2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)最新文献_第2页

Dynamic Algorithm Selection for SMT SMT的动态算法选择

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3418922

Nikhil Pimpalkhare

引用次数: 0

Synthesis-Based Resolution of Feature Interactions in Cyber-Physical Systems 信息物理系统中基于综合的特征交互解析

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3416630

B. Gafford, Tobias Dürschmid, Gabriel A. Moreno, Eunsuk Kang

{"title":"Synthesis-Based Resolution of Feature Interactions in Cyber-Physical Systems","authors":"B. Gafford, Tobias Dürschmid, Gabriel A. Moreno, Eunsuk Kang","doi":"10.1145/3324884.3416630","DOIUrl":"https://doi.org/10.1145/3324884.3416630","url":null,"abstract":"The feature interaction problem arises when two or more independent features interact with each other in an undesirable manner. Feature interactions remain a challenging and important problem in emerging domains of cyber-physical systems (CPS), such as intelligent vehicles, unmanned aerial vehicles (UAVs) and the Internet of Things (IoT), where the outcome of an unexpected interaction may result in a safety failure. Existing approaches to resolving feature interactions rely on priority lists or fixed strategies, but may not be effective in scenarios where none of the competing feature actions are satisfactory with respect to system requirements. This paper proposes a novel synthesis-based approach to resolution, where a conflict among features is resolved by synthesizing an action that best satisfies the specification of desirable system behaviors in the given environmental context. Unlike existing resolution methods, our approach is capable of producing a desirable system outcome even when none of the conflicting actions are satisfactory. The effectiveness of the proposed approach is demonstrated using a case study involving interactions among safety-critical features in an autonomous drone.","PeriodicalId":106337,"journal":{"name":"2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"15 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":"121662576","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

Enhanced Compiler Bug Isolation via Memoized Search 通过记忆搜索增强编译器错误隔离

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3416570

Junjie Chen, Haoyang Ma, Lingming Zhang

{"title":"Enhanced Compiler Bug Isolation via Memoized Search","authors":"Junjie Chen, Haoyang Ma, Lingming Zhang","doi":"10.1145/3324884.3416570","DOIUrl":"https://doi.org/10.1145/3324884.3416570","url":null,"abstract":"Compiler bugs can be disastrous since they could affect all the software systems built on the buggy compilers. Meanwhile, diagnosing compiler bugs is extremely challenging since usually limited debugging information is available and a large number of compiler files can be suspicious. More specifically, when compiling a given bug-triggering test program, hundreds of compiler files are usually involved, and can all be treated as suspicious buggy files. To facilitate compiler debugging, in this paper we propose the first reinforcement compiler bug isolation approach via structural mutation, called RecBi. For a given bug-triggering test program, RecBi first augments traditional local mutation operators with structural ones to transform it into a set of passing test programs. Since not all the passing test programs can help isolate compiler bugs effectively, RecBi further leverages reinforcement learning to intelligently guide the process of passing test program generation. Then, RecBi ranks all the suspicious files by analyzing the compiler execution traces of the generated passing test programs and the given failing test program following the practice of compiler bug isolation. The experimental results on 120 real bugs from two most popular C open-source compilers, i.e., GCC and LLVM, show that RecBi is able to isolate about 23%/58%/78% bugs within Top-l/Top-5/Top-10 compiler files, and significantly outperforms the state-of-the-art compiler bug isolation approach by improving 92.86%/55.56%/25.68% isolation effectiveness in terms of Top-l/Top-5/Top-10 results.","PeriodicalId":106337,"journal":{"name":"2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"48 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":"123875262","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

CP-Detector: Using Configuration-related Performance Properties to Expose Performance Bugs cp检测器:使用与配置相关的性能属性来暴露性能缺陷

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3416531

Haochen He, Zhouyang Jia, Shanshan Li, Erci Xu, Tingting Yu, Yue Yu, Ji Wang, Xiangke Liao

