Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering最新文献_第9页

Software Evolution Management with Differential Facts 具有不同事实的软件演化管理

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering Pub Date : 2022-10-10 DOI: 10.1145/3551349.3559513

Xiuheng Wu

引用次数: 0

V-Achilles: An Interactive Visualization of Transitive Security Vulnerabilities V-Achilles:传递性安全漏洞的交互式可视化

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering Pub Date : 2022-10-10 DOI: 10.1145/3551349.3559526

Vipawan Jarukitpipat, Klinton Chhun, Wachirayana Wanprasert, Chaiyong Ragkhitwetsagul, Morakot Choetkiertikul, T. Sunetnanta, R. Kula, Bodin Chinthanet, T. Ishio, Kenichi Matsumoto

引用次数: 0

Multi-objective Optimization-based Bug-fixing Template Mining for Automated Program Repair 基于多目标优化的自动程序修复bug模板挖掘

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering Pub Date : 2022-10-10 DOI: 10.1145/3551349.3559554

Misoo Kim, Youngkyoung Kim, Kicheol Kim, Eunseok Lee

{"title":"Multi-objective Optimization-based Bug-fixing Template Mining for Automated Program Repair","authors":"Misoo Kim, Youngkyoung Kim, Kicheol Kim, Eunseok Lee","doi":"10.1145/3551349.3559554","DOIUrl":"https://doi.org/10.1145/3551349.3559554","url":null,"abstract":"Template-based automatic program repair (T-APR) techniques depend on the quality of bug-fixing templates. For such templates to be of sufficient quality for T-APR techniques to succeed, they must satisfy three criteria: applicability, fixability, and efficiency. Existing template mining approaches select templates based only on the first criteria, and are thus suboptimal in their performance. This study proposes a multi-objective optimization-based bug-fixing template mining method for T-APR in which we estimate template quality based on nine code abstraction tasks and three objective functions. Our method determines the optimal code abstraction strategy (i.e., the optimal combination of abstraction tasks) which maximizes the values of three objective functions and generates a final set of bug-fixing templates by clustering template candidates to which the optimal abstraction strategy is applied. Our preliminary experiment demonstrated that our optimized strategy can improve templates’ applicability and efficiency by 7% and 146% over the existing mining technique, respectively. We therefore conclude that the multi-objective optimization-based template mining technique effectively finds high-quality bug-fixing templates.","PeriodicalId":197939,"journal":{"name":"Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121368779","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

A Light Bug Triage Framework for Applying Large Pre-trained Language Model 应用大型预训练语言模型的轻Bug分类框架

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering Pub Date : 2022-10-10 DOI: 10.1145/3551349.3556898

Jaehyung Lee, Kisun Han, Hwanjo Yu

{"title":"A Light Bug Triage Framework for Applying Large Pre-trained Language Model","authors":"Jaehyung Lee, Kisun Han, Hwanjo Yu","doi":"10.1145/3551349.3556898","DOIUrl":"https://doi.org/10.1145/3551349.3556898","url":null,"abstract":"Assigning appropriate developers to the bugs is one of the main challenges in bug triage. Demands for automatic bug triage are increasing in the industry, as manual bug triage is labor-intensive and time-consuming in large projects. The key to the bug triage task is extracting semantic information from a bug report. In recent years, large Pre-trained Language Models (PLMs) including BERT [4] have achieved dramatic progress in the natural language processing (NLP) domain. However, applying large PLMs to the bug triage task for extracting semantic information has several challenges. In this paper, we address the challenges and propose a novel framework for bug triage named LBT-P, standing for Light Bug Triage framework with a Pre-trained language model. It compresses a large PLM into small and fast models using knowledge distillation techniques and also prevents catastrophic forgetting of PLM by introducing knowledge preservation fine-tuning. We also develop a new loss function exploiting representations of earlier layers as well as deeper layers in order to handle the overthinking problem. We demonstrate our proposed framework on the real-world private dataset and three public real-world datasets [11]: Google Chromium, Mozilla Core, and Mozilla Firefox. The result of the experiments shows the superiority of LBT-P.","PeriodicalId":197939,"journal":{"name":"Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122943522","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: 7

Evolving Ranking-Based Failure Proximities for Better Clustering in Fault Isolation 基于进化排序的故障接近度在故障隔离中的应用

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering Pub Date : 2022-10-10 DOI: 10.1145/3551349.3556922

