2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)最新文献_第7页

Enabling Software Resilience in GPGPU Applications via Partial Thread Protection 通过部分线程保护在GPGPU应用程序中启用软件弹性

2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) Pub Date : 2021-03-04 DOI: 10.1109/ICSE43902.2021.00114

Lishan Yang, Bin Nie, Adwait Jog, E. Smirni

{"title":"Enabling Software Resilience in GPGPU Applications via Partial Thread Protection","authors":"Lishan Yang, Bin Nie, Adwait Jog, E. Smirni","doi":"10.1109/ICSE43902.2021.00114","DOIUrl":"https://doi.org/10.1109/ICSE43902.2021.00114","url":null,"abstract":"Graphics Processing Units (GPUs) are widely used by various applications in a broad variety of fields to accelerate their computation but remain susceptible to transient hardware faults (soft errors) that can easily compromise application output. By taking advantage of a general purpose GPU application hierarchical organization in threads, warps, and cooperative thread arrays, we propose a methodology that identifies the resilience of threads and aims to map threads with the same resilience characteristics to the same warp. This allows to engage partial replication mechanisms for error detection/correction at the warp level. By exploring 12 benchmarks (17 kernels) from 4 benchmark suites, we illustrate that threads can be remapped into reliable or unreliable warps with only 1.63% introduced overhead (on average), and then enable selective protection via replication to those groups of threads that truly need it. Furthermore, we show that thread remapping to different warps does not sacrifice application performance. We show how this remapping facilitates warp replication for error detection and/or correction and achieves average reduction of 20.61% and 27.15% execution cycles, respectively comparing to standard duplication/triplication.","PeriodicalId":305167,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114238445","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

Restoring Execution Environments of Jupyter Notebooks 恢复Jupyter笔记本的执行环境

2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) Pub Date : 2021-03-04 DOI: 10.1109/ICSE43902.2021.00144

Jiawei Wang, Li Li, A. Zeller

引用次数: 26

Technical Leverage in a Software Ecosystem: Development Opportunities and Security Risks 软件生态系统中的技术杠杆:发展机会和安全风险

2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) Pub Date : 2021-03-04 DOI: 10.1109/ICSE43902.2021.00125

F. Massacci, Ivan Pashchenko

{"title":"Technical Leverage in a Software Ecosystem: Development Opportunities and Security Risks","authors":"F. Massacci, Ivan Pashchenko","doi":"10.1109/ICSE43902.2021.00125","DOIUrl":"https://doi.org/10.1109/ICSE43902.2021.00125","url":null,"abstract":"In finance, leverage is the ratio between assets borrowed from others and one's own assets. A matching situation is present in software: by using free open-source software (FOSS) libraries a developer leverages on other people's code to multiply the offered functionalities with a much smaller own codebase. In finance as in software, leverage magnifies profits when returns from borrowing exceed costs of integration, but it may also magnify losses, in particular in the presence of security vulnerabilities. We aim to understand the level of technical leverage in the FOSS ecosystem and whether it can be a potential source of security vulnerabilities. Also, we introduce two metrics change distance and change direction to capture the amount and the evolution of the dependency on third-party libraries. The application of the proposed metrics on 8494 distinct library versions from the FOSS Maven-based Java libraries shows that small and medium libraries (less than 100KLoC) have disproportionately more leverage on FOSS dependencies in comparison to large libraries. We show that leverage pays off as leveraged libraries only add a 4% delay in the time interval between library releases while providing four times more code than their own. However, libraries with such leverage (i.e., 75% of libraries in our sample) also have 1.6 higher odds of being vulnerable in comparison to the libraries with lower leverage. We provide an online demo for computing the proposed metrics for real-world software libraries available under the following URL: https://techleverage.eu/","PeriodicalId":305167,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)","volume":"139 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132592827","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: 10

Self-Checking Deep Neural Networks in Deployment 部署中的自检深度神经网络

2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) Pub Date : 2021-03-03 DOI: 10.1109/ICSE43902.2021.00044

Yan Xiao, Ivan Beschastnikh, David S. Rosenblum, Changsheng Sun, Sebastian G. Elbaum, Yun Lin, J. Dong