{"title":"CP-Detector: Using Configuration-related Performance Properties to Expose Performance Bugs","authors":"Haochen He, Zhouyang Jia, Shanshan Li, Erci Xu, Tingting Yu, Yue Yu, Ji Wang, Xiangke Liao","doi":"10.1145/3324884.3416531","DOIUrl":"https://doi.org/10.1145/3324884.3416531","url":null,"abstract":"Performance bugs are often hard to detect due to their non fail-stop symptoms. Existing debugging techniques can only detect performance bugs with known patterns (e.g., inefficient loops). The key reason behind this incapability is the lack of a general test oracle. Here, we argue that the performance (e.g., throughput, latency, execution time) expectation of configuration can serve as a strong oracle candidate for performance bug detection. First, prior work shows that most performance bugs are related to configurations. Second, the configuration change reflects common expectation on performance changes. If the actual performance is contrary to the expectation, the related code snippet is likely to be problematic. In this paper, we first conducted a comprehensive study on 173 real-world configuration-related performance bugs (CPBugs) from 12 representative software systems. We then derived seven configuration-related performance properties, which can serve as the test oracle in performance testing. Guided by the study, we designed and evaluated an automated performance testing framework, CP-DETECTOR, for detecting real-world configuration-related performance bugs. CP-DETECTOR was evaluated on 12 open-source projects. The results showed that it detected 43 out of 61 existing bugs and reported 13 new bugs.","PeriodicalId":106337,"journal":{"name":"2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"10 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":"125096890","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: 12

Towards Building Robust DNN Applications: An Industrial Case Study of Evolutionary Data Augmentation 构建稳健的深度神经网络应用:进化数据增强的工业案例研究

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3421841

Haruki Yokoyama, Satoshi Onoue, S. Kikuchi

{"title":"Towards Building Robust DNN Applications: An Industrial Case Study of Evolutionary Data Augmentation","authors":"Haruki Yokoyama, Satoshi Onoue, S. Kikuchi","doi":"10.1145/3324884.3421841","DOIUrl":"https://doi.org/10.1145/3324884.3421841","url":null,"abstract":"Data augmentation techniques that increase the amount of training data by adding realistic transformations are used in machine learning to improve the level of accuracy. Recent studies have demonstrated that data augmentation techniques improve the robustness of image classification models with open datasets; however, it has yet to be investigated whether these techniques are effective for industrial datasets. In this study, we investigate the feasibility of data augmentation techniques for industrial use. We evaluate data augmentation techniques in image classification and object detection tasks using an industrial in-house graphical user interface dataset. As the results indicate, the genetic algorithm-based data augmentation technique outperforms two random-based methods in terms of the robustness of the image classification model. In addition, through this evaluation and interviews with the developers, we learned following two lessons: data augmentation techniques should (1) maintain the training speed to avoid slowing the development and (2) include extensibility for a variety of tasks.","PeriodicalId":106337,"journal":{"name":"2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"1 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":"130191072","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

UI Obfuscation and Its Effects on Automated UI Analysis for Android Apps UI混淆及其对Android应用程序自动UI分析的影响

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3416642

Hao Zhou, Ting Chen, Haoyu Wang, Le Yu, Xiapu Luo, Ting Wang, Wei Zhang

引用次数: 7

Plug the Database & Play With Automatic Testing: Improving System Testing by Exploiting Persistent Data 插入数据库并使用自动测试:利用持久数据改进系统测试

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3416561

Diego Clerissi, G. Denaro, M. Mobilio, L. Mariani

{"title":"Plug the Database & Play With Automatic Testing: Improving System Testing by Exploiting Persistent Data","authors":"Diego Clerissi, G. Denaro, M. Mobilio, L. Mariani","doi":"10.1145/3324884.3416561","DOIUrl":"https://doi.org/10.1145/3324884.3416561","url":null,"abstract":"A key challenge in automatic Web testing is the generation of syntactically and semantically valid input values that can exercise the many functionalities that impose constraints on the validity of the inputs. Existing test case generation techniques either rely on manually curated catalogs of values, or extract values from external data sources, such as the Web or publicly available knowledge bases. Unfortunately, relying on manual effort is generally too expensive for most practical applications, while domain-specific and application-specific data can be hardly found either on the Web or in general purpose knowledge bases.This paper proposes DBINPuTs, a novel approach that reuses the data from the database of the target Web application, to automatically identify domain-specific and application-specific inputs, and effectively fulfill the validity constraints present in the tested Web pages. DBINPUTS can properly cope with system testing and maintenance testing efforts, since databases are naturally and inexpensively available in those phases. To extract valid inputs from the application databases, DBINPUTS exploits the syntactic and semantic similarity between the identifiers of the input fields and the ones in the tables of the database, automatically resolving the mismatch between the user interface and the schema of the database. Our experiments provide initial evidence that DBINPUTS can outperform both random input selection and Link, a competing approach for searching inputs from knowledge bases.","PeriodicalId":106337,"journal":{"name":"2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"44 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":"132617550","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