Yi Song, Xiaoyuan Xie, Xihao Zhang, Quanming Liu, Ruizhi Gao

{"title":"Evolving Ranking-Based Failure Proximities for Better Clustering in Fault Isolation","authors":"Yi Song, Xiaoyuan Xie, Xihao Zhang, Quanming Liu, Ruizhi Gao","doi":"10.1145/3551349.3556922","DOIUrl":"https://doi.org/10.1145/3551349.3556922","url":null,"abstract":"Failures that are not related to a specific fault can reduce the effectiveness of fault localization in multi-fault scenarios. To tackle this challenge, researchers and practitioners typically cluster failures (e.g., failed test cases) into several disjoint groups, with those caused by the same fault grouped together. In such a fault isolation process that requires input in a mathematical form, ranking-based failure proximity (R-proximity) is widely used to model failed test cases. In R-proximity, each failed test case is represented as a suspiciousness ranking list of program statements through a fingerprinting function (i.e., a risk evaluation formula, REF). Although many off-the-shelf REFs have been integrated into R-proximity, they were designed for single-fault localization originally. To the best of our knowledge, no REF has been developed to serve as a fingerprinting function of R-proximity in multi-fault scenarios. For better clustering failures in fault isolation, in this paper, we present a genetic programming-based framework along with a sophisticated fitness function, for evolving REFs with the goal of more properly representing failures in multi-fault scenarios. By using a small set of programs for training, we get a collection of REFs that can obtain good results applicable in a larger and more general scale of scenarios. The best one of them outperforms the state-of-the-art by 50.72% and 47.41% in faults number estimation and clustering effectiveness, respectively. Our framework is highly configurable for further use, and the evolved formulas can be directly applied in future failure representation tasks without any retraining.","PeriodicalId":197939,"journal":{"name":"Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131305341","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

Principled Composition of Function Variants for Dynamic Software Diversity and Program Protection 动态软件多样性和程序保护中功能变体的原则组合

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering Pub Date : 2022-10-10 DOI: 10.1145/3551349.3559553

Giacomo Priamo, Daniele Cono D'Elia, Leonardo Querzoni

引用次数: 0

Quacky: Quantitative Access Control Permissiveness Analyzer✱ Quacky:定量访问控制许可分析器:译者

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering Pub Date : 2022-10-10 DOI: 10.1145/3551349.3559530

William Eiers, G. Sankaran, Albert Li, Emily O'Mahony, Benjamin Prince, T. Bultan

引用次数: 1

A Unified Specification Mining Framework for Smart Contracts 智能合约的统一规范挖掘框架

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering Pub Date : 2022-10-10 DOI: 10.1145/3551349.3559512

Ye Liu

引用次数: 1

Groundhog: An Automated Accessibility Crawler for Mobile Apps 土拨鼠:移动应用程序的自动访问爬虫

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering Pub Date : 2022-10-10 DOI: 10.1145/3551349.3556905

Navid Salehnamadi, Forough Mehralian, S. Malek

{"title":"Groundhog: An Automated Accessibility Crawler for Mobile Apps","authors":"Navid Salehnamadi, Forough Mehralian, S. Malek","doi":"10.1145/3551349.3556905","DOIUrl":"https://doi.org/10.1145/3551349.3556905","url":null,"abstract":"Accessibility is a critical software quality affecting more than 15% of the world’s population with some form of disabilities. Modern mobile platforms, i.e., iOS and Android, provide guidelines and testing tools for developers to assess the accessibility of their apps. The main focus of the testing tools is on examining a particular screen’s compliance with some predefined rules derived from accessibility guidelines. Unfortunately, these tools cannot detect accessibility issues that manifest themselves in interactions with apps using assistive services, e.g., screen readers. A few recent studies have proposed assistive-service driven testing; however, they require manually constructed inputs from developers to evaluate a specific screen or presume availability of UI test cases. In this work, we propose an automated accessibility crawler for mobile apps, Groundhog, that explores an app with the purpose of finding accessibility issues without any manual effort from developers. Groundhog assesses the functionality of UI elements in an app with and without assistive services and pinpoints accessibility issues with an intuitive video of how to replicate them. Our experiments show Groundhog is highly effective in detecting accessibility barriers that existing techniques cannot discover. Powered by Groundhog, we conducted an empirical study on a large set of real-world apps and found new classes of critical accessibility issues that should be the focus of future work in this area.","PeriodicalId":197939,"journal":{"name":"Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123475606","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

The Metamorphosis: Automatic Detection of Scaling Issues for Mobile Apps 变形:移动应用程序缩放问题的自动检测

Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering Pub Date : 2022-10-10 DOI: 10.1145/3551349.3556935

Yuhui Su, Chun-Yu Chen, Junjie Wang, Zhe Liu, Dandan Wang, Shoubin Li, Qing Wang

{"title":"The Metamorphosis: Automatic Detection of Scaling Issues for Mobile Apps","authors":"Yuhui Su, Chun-Yu Chen, Junjie Wang, Zhe Liu, Dandan Wang, Shoubin Li, Qing Wang","doi":"10.1145/3551349.3556935","DOIUrl":"https://doi.org/10.1145/3551349.3556935","url":null,"abstract":"As the bridge between users and software, Graphical User Interface (GUI) is critical to the app accessibility. Scaling up the font or display size of GUI can help improve the visual impact, readability, and usability of an app, and is frequently used by the elderly and people with vision impairment. Yet this can easily lead to scaling issues such as text truncation, component overlap, which negatively influence the acquirement of the right information and the fluent usage of the app. Previous techniques for UI display issue detection and cross-platform inconsistency detection cannot work well for these scaling issues. In this paper, we propose an automated method, dVermin, for scaling issue detection, through detecting the inconsistency of a view under the default and a larger display scale. The evaluation result shows that dVermin achieves 97% precision and 97% recall in issue page detection, and 84% precision and 91% recall for issue view detection, outperforming two state-of-the-art baselines by a large margin. We also evaluate dVermin with popular Android apps on F-droid, and successfully uncover 21 previously-undetected scaling issues with 20 of them being confirmed/fixed.","PeriodicalId":197939,"journal":{"name":"Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115299504","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: 5