2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)最新文献_第2页

How C++ Developers Use Immutability Declarations: An Empirical Study c++开发者如何使用不变性声明:一个实证研究

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) Pub Date : 2019-05-25 DOI: 10.1109/ICSE.2019.00050

Jon Eyolfson, Patrick Lam

{"title":"How C++ Developers Use Immutability Declarations: An Empirical Study","authors":"Jon Eyolfson, Patrick Lam","doi":"10.1109/ICSE.2019.00050","DOIUrl":"https://doi.org/10.1109/ICSE.2019.00050","url":null,"abstract":"Best practices for developers, as encoded in recent programming language designs, recommend the use of immutability whenever practical. However, there is a lack of empirical evidence about the uptake of this advice. Our goal is to understand the usage of immutability by C++ developers in practice. This work investigates how C++ developers use immutability by analyzing their use of the C++ immutability qualifier, const, and by analyzing the code itself. We answer the following broad questions about const usage: 1) do developers actually write non-trivial (more than 3 methods) immutable classes and immutable methods? 2) do developers label their immutable classes and methods? We analyzed 7 medium-to-large open source projects and collected two sources of empirical data: 1) const annotations by developers, indicating an intent to write immutable code; and 2) the results of a simple static analysis which identified easily const-able methods---those that clearly did not mutate state. We estimate that 5% of non-trivial classes (median) are immutable. We found the vast majority of classes do carry immutability labels on methods: surprisingly, developers const-annotate 46% of methods, and we estimate that at least 51% of methods could be const-annotated. Furthermore, developers missed immutability labels on at least 6% of unannotated methods. We provide an in-depth discussion on how developers use const and the results of our analyses.","PeriodicalId":6736,"journal":{"name":"2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)","volume":"34 1","pages":"362-372"},"PeriodicalIF":0.0,"publicationDate":"2019-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77090907","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: 2

Rotten Green Tests 腐烂的绿色测试

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) Pub Date : 2019-05-25 DOI: 10.1109/ICSE.2019.00062

J. Delplanque, Stéphane Ducasse, G. Polito, A. Black, Anne Etien

{"title":"Rotten Green Tests","authors":"J. Delplanque, Stéphane Ducasse, G. Polito, A. Black, Anne Etien","doi":"10.1109/ICSE.2019.00062","DOIUrl":"https://doi.org/10.1109/ICSE.2019.00062","url":null,"abstract":"Unit tests are a tenant of agile programming methodologies, and are widely used to improve code quality and prevent code regression. A green (passing) test is usually taken as a robust sign that the code under test is valid. However, some green tests contain assertions that are never executed. We call such tests Rotten Green Tests. Rotten Green Tests represent a case worse than a broken test: they report that the code under test is valid, but in fact do not test that validity. We describe an approach to identify rotten green tests by combining simple static and dynamic call-site analyses. Our approach takes into account test helper methods, inherited helpers, and trait compositions, and has been implemented in a tool called DrTest. DrTest reports no false negatives, yet it still reports some false positives due to conditional use or multiple test contexts. Using DrTest we conducted an empirical evaluation of 19,905 real test cases in mature projects of the Pharo ecosystem. The results of the evaluation show that the tool is effective; it detected 294 tests as rotten—green tests that contain assertions that are not executed. Some rotten tests have been “sleeping” in Pharo for at least 5 years.","PeriodicalId":6736,"journal":{"name":"2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)","volume":"52 1","pages":"500-511"},"PeriodicalIF":0.0,"publicationDate":"2019-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82686956","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: 14

FastLane: Test Minimization for Rapidly Deployed Large-Scale Online Services 快速通道:快速部署大规模在线服务的测试最小化

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) Pub Date : 2019-05-25 DOI: 10.1109/ICSE.2019.00054

Adithya Abraham Philip, Ranjita Bhagwan, Rahul Kumar, C. Maddila, Nachiappan Nagappan

引用次数: 18

Tool Choice Matters: JavaScript Quality Assurance Tools and Usage Outcomes in GitHub Projects 工具选择很重要:JavaScript质量保证工具和GitHub项目中的使用结果

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) Pub Date : 2019-05-25 DOI: 10.1109/ICSE.2019.00060

David Kavaler, Asher Trockman, Bogdan Vasilescu, V. Filkov

{"title":"Tool Choice Matters: JavaScript Quality Assurance Tools and Usage Outcomes in GitHub Projects","authors":"David Kavaler, Asher Trockman, Bogdan Vasilescu, V. Filkov","doi":"10.1109/ICSE.2019.00060","DOIUrl":"https://doi.org/10.1109/ICSE.2019.00060","url":null,"abstract":"Quality assurance automation is essential in modern software development. In practice, this automation is supported by a multitude of tools that fit different needs and