382136","DOIUrl":"https://doi.org/10.1145/3377812.3382136","url":null,"abstract":"Understanding an unfamiliar program is always a daunting task for any programmer, either experienced or inexperienced. Many studies have shown that even an experienced programmer who is already familiar with the code may still need to rediscover the code frequently during software maintenance. The difficulties of program comprehension is much more intense when a system is completely new. One well-known solution to this notorious problem is to create effective technical documentation to make up for the lack of knowledge.The purpose of technical documentation is to achieve the transfer of knowledge. However, creating effective technical documentation has been impeded by many problems in practice [1]. In this paper, we propose a novel tool called GeekyNote to address the major challenges in technical documentation. The key ideas GeekyNote proposes are: (1) documents are annotated to versioned source code transparently; (2) formal textual writings are discouraged and screencasts (or other forms of documents) are encouraged; (3) the up-to-dateness between documents and code can be detected, measured, and managed; (4) the documentation that works like a debugging-trace is supported; (5) couplings can be easily created and managed for future maintenance needs; (6) how good a system is documented can be measured. A demo video can be accessed at https://youtu.be/cBueuPVDgWM.","PeriodicalId":421517,"journal":{"name":"Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117060596","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: 0
AppTestMigrator
Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings Pub Date : 2020-06-27 DOI: 10.1145/3377812.3382149
Farnaz Behrang, A. Orso
{"title":"AppTestMigrator","authors":"Farnaz Behrang, A. Orso","doi":"10.1145/3377812.3382149","DOIUrl":"https://doi.org/10.1145/3377812.3382149","url":null,"abstract":"The use of mobile apps is increasingly widespread, and much effort is put into testing these apps to make sure they behave as intended. In this demo, we present AppTestMigrator, a technique and tool for migrating test cases between apps with similar functionality. The intuition behind AppTestMigrator is that many apps share similarities in their functionality, and these similarities often result in conceptually similar user interfaces (through which that functionality is accessed). AppTestMigrator attempts to automatically transform the sequence of events and oracles in a test case for an app (source app) to events and oracles for another app (target app). The results of our preliminary evaluation show the effectiveness of AppTestMigrator in migrating test cases between mobile apps with similar functionality.Video URL: https://youtu.be/WQnfEcwYqa4","PeriodicalId":421517,"journal":{"name":"Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126807301","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: 2
FuRong
Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings Pub Date : 2020-06-27 DOI: 10.1145/3377812.3382138
Yuanhan Tian, Shengcheng Yu, Chunrong Fang, Peiyuan Li
{"title":"FuRong","authors":"Yuanhan Tian, Shengcheng Yu, Chunrong Fang, Peiyuan Li","doi":"10.1145/3377812.3382138","DOIUrl":"https://doi.org/10.1145/3377812.3382138","url":null,"abstract":"Automated testing has been widely used to ensure the quality of Android applications. However, incomprehensible testing results make it difficult for developers to understand and fix potential bugs. This paper proposes FuRong, a novel tool, to fuse bug reports of high-readability and strong-guiding-ability via analyzing the automated testing results on multi-devices. FuRong builds a bug model with complete context information, such as screenshots, operation sequences, and logs from multi-devices, and then leverages pretrained Decision Tree classifier (with 18 bug category labels) to classify bugs. FuRong deduplicates the classified bugs via Levenshtein distance and finally generates the easy-to-understand report, not only context information of bugs, where possible causes and fix suggestions for each bug category are also provided. An empirical study of 8 open-source Android applications with automated testing on 20 devices has been conducted, the results show the effectiveness of FuRong, which has a bug classification precision of 93.4% and a bug classification accuracy of 87.9%. Video URL: https://youtu.be/LUkFTc32B6k","PeriodicalId":421517,"journal":{"name":"Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130382922","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: 1
VITALSE VITALSE
Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings Pub Date : 2020-06-27 DOI: 10.1145/3377812.3382154
Devjeet Roy, Sarah Fakhoury, V. Arnaoudova
