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2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)最新文献

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We’ll Fix it in Post: What Do Bug Fixes in Video Game Update Notes Tell Us? 我们将在Post中修复它:电子游戏更新说明中的Bug修复告诉我们什么?
2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) Pub Date : 2021-05-01 DOI: 10.1109/ICSE-Companion52605.2021.00120
Andrew Truelove, E. Almeida, Iftekhar Ahmed
{"title":"We’ll Fix it in Post: What Do Bug Fixes in Video Game Update Notes Tell Us?","authors":"Andrew Truelove, E. Almeida, Iftekhar Ahmed","doi":"10.1109/ICSE-Companion52605.2021.00120","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00120","url":null,"abstract":"Bugs that persist into releases of video games can have negative impacts on both developers and users, but particular aspects of testing in game development can lead to difficulties in effectively catching these missed bugs. It has become common practice for developers to apply updates to games in order to fix missed bugs. These updates are often accompanied by notes that describe the changes to the game included in the update. However, some bugs reappear even after an update attempts to fix them. In this paper, we develop a taxonomy for bug types in games that is based on prior work. We examine 12,122 bug fixes from 723 updates for 30 popular games on the Steam platform. We label the bug fixes included in these updates to identify the frequency of these different bug types, the rate at which bug types recur over multiple updates, and which bug types are treated as more severe. Additionally, we survey game developers regarding their experience with different bug types and what aspects of game development they most strongly associate with bug appearance. We find that Information bugs appear the most frequently in updates, while Crash bugs recur the most frequently and are often treated as more severe than other bug types. Finally, we find that challenges in testing, code quality, and bug reproduction have a close association with bug persistence. These findings should help developers identify which aspects of game development could benefit from greater attention in order to prevent bugs. Researchers can use our results in devising tools and methods to better identify and address certain bug types.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117232399","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
A Survey on Method Naming Standards: Questions and Responses Artifact 方法命名标准综述:问题与回答工件
2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) Pub Date : 2021-05-01 DOI: 10.1109/ICSE-Companion52605.2021.00112
Reem S. Alsuhaibani, Christian D. Newman, M. J. Decker, M. Collard, J. Maletic
{"title":"A Survey on Method Naming Standards: Questions and Responses Artifact","authors":"Reem S. Alsuhaibani, Christian D. Newman, M. J. Decker, M. Collard, J. Maletic","doi":"10.1109/ICSE-Companion52605.2021.00112","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00112","url":null,"abstract":"The artifacts of a large (+1100 responses) survey of professional software developers concerning standards for naming source code methods is presented. The artifact consists of the survey questions along with all the responses from participants. The artifact allows other researchers to examine and study the responses to the survey.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114165971","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
MUTAGEN: Faster Mutation-Based Random Testing MUTAGEN:更快的基于突变的随机测试
2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) Pub Date : 2021-05-01 DOI: 10.1109/ICSE-Companion52605.2021.00053
Agustín Mista
{"title":"MUTAGEN: Faster Mutation-Based Random Testing","authors":"Agustín Mista","doi":"10.1109/ICSE-Companion52605.2021.00053","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00053","url":null,"abstract":"We present MUTAGEN, a fully automated mutation-oriented framework for property-based testing. Our tool usesnovel heuristics to improve the performance of the testing loop, and it is capable of finding complex bugs within seconds. We evaluate MUTAGEN by generating random WebAssembly programs that we use to find bugs in a faulty validator.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125765377","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
An Empirical Assessment of Global COVID-19 Contact Tracing Applications 全球COVID-19接触者追踪应用的实证评估
2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) Pub Date : 2021-05-01 DOI: 10.1109/ICSE-Companion52605.2021.00074
Ruoxi Sun, Wen Wang, Minhui Xue, Gareth Tyson, S. Çamtepe, D. Ranasinghe