Automatic Generation of IFTTT Mashup Infrastructures IFTTT Mashup基础设施的自动生成

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3421837

Lei Liu, M. Bahrami, Wei-Peng Chen

{"title":"Automatic Generation of IFTTT Mashup Infrastructures","authors":"Lei Liu, M. Bahrami, Wei-Peng Chen","doi":"10.1145/3324884.3421837","DOIUrl":"https://doi.org/10.1145/3324884.3421837","url":null,"abstract":"In recent years, IF-This-Then-That (IFTTT) services are becoming more and more popular. Many platforms such as Zapier, IFTTT.com, and Workato provide such services, which allow users to create workflows with “triggers” and “actions” by using Web Application Programming Interfaces (APIs). However, the number of IFTTT recipes in the above platforms increases much slower than the growth of Web APIs. This is because human efforts are still largely required to build and deploy IFTTT recipes in the above platforms. To address this problem, in this paper, we present an automation tool to automatically generate the IFTTT mashup infrastructure. The proposed tool provides 5 REST APIs, which can automatically generate triggers, rules, and actions in AWS, and create a workflow XML to describe an IFTTT mashup by connecting the triggers, rules, and actions. This workflow XML is automatically sent to Fujitsu RunMyProcess (RMP) to set up and execute IFTTT mashup. The proposed tool, together with its associated method and procedure, enables an end-to-end solution for automatically creating, deploying, and executing IFTTT mashups in a few seconds, which can greatly reduce the development cycle and cost for new IFTTT mashups.","PeriodicalId":106337,"journal":{"name":"2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"25 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":"133707602","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

The Impact of Generic Data Structures: Decoding the Role of Lists in the Linux Kernel 通用数据结构的影响:解析列表在Linux内核中的作用

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3416635

Nic Volanschi, J. Lawall

引用次数: 0

Multiple-Boundary Clustering and Prioritization to Promote Neural Network Retraining 多边界聚类和优先排序促进神经网络再训练

2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE) Pub Date : 2020-09-01 DOI: 10.1145/3324884.3416621

Weijun Shen, Yanhui Li, Lin Chen, Yuanlei Han, Yuming Zhou, Baowen Xu

{"title":"Multiple-Boundary Clustering and Prioritization to Promote Neural Network Retraining","authors":"Weijun Shen, Yanhui Li, Lin Chen, Yuanlei Han, Yuming Zhou, Baowen Xu","doi":"10.1145/3324884.3416621","DOIUrl":"https://doi.org/10.1145/3324884.3416621","url":null,"abstract":"With the increasing application of deep learning (DL) models in many safety-critical scenarios, effective and efficient DL testing techniques are much in demand to improve the quality of DL models. One of the major challenges is the data gap between the training data to construct the models and the testing data to evaluate them. To bridge the gap, testers aim to collect an effective subset of inputs from the testing contexts, with limited labeling effort, for retraining DL models.To assist the subset selection, we propose Multiple-Boundary Clustering and Prioritization (MCP), a technique to cluster test samples into the boundary areas of multiple boundaries for DL models and specify the priority to select samples evenly from all boundary areas, to make sure enough useful samples for each boundary reconstruction. To evaluate MCP, we conduct an extensive empirical study with three popular DL models and 33 simulated testing contexts. The experiment results show that, compared with state-of-the-art baseline methods, on effectiveness, our approach MCP has a significantly better performance by evaluating the improved quality of retrained DL models; on efficiency, MCP also has the advantages in time costs.","PeriodicalId":106337,"journal":{"name":"2020 35th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"25 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":"117156871","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: 33