{"title":"VITALSE","authors":"Devjeet Roy, Sarah Fakhoury, V. Arnaoudova","doi":"10.1145/3377812.3382154","DOIUrl":"https://doi.org/10.1145/3377812.3382154","url":null,"abstract":"Recent research in empirical software engineering is applying techniques from neurocognitive science and breaking new grounds in the ways that researchers can model and analyze the cognitive processes of developers as they interact with software artifacts. However, given the novelty of this line of research, only one tool exists to help researchers represent and analyze this kind of multimodal biometric data. While this tool does help with visualizing temporal eyetracking and physiological data, it does not allow for the mapping of physiological data to source code elements, instead projecting information over images of code. One drawback of this is that researchers are still unable to meaningfully combine and map physiological and eye tracking data to source code artifacts. The use of images also bars the support of long or multiple code les, which prevents researchers from analyzing data from experiments conducted in realistic settings. To address these drawbacks, we propose VITALSE, a tool for the interactive visualization of combined multi-modal biometric data for software engineering tasks. VITALSE provides interactive and customizable temporal heatmaps created with synchronized eyetracking and biometric data. The tool supports analysis on multiple les, user defined annotations for points of interest over source code elements, and high level customizable metric summaries for the provided dataset. VITALSE, a video demonstration, and sample data to demonstrate its capabilities can be found at http://www.vitalse.app.","PeriodicalId":421517,"journal":{"name":"Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114302690","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: 4
Seraph 六翼天使
Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings Pub Date : 2020-06-27 DOI: 10.1145/3377812.3382157
Zhiqiang Yang, Han Liu, Yue Li, Huixuan Zheng, Lei Wang, Bangdao Chen
{"title":"Seraph","authors":"Zhiqiang Yang, Han Liu, Yue Li, Huixuan Zheng, Lei Wang, Bangdao Chen","doi":"10.1145/3377812.3382157","DOIUrl":"https://doi.org/10.1145/3377812.3382157","url":null,"abstract":"As blockchain becomes increasingly popular across various industries in recent years, many companies started designing and developing their own smart contract platforms to enable better services on blockchain. While smart contracts are notoriously known to be vulnerable to external attacks, such platform diversity further amplified the security challenge. To mitigate this problem, we designed the very first cross-platform security analyzer called Seraph for smart contracts. Specifically, Seraph enables automated security analysis for different platforms built on two mainstream virtual machine architectures, i.e, EVM and WASM. To this end, Seraph introduces a set of general connector API to abstract interactions between the virtual machine and blockchain, e.g., load and update storage data on blockchain. Moreover, we proposed the symbolic semantic graph to model critical dependencies and decoupled security analysis from contract code as well. Our preliminary evaluation on four existing smart contract platforms demonstrated the potential of Seraph in finding security threats both flexibly and accurately. A video of Seraph is available at https://youtu.be/wxixZkVqUsc.","PeriodicalId":421517,"journal":{"name":"Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127220276","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: 1
Refactor4Green Refactor4Green
Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings Pub Date : 2020-06-27 DOI: 10.1145/3377812.3390792
Vartika Agrahari, S. Chimalakonda
{"title":"Refactor4Green","authors":"Vartika Agrahari, S. Chimalakonda","doi":"10.1145/3377812.3390792","DOIUrl":"https://doi.org/10.1145/3377812.3390792","url":null,"abstract":"The rise in awareness of sustainable software has led to a focus on energy efficiency and consideration of code smells during soft-ware development. This eventually requires software engineering teachers to focus on topics such as code smells in their software engineering courses to bring awareness among students on the impact of code smells and bad design choices, not just for the soft-ware but also for the environment. Thus, we propose a desktop game named Refactor4Green to teach code smells and refactoring to novice programmers. The core idea of the game is to introduce code smells with refactoring choices through the theme of a green environment. We conducted a preliminary study with university students and got positive feedback from 83.06% of the participants.","PeriodicalId":421517,"journal":{"name":"Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128313077","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: 0
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