{"title":"An Empirical Assessment of Global COVID-19 Contact Tracing Applications","authors":"Ruoxi Sun, Wen Wang, Minhui Xue, Gareth Tyson, S. Çamtepe, D. Ranasinghe","doi":"10.1109/ICSE-Companion52605.2021.00074","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00074","url":null,"abstract":"This is the artifact accompanying the paper \"An Empirical Assessment of Global COVID-19 Contact Tracing Applications\", accepted by ICSE 2021. The artifact presents the first automated security and privacy assessment tool that tests contact tracing apps for security weaknesses, malware, embedded trackers and private information leakage. COVIDGUARDIAN outperforms 4 state-of-the-practice industrial and open-source tools. Note that, Although the tool is tailored to focus on contact tracing apps, it can also be adapted to other types of apps with respect to the NLP PII learning context, e.g., by changing the source & sink list or updating the sensitive PII keywords.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126695741","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
Artifact: Distribution-Aware Testing of Neural Networks Using Generative Models 工件:使用生成模型的神经网络的分布感知测试
2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) Pub Date : 2021-05-01 DOI: 10.1109/ICSE-Companion52605.2021.00091
Swaroopa Dola, Matthew B. Dwyer, M. Soffa
{"title":"Artifact: Distribution-Aware Testing of Neural Networks Using Generative Models","authors":"Swaroopa Dola, Matthew B. Dwyer, M. Soffa","doi":"10.1109/ICSE-Companion52605.2021.00091","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00091","url":null,"abstract":"The artifact used for the experimental evaluation of Distribution-Aware Testing of Neural Networks Using Generative Models is publicly available on GitHub and it is reusable. The artifact consists of python scripts, trained deep neural network model files and data required for running the experiments. It is also provided as a VirtualBox VM image for reproducing the paper results. Users should be familiar with using VirtualBox software and Linux platform to reproduce or reuse the artifact.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126751411","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
Understanding Language Selection in Multi-language Software Projects on GitHub 理解GitHub上多语言软件项目中的语言选择
2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) Pub Date : 2021-05-01 DOI: 10.1109/ICSE-Companion52605.2021.00119
Wen Li, Na Meng, Li Li, Haipeng Cai
{"title":"Understanding Language Selection in Multi-language Software Projects on GitHub","authors":"Wen Li, Na Meng, Li Li, Haipeng Cai","doi":"10.1109/ICSE-Companion52605.2021.00119","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00119","url":null,"abstract":"There are hundreds of programming languages available for software development today. As a result, modern software is increasingly developed in multiple languages. In this context, there is an urgent need for automated tools for multi-language software quality assurance. To that end, it is useful to first understand how languages are chosen by developers in multi-language software projects. One intuitive perspective towards the understanding would be to explore the potential functionality relevance of those choices. With a plethora of publicly hosted multi-language software projects available on GitHub, we were able to obtain thousands of popular, relevant repositories across 10 years from 2010 to 2019 to enable the exploration. We start by estimating the functionality domain of each project through topic modeling, followed by studying the statistical correlation between these domains and language selection over all the sample projects through association mining. We proceed with an evolutionary characterization of these projects to provide a longitudinal view of how the association has changed over the years. Our findings offer useful insights into the rationale behind developers' choices of language combinations in multi-language software construction.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126592036","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: 13
Distribution Awareness for AI System Testing AI系统测试的分布意识
2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) Pub Date : 2021-05-01 DOI: 10.1109/ICSE-Companion52605.2021.00045
David Berend
{"title":"Distribution Awareness for AI System Testing","authors":"David Berend","doi":"10.1109/ICSE-Companion52605.2021.00045","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00045","url":null,"abstract":"As Deep Learning (DL) is continuously adopted in many safety critical applications, its quality and reliability start to raise concerns. Similar to the traditional software development process, testing the DL software to uncover its defects at an early stage is an effective way to reduce risks after deployment. Although recent progress has been made in designing novel testing techniques for DL software, the distribution of generated test data is not taken into consideration. It is therefore hard to judge whether the identified errors are indeed meaningful errors to the DL application. Therefore, we propose a new distribution aware testing technique which aims to generate new unseen test cases relevant to the underlying DL system task. Our results show that this technique is able to filter up to 55.44% of error test case on CIFAR-10 and is 10.05% more effective in enhancing robustness.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116498299","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