{"title":"Self-Checking Deep Neural Networks in Deployment","authors":"Yan Xiao, Ivan Beschastnikh, David S. Rosenblum, Changsheng Sun, Sebastian G. Elbaum, Yun Lin, J. Dong","doi":"10.1109/ICSE43902.2021.00044","DOIUrl":"https://doi.org/10.1109/ICSE43902.2021.00044","url":null,"abstract":"The widespread adoption of Deep Neural Networks (DNNs) in important domains raises questions about the trustworthiness of DNN outputs. Even a highly accurate DNN will make mistakes some of the time, and in settings like self-driving vehicles these mistakes must be quickly detected and properly dealt with in deployment. Just as our community has developed effective techniques and mechanisms to monitor and check programmed components, we believe it is now necessary to do the same for DNNs. In this paper we present DNN self-checking as a process by which internal DNN layer features are used to check DNN predictions. We detail SelfChecker, a self-checking system that monitors DNN outputs and triggers an alarm if the internal layer features of the model are inconsistent with the final prediction. SelfChecker also provides advice in the form of an alternative prediction. We evaluated SelfChecker on four popular image datasets and three DNN models and found that SelfChecker triggers correct alarms on 60.56% of wrong DNN predictions, and false alarms on 2.04% of correct DNN predictions. This is a substantial improvement over prior work (SelfOracle, Dissector, and ConfidNet). In experiments with self-driving car scenarios, SelfChecker triggers more correct alarms than SelfOracle for two DNN models (DAVE-2 and Chauffeur) with comparable false alarms. Our implementation is available as open source.","PeriodicalId":305167,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134395353","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: 25

An Empirical Analysis of UI-Based Flaky Tests 基于ui的片状检验的实证分析

2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) Pub Date : 2021-03-03 DOI: 10.1109/ICSE43902.2021.00141

Alan Romano, Zihe Song, Sampath Grandhi, Wei Yang, Weihang Wang

引用次数: 24

How to Identify Boundary Conditions with Contrasty Metric? 如何用对比度量识别边界条件?

2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) Pub Date : 2021-03-03 DOI: 10.1109/ICSE43902.2021.00132

Weilin Luo, Hai Wan, Xiaotong Song, Binhao Yang, Hongzhen Zhong, Yin Chen

{"title":"How to Identify Boundary Conditions with Contrasty Metric?","authors":"Weilin Luo, Hai Wan, Xiaotong Song, Binhao Yang, Hongzhen Zhong, Yin Chen","doi":"10.1109/ICSE43902.2021.00132","DOIUrl":"https://doi.org/10.1109/ICSE43902.2021.00132","url":null,"abstract":"The boundary conditions (BCs) have shown great potential in requirements engineering because a BC captures the particular combination of circumstances, i.e., divergence, in which the goals of the requirement cannot be satisfied as a whole. Existing researches have attempted to automatically identify lots of BCs. Unfortunately, a large number of identified BCs make assessing and resolving divergences expensive. Existing methods adopt a coarse-grained metric, generality, to filter out less general BCs. However, the results still retain a large number of redundant BCs since a general BC potentially captures redundant circumstances that do not lead to a divergence. Furthermore, the likelihood of BC can be misled by redundant BCs resulting in costly repeatedly assessing and resolving divergences. In this paper, we present a fine-grained metric to filter out the redundant BCs. We first introduce the concept of contrasty of BC. Intuitively, if two BCs are contrastive, they capture different divergences. We argue that a set of contrastive BCs should be recommended to engineers, rather than a set of general BCs that potentially only indicates the same divergence. Then we design a post-processing framework (PPFc) to produce a set of contrastive BCs after identifying BCs. Experimental results show that the contrasty metric dramatically reduces the number of BCs recommended to engineers. Results also demonstrate that lots of BCs identified by the state-of-the-art method are redundant in most cases. Besides, to improve efficiency, we propose a joint framework (JFc) to interleave assessing based on the contrasty metric with identifying BCs. The primary intuition behind JFc is that it considers the search bias toward contrastive BCs during identifying BCs, thereby pruning the BCs capturing the same divergence. Experiments confirm the improvements of JFc in identifying contrastive BCs.","PeriodicalId":305167,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128985193","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

