2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)最新文献_第10页

TrEKer: Tracing error propagation in operating system kernels 在操作系统内核中跟踪错误传播

2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2017-10-30 DOI: 10.1109/ASE.2017.8115650

Nicolas Coppik, Oliver Schwahn, Stefan Winter, N. Suri

{"title":"TrEKer: Tracing error propagation in operating system kernels","authors":"Nicolas Coppik, Oliver Schwahn, Stefan Winter, N. Suri","doi":"10.1109/ASE.2017.8115650","DOIUrl":"https://doi.org/10.1109/ASE.2017.8115650","url":null,"abstract":"Modern operating systems (OSs) consist of numerous interacting components, many of which are developed and maintained independently of one another. In monolithic systems, the boundaries of and interfaces between such components are not strictly enforced at runtime. Therefore, faults in individual components may directly affect other parts of the system in various ways. Software fault injection (SFI) is a testing technique to assess the resilience of a software system in the presence of faulty components. Unfortunately, SFI tests of OSs are inconclusive if they do not lead to observable failures, as corruptions of the internal software state may not be visible at its interfaces and, yet, affect the subsequent execution of the OS beyond the duration of the test. In this paper we present TREKER, a fully automated approach for identifying how faulty OS components affect other parts of the system. TREKER combines static and dynamic analyses to achieve efficient tracing on the granularity of memory accesses. We demonstrate TrEKer's ability to support SFI oracles by accurately tracing the effects of faults injected into three widely used Linux kernel modules.","PeriodicalId":382876,"journal":{"name":"2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128196341","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: 11

EventFlowSlicer: A tool for generating realistic goal-driven GUI tests EventFlowSlicer:一个生成现实目标驱动GUI测试的工具

2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2017-10-30 DOI: 10.1109/ASE.2017.8115711

Jonathan A. Saddler, Myra B. Cohen

{"title":"EventFlowSlicer: A tool for generating realistic goal-driven GUI tests","authors":"Jonathan A. Saddler, Myra B. Cohen","doi":"10.1109/ASE.2017.8115711","DOIUrl":"https://doi.org/10.1109/ASE.2017.8115711","url":null,"abstract":"Most automated testing techniques for graphical user interfaces (GUIs) produce test cases that are only concerned with covering the elements (widgets, menus, etc.) on the interface, or the underlying program code, with little consideration of test case semantics. This is effective for functional testing where the aim is to find as many faults as possible. However, when one wants to mimic a real user for evaluating usability, or when it is necessary to extensively test important end-user tasks of a system, or to generate examples of how to use an interface, this generation approach fails. Capture and replay techniques can be used, however there are often multiple ways to achieve a particular goal, and capturing all of these is usually too time consuming and unrealistic. Prior work on human performance regression testing introduced a constraint based method to filter test cases created by a functional test case generator, however that work did not capture the specifications, or directly generate only the required tests and considered only a single type of test goal. In this paper we present EventFlowSlicer, a tool that allows the GUI tester to specify and generate all realistic test cases relevant to achieve a stated goal. The user first captures relevant events on the interface, then adds constraints to provide restrictions on the task. An event flow graph is extracted containing only the widgets of interest for that goal. Next all test cases are generated for edges in the graph which respect the constraints. The test cases can then be replayed using a modified version of GUITAR. A video demonstration of EventFlowSlicer can be found at https://youtu.be/hw7WYz8WYVU.","PeriodicalId":382876,"journal":{"name":"2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130232337","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

DSSynth: An automated digital controller synthesis tool for physical plants DSSynth:用于物理工厂的自动数字控制器合成工具

2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2017-10-30 DOI: 10.1109/ASE.2017.8115705

A. Abate, I. Bessa, Dario Cattaruzza, Lennon C. Chaves, L. Cordeiro, C. David, Pascal Kesseli, D. Kroening, E. Polgreen

引用次数: 6

RuntimeSearch: Ctrl+F for a running program RuntimeSearch: Ctrl+F表示正在运行的程序

2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2017-10-30 DOI: 10.1109/ASE.2017.8115651

Matúš Sulír, J. Porubän

引用次数: 2

The impact of continuous integration on other software development practices: A large-scale empirical study 持续集成对其他软件开发实践的影响:一项大规模的实证研究

2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2017-10-30 DOI: 10.1109/ASE.2017.8115619

Yangyang Zhao, Alexander Serebrenik, Yuming Zhou, V. Filkov, Bogdan Vasilescu

引用次数: 135

IntPTI: Automatic integer error repair with proper-type inference IntPTI:具有适当类型推断的自动整数错误修复

2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2017-10-30 DOI: 10.1109/ASE.2017.8115718

Xi Cheng, Min Zhou, Xiaoyu Song, M. Gu, Jiaguang Sun

{"title":"IntPTI: Automatic integer error repair with proper-type inference","authors":"Xi Cheng, Min Zhou, Xiaoyu Song, M. Gu, Jiaguang Sun","doi":"10.1109/ASE.2017.8115718","DOIUrl":"https://doi.org/10.1109/ASE.2017.8115718","url":null,"abstract":"Integer errors in C/C++ are caused by arithmetic operations yielding results which are unrepresentable in certain type. They can lead to serious safety and security issues. Due to the complicated semantics of C/C++ integers, integer errors are widely harbored in real-world programs and it is error-prone to repair them even for experts. An automatic tool is desired to 1) automatically generate fixes which assist developers to correct the buggy code, and 2) provide sufficient hints to help developers review the generated fixes and better understand integer types in C/C++. In this paper, we present a tool IntPTI that implements the desired functionalities for C programs. IntPTI infers appropriate types for variables and expressions to eliminate representation issues, and then utilizes the derived types with fix patterns codified from the successful human-written patches. IntPTI provides a user-friendly web interface which allows users to review and manage the fixes. We evaluate IntPTI on 7 real-world projects and the results show its competitive repair accuracy and its scalability on large code bases. The demo video for IntPTI is available at: https://youtu.be/9Tgd4A_FgZM.","PeriodicalId":382876,"journal":{"name":"2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121448162","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: 16

