2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)最新文献

Generating Highly-structured Input Data by Combining Search-based Testing and Grammar-based Fuzzing 结合基于搜索的测试和基于语法的模糊测试生成高度结构化的输入数据

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3418930

Mitchell Olsthoorn, A. Deursen, Annibale Panichella

引用次数: 12

Styx: A Data-Oriented Mutation Framework to Improve the Robustness of DNN Styx:一个面向数据的突变框架，以提高深度神经网络的鲁棒性

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3418903

Meixi Liu, Weijiang Hong, Weiyu Pan, Chendong Feng, Zhenbang Chen, Ji Wang

引用次数: 2

Scalable Multiple-View Analysis of Reactive Systems via Bidirectional Model Transformations 通过双向模型转换的可伸缩反应系统多视图分析

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3416579

Christos Tsigkanos, Nianyu Li, Zhi Jin, Zhenjiang Hu, C. Ghezzi

{"title":"Scalable Multiple-View Analysis of Reactive Systems via Bidirectional Model Transformations","authors":"Christos Tsigkanos, Nianyu Li, Zhi Jin, Zhenjiang Hu, C. Ghezzi","doi":"10.1145/3324884.3416579","DOIUrl":"https://doi.org/10.1145/3324884.3416579","url":null,"abstract":"Systematic model-driven design and early validation enable engineers to verify that a reactive system does not violate its requirements before actually implementing it. Requirements may come from multiple stakeholders, who are often concerned with different facets - design typically involves different experts having different concerns and views of the system. Engineers start from a specification which may be sourced from some domain model, while validation is often done on state-transition structures that support model checking. Two computationally expensive steps may work against scalability: transformation from specification to state-transition structures, and model checking. We propose a technique that makes the former efficient and also makes the resulting transition systems small enough to be efficiently verified. The technique automatically projects the specification into submodels depending on a property sought to be evaluated, which captures some stakeholder's viewpoint. The resulting reactive system submodel is then transformed into a state-transition structure and verified. The technique achieves cone-of-influence reduction, by slicing at the specification model level. Submodels are analysis-equivalent to the corresponding full model. If stakeholders propose a change to a submodel based on their own view, changes are automatically propagated to the specification model and other views affected. Automated reflection is achieved thanks to bidirectional model transformations, ensuring correctness. We cast our proposal in the context of graph-based reactive systems whose dynamics is described by rewriting rules. We demonstrate our view-based framework in practice on a case study within cyber-physical systems.","PeriodicalId":106337,"journal":{"name":"2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130615842","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: 9

Synthesizing Smart Solving Strategy for Symbolic Execution 符号执行的综合智能求解策略

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3418904

Zehua Chen, Zhenbang Chen, Ziqi Shuai, Yufeng Zhang, Weiyu Pan

引用次数: 1

Continuous Compliance 连续的合规

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3416593

Martin Kellogg, Martin Schäf, S. Tasiran, Michael D. Ernst

{"title":"Continuous Compliance","authors":"Martin Kellogg, Martin Schäf, S. Tasiran, Michael D. Ernst","doi":"10.1145/3324884.3416593","DOIUrl":"https://doi.org/10.1145/3324884.3416593","url":null,"abstract":"Vendors who wish to provide software or services to large corporations and governments must often obtain numerous certificates of compliance. Each certificate asserts that the software satisfies a compliance regime, like SOC or the PCI DSS, to protect the privacy and security of sensitive data. The industry standard for obtaining a compliance certificate is an auditor manually auditing source code. This approach is expensive, error-prone, partial, and prone to regressions. We propose continuous compliance to guarantee that the codebase stays compliant on each code change using lightweight verification tools. Continuous compliance increases assurance and reduces costs. Continuous compliance is applicable to any source-code compliance requirement. To illustrate our approach, we built verification tools for five common audit controls related to data security: cryptographically unsafe algorithms must not be used, keys must be at least 256 bits long, credentials must not be hard-coded into program text, HTTPS must always be used instead of HTTP, and cloud data stores must not be world-readable. We evaluated our approach in three ways. (1) We applied our tools to over 5 million lines of open-source software. (2) We compared our tools to other publicly-available tools for detecting misuses of encryption on a previously-published benchmark, finding that only ours are suitable for continuous compliance. (3) We deployed a continuous compliance process at AWS, a large cloud-services company: we integrated verification tools into the compliance process (including auditors accepting their output as evidence) and ran them on over 68 million lines of code. Our tools and the data for the former two evaluations are publicly available.","PeriodicalId":106337,"journal":{"name":"2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128029455","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

A Program Verification based Approach to Find Data Race Vulnerabilities in Interrupt-driven Program 中断驱动程序中基于程序验证的数据竞争漏洞查找方法

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3418925

Haining Feng

引用次数: 0

The New Approach to IT Testing : Real Transaction-Based Automated Validation Solution IT测试的新方法:真正的基于事务的自动验证解决方案

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3421839

Yongsik Kim, SoAh Min, Youkyung Kim

引用次数: 0

Inferring and Applying Def-Use Like Configuration Couplings in Deployment Descriptors 在部署描述符中推断和应用类似自定义使用的配置耦合

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3416577

Chengyuan Wen, Yaxuan Zhang, Xiao He, Na Meng

{"title":"Inferring and Applying Def-Use Like Configuration Couplings in Deployment Descriptors","authors":"Chengyuan Wen, Yaxuan Zhang, Xiao He, Na Meng","doi":"10.1145/3324884.3416577","DOIUrl":"https://doi.org/10.1145/3324884.3416577","url":null,"abstract":"When building enterprise applications on Java frameworks (e.g., Spring), developers often specify components and configure operations with a special kind of XML files named “deployment descriptors (DD)”. Maintaining such XML files is challenging and time-consuming; because (1) the correct configuration semantics is domain-specific but usually vaguely documented, and (2) existing compilers and program analysis tools rarely examine XML files. To help developers ensure the quality of DD, this paper presents a novel approach-XEDITOR-that extracts configuration couplings (i.e., frequently co-occurring configurations) from DD, and adopts the coupling rules to validate new or updated files. Xeditor has two phases: coupling extraction and bug detection. To identify couplings, Xeditor first mines DD in open-source projects, and extracts XML entity pairs that (i) frequently coexist in the same files and (ii) hold the same data at least once. Xeditor then applies customized association rule mining to the extracted pairs. For bug detection, given a new XML file, Xeditor checks whether the file violates any coupling; if so, Xeditor reports the violation(s). For evaluation, we first created two data sets with the 4,248 DD mined from 1,137 GitHub projects. According to the experiments with these data sets, Xeditor extracted couplings with high precision (73%); it detected bugs with 92% precision, 96% recall, and 94% accuracy. Additionally, we applied Xeditor to the version history of another 478 GitHub projects. Xeditor identified 25 very suspicious XML updates, 15 of which were later fixed by developers.","PeriodicalId":106337,"journal":{"name":"2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121973877","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

Mastering Uncertainty in Performance Estimations of Configurable Software Systems 掌握可配置软件系统性能评估中的不确定性

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1007/s10664-022-10250-2

Johannes Dorn, S. Apel, Norbert Siegmund

引用次数: 17

Scalability and Precision Improvement of Neural Program Synthesis 神经程序合成的可扩展性和精度提高

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3418912

Yating Zhang

引用次数: 0