Can Program Synthesis be Used to Learn Merge Conflict Resolutions? An Empirical Analysis 程序合成可以用来学习合并冲突的解决方法吗?实证分析

2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) Pub Date : 2021-03-02 DOI: 10.1109/ICSE43902.2021.00077

Rangeet Pan, Vu Le, Nachiappan Nagappan, Sumit Gulwani, Shuvendu K. Lahiri, Mike Kaufman

{"title":"Can Program Synthesis be Used to Learn Merge Conflict Resolutions? An Empirical Analysis","authors":"Rangeet Pan, Vu Le, Nachiappan Nagappan, Sumit Gulwani, Shuvendu K. Lahiri, Mike Kaufman","doi":"10.1109/ICSE43902.2021.00077","DOIUrl":"https://doi.org/10.1109/ICSE43902.2021.00077","url":null,"abstract":"Forking structure is widespread in the open-source repositories and that causes a significant number of merge conflicts. In this paper, we study the problem of textual merge conflicts from the perspective of Microsoft Edge, a large, highly collaborative fork off the main Chromium branch with significant merge conflicts. Broadly, this study is divided into two sections. First, we empirically evaluate textual merge conflicts in Microsoft Edge and classify them based on the type of files, location of conflicts in a file, and the size of conflicts. We found that ~28% of the merge conflicts are 1-2 line changes, and many resolutions have frequent patterns. Second, driven by these findings, we explore Program Synthesis (for the first time) to learn patterns and resolve structural merge conflicts. We propose a novel domain-specific language (DSL) that captures many of the repetitive merge conflict resolution patterns and learn resolution strategies as programs in this DSL from example resolutions. We found that the learned strategies can resolve 11.4% of the conflicts (~41% of 1-2 line changes) that arise in the C++ files with 93.2% accuracy.","PeriodicalId":305167,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132040948","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: 21

CHAMP: Characterizing Undesired App Behaviors from User Comments Based on Market Policies CHAMP:基于市场政策，从用户评论中描述不受欢迎的应用行为

2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) Pub Date : 2021-03-01 DOI: 10.1109/ICSE43902.2021.00089

Yangyu Hu, Haoyu Wang, Tiantong Ji, Xusheng Xiao, Xiapu Luo, Peng Gao, Yao Guo

{"title":"CHAMP: Characterizing Undesired App Behaviors from User Comments Based on Market Policies","authors":"Yangyu Hu, Haoyu Wang, Tiantong Ji, Xusheng Xiao, Xiapu Luo, Peng Gao, Yao Guo","doi":"10.1109/ICSE43902.2021.00089","DOIUrl":"https://doi.org/10.1109/ICSE43902.2021.00089","url":null,"abstract":"Millions of mobile apps have been available through various app markets. Although most app markets have enforced a number of automated or even manual mechanisms to vet each app before it is released to the market, thousands of low-quality apps still exist in different markets, some of which violate the explicitly specified market policies. In order to identify these violations accurately and timely, we resort to user comments, which can form an immediate feedback for app market maintainers, to identify undesired behaviors that violate market policies, including security-related user concerns. Specifically, we present the first large-scale study to detect and characterize the correlations between user comments and market policies. First, we propose CHAMP, an approach that adopts text mining and natural language processing (NLP) techniques to extract semantic rules through a semi-automated process, and classifies comments into 26 pre-defined types of undesired behaviors that violate market policies. Our evaluation on real-world user comments shows that it achieves both high precision and recall (>0.9) in classifying comments for undesired behaviors. Then, we curate a large-scale comment dataset (over 3 million user comments) from apps in Google Play and 8 popular alternative Android app markets, and apply CHAMP to understand the characteristics of undesired behavior comments in the wild. The results confirm our speculation that user comments can be used to pinpoint suspicious apps that violate policies declared by app markets. The study also reveals that policy violations are widespread in many app markets despite their extensive vetting efforts. CHAMP can be a whistle blower that assigns policy-violation scores and identifies most informative comments for apps.","PeriodicalId":305167,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122540858","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