SentiCR: A customized sentiment analysis tool for code review interactions SentiCR:用于代码审查交互的定制情感分析工具

2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2017-10-30 DOI: 10.1109/ASE.2017.8115623

Toufique Ahmed, Amiangshu Bosu, Anindya Iqbal, S. Rahimi

引用次数: 110

BProVe: A formal verification framework for business process models BProVe:业务流程模型的正式验证框架

2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2017-10-30 DOI: 10.1109/ASE.2017.8115635

F. Corradini, Fabrizio Fornari, A. Polini, B. Re, F. Tiezzi, Andrea Vandin

{"title":"BProVe: A formal verification framework for business process models","authors":"F. Corradini, Fabrizio Fornari, A. Polini, B. Re, F. Tiezzi, Andrea Vandin","doi":"10.1109/ASE.2017.8115635","DOIUrl":"https://doi.org/10.1109/ASE.2017.8115635","url":null,"abstract":"Business Process Modelling has acquired increasing relevance in software development. Available notations, such as BPMN, permit to describe activities of complex organisations. On the one hand, this shortens the communication gap between domain experts and IT specialists. On the other hand, this permits to clarify the characteristics of software systems introduced to provide automatic support for such activities. Nevertheless, the lack of formal semantics hinders the automatic verification of relevant properties. This paper presents a novel verification framework for BPMN 2.0, called BProVe. It is based on an operational semantics, implemented using MAUDE, devised to make the verification general and effective. A complete tool chain, based on the Eclipse modelling environment, allows for rigorous modelling and analysis of Business Processes. The approach has been validated using more than one thousand models available on a publicly accessible repository. Besides showing the performance of BProVe, this validation demonstrates its practical benefits in identifying correctness issues in real models.","PeriodicalId":382876,"journal":{"name":"2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131636212","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: 24

Towards the automatic classification of traceability links 实现可追溯性环节的自动分类

2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2017-10-30 DOI: 10.1109/ASE.2017.8115723

Chris Mills

{"title":"Towards the automatic classification of traceability links","authors":"Chris Mills","doi":"10.1109/ASE.2017.8115723","DOIUrl":"https://doi.org/10.1109/ASE.2017.8115723","url":null,"abstract":"A wide range of text-based artifacts contribute to software projects (e.g., source code, test cases, use cases, project requirements, interaction diagrams, etc.). Traceability Link Recovery (TLR) is the software task in which relevant documents in these various sets are linked to one another, uncovering information about the project that is not available when considering only the documents themselves. This information is helpful for enabling other tasks such as improving test coverage, impact analysis, and ensuring that system or regulatory requirements are met. However, while traceability links are useful, performing TLR manually is time consuming and fraught with error. Previous work has applied Information Retrieval (IR) and other techniques to reduce the human effort involved; however, that effort remains significant. In this research we seek to take the next step in reducing it by using machine learning (ML) classification models to predict whether a candidate link is valid or invalid without human oversight. Preliminary results show that this approach has promise for accurately recommending valid links; however, there are several challenges that still must be addressed in order to achieve a technique with high enough performance to consider it a viable, completely automated solution.","PeriodicalId":382876,"journal":{"name":"2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128053424","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

Renaming and shifted code in structured merging: Looking ahead for precision and performance 结构化合并中的重命名和移位代码:展望精度和性能

2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2017-10-30 DOI: 10.1109/ASE.2017.8115665

Olaf Leßenich, S. Apel, Christian Kästner, Georg Seibt, J. Siegmund

{"title":"Renaming and shifted code in structured merging: Looking ahead for precision and performance","authors":"Olaf Leßenich, S. Apel, Christian Kästner, Georg Seibt, J. Siegmund","doi":"10.1109/ASE.2017.8115665","DOIUrl":"https://doi.org/10.1109/ASE.2017.8115665","url":null,"abstract":"Diffing and merging of source-code artifacts is an essential task when integrating changes in software versions. While state-of-the-art line-based merge tools (e.g., git merge) are fast and independent of the programming language used, they have only a low precision. Recently, it has been shown that the precision of merging can be substantially improved by using a language-aware, structured approach that works on abstract syntax trees. But, precise structured merging is NP hard, especially, when considering the notoriously difficult scenarios of renamings and shifted code. To address these scenarios without compromising scalability, we propose a syntax-aware, heuristic optimization for structured merging that employs a lookahead mechanism during tree matching. The key idea is that renamings and shifted code are not arbitrarily distributed, but their occurrence follows patterns, which we address with a syntax-specific lookahead. Our experiments with 48 real-world open-source projects (4,878 merge scenarios with over 400 million lines of code) demonstrate that we can significantly improve matching precision in 28 percent of cases while maintaining performance.","PeriodicalId":382876,"journal":{"name":"2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132257936","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: 20