FastCA: An Effective and Efficient Tool for Combinatorial Covering Array Generation FastCA:一种有效的组合覆盖阵列生成工具
2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) Pub Date : 2021-05-01 DOI: 10.1109/ICSE-Companion52605.2021.00040
Jinkun Lin, Shaowei Cai, Bing He, Yingjie Fu, Chuan Luo, Qingwei Lin
{"title":"FastCA: An Effective and Efficient Tool for Combinatorial Covering Array Generation","authors":"Jinkun Lin, Shaowei Cai, Bing He, Yingjie Fu, Chuan Luo, Qingwei Lin","doi":"10.1109/ICSE-Companion52605.2021.00040","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00040","url":null,"abstract":"Combinatorial interaction testing (CIT) is a popular approach to detecting faults in highly configurable software systems. The core task of CIT is to generate a small test suite called a t-way covering array (CA), where t is the covering strength. A major drawback of existing solvers for CA generation is that they usually need considerable time to obtain a high-quality solution, which hinders its wider applications. In this paper, we describe FastCA, an effective and efficient tool for generating constrained CAs. We observe that the high time consumption of existing meta-heuristic algorithms is mainly due to the procedure of score computation. To this end, we present a much more efficient method for score computation. Thanks to this new lightweight score computation method, FastCA can work in the gradient mode to effectively explore the search space. Experiments on a broad range of real-world benchmarks and synthetic benchmarks show that FastCA significantly outperforms state-of-the-art solvers, in terms of both the size of obtained covering array and the run time. Video: https://youtu.be/-6CuojQIt-kRepository: https://github.com/jkunlin/FastCATool.git","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130322170","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
Finding Metamorphic Relations for Scientific Software 寻找科学软件的变质关系
2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) Pub Date : 2021-05-01 DOI: 10.1109/ICSE-Companion52605.2021.00118
Xuanyi Lin, Zedong Peng, Nan Niu, Wentao Wang, Hui Liu
{"title":"Finding Metamorphic Relations for Scientific Software","authors":"Xuanyi Lin, Zedong Peng, Nan Niu, Wentao Wang, Hui Liu","doi":"10.1109/ICSE-Companion52605.2021.00118","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00118","url":null,"abstract":"Metamorphic testing uncovers defects by checking whether a relation holds among multiple software executions. These relations are known as metamorphic relations (MRs). For scientific software operating in a large multi-parameter input space, identifying MRs that determine the simultaneous changes among multiple variables is challenging. In this poster, we propose a fully automatic approach to classifying input and output variables from scientific software’s user manual, mining these variables’ associations from the user forum to generate MRs, and validating the MRs with existing regression tests. Preliminary results of our end-to-end MR support for the Storm Water Management Model (SWMM) are reported.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131062407","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
COSTER: A Tool for Finding Fully Qualified Names of API Elements in Online Code Snippets COSTER:在在线代码片段中查找API元素的完全限定名称的工具
2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) Pub Date : 2021-05-01 DOI: 10.1109/ICSE-Companion52605.2021.00039
C. Saifullah, M. Asaduzzaman, C. Roy
{"title":"COSTER: A Tool for Finding Fully Qualified Names of API Elements in Online Code Snippets","authors":"C. Saifullah, M. Asaduzzaman, C. Roy","doi":"10.1109/ICSE-Companion52605.2021.00039","DOIUrl":"https://doi.org/10.1109/ICSE-Companion52605.2021.00039","url":null,"abstract":"Code snippets available on question answering sites (e.g., Stack Overflow) are a great source of information for learning how to use APIs. However, it is difficult to determine which APIs are discussed in those code snippets because they often suffer from declaration ambiguities and missing external references. In this paper, we introduce COSTER, a context-sensitive type solver that can determine the fully qualified names (FQNs) of API elements in those code snippets. The tool uses three different similarity measures to rank potential FQNs of a query API element. Results from our quantitative evaluation and user study demonstrate that the proposed tool can not only recommend FQNs of API elements with great accuracy but can also help developers to reuse online code snippets by suggesting the required import statements.","PeriodicalId":136929,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114152130","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
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