Seamless Variability Management with the Virtual Platform 虚拟平台的无缝可变性管理

2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) Pub Date : 2021-02-28 DOI: 10.1109/ICSE43902.2021.00147

Wardah Mahmood, D. Strüber, T. Berger, R. Lämmel, M. Mukelabai

{"title":"Seamless Variability Management with the Virtual Platform","authors":"Wardah Mahmood, D. Strüber, T. Berger, R. Lämmel, M. Mukelabai","doi":"10.1109/ICSE43902.2021.00147","DOIUrl":"https://doi.org/10.1109/ICSE43902.2021.00147","url":null,"abstract":"Customization is a general trend in software engineering, demanding systems that support variable stakeholder requirements. Two opposing strategies are commonly used to create variants: software clone&own and software configuration with an integrated platform. Organizations often start with the former, which is cheap, agile, and supports quick innovation, but does not scale. The latter scales by establishing an integrated platform that shares software assets between variants, but requires high up-front investments or risky migration processes. So, could we have a method that allows an easy transition or even combine the benefits of both strategies? We propose a method and tool that supports a truly incremental development of variant rich systems, exploiting a spectrum between both opposing strategies. We design, formalize, and prototype the variability management framework virtual platform. It bridges clone&own and platform-oriented development. Relying on programming language independent conceptual structures representing software assets, it offers operators for engineering and evolving a system, comprising: traditional, asset-oriented operators and novel, feature-oriented operators for incrementally adopting concepts of an integrated platform. The operators record meta-data that is exploited by other operators to support the transition. Among others, they eliminate expensive feature-location effort or the need to trace clones. Our evaluation simulates the evolution of a real-world, clone-based system, measuring its costs and benefits.","PeriodicalId":305167,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128033940","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

PyCG: Practical Call Graph Generation in Python Python中的实用调用图生成

2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE) Pub Date : 2021-02-28 DOI: 10.1109/ICSE43902.2021.00146

Vitalis Salis, Thodoris Sotiropoulos, Panos Louridas, D. Spinellis, Dimitris Mitropoulos

{"title":"PyCG: Practical Call Graph Generation in Python","authors":"Vitalis Salis, Thodoris Sotiropoulos, Panos Louridas, D. Spinellis, Dimitris Mitropoulos","doi":"10.1109/ICSE43902.2021.00146","DOIUrl":"https://doi.org/10.1109/ICSE43902.2021.00146","url":null,"abstract":"Call graphs play an important role in different contexts, such as profiling and vulnerability propagation analysis. Generating call graphs in an efficient manner can be a challenging task when it comes to high-level languages that are modular and incorporate dynamic features and higher-order functions. Despite the language's popularity, there have been very few tools aiming to generate call graphs for Python programs. Worse, these tools suffer from several effectiveness issues that limit their practicality in realistic programs. We propose a pragmatic, static approach for call graph generation in Python. We compute all assignment relations between program identifiers of functions, variables, classes, and modules through an inter-procedural analysis. Based on these assignment relations, we produce the resulting call graph by resolving all calls to potentially invoked functions. Notably, the underlying analysis is designed to be efficient and scalable, handling several Python features, such as modules, generators, function closures, and multiple inheritance. We have evaluated our prototype implementation, which we call PyCG, using two benchmarks: a micro-benchmark suite containing small Python programs and a set of macro-benchmarks with several popular real-world Python packages. Our results indicate that PyCG can efficiently handle thousands of lines of code in less than a second (0.38 seconds for 1k LoC on average). Further, it outperforms the state-of-the-art for Python in both precision and recall: PyCG achieves high rates of precision ~99.2% and adequate recall ~69.9%. Finally, we demonstrate how PyCG can aid dependency impact analysis by showcasing a potential enhancement to GitHub's \"security advisory\" notification service using a real-world example.","PeriodicalId":305167,"journal":{"name":"2021 IEEE/ACM 43rd International Conference on Software Engineering (ICSE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115430028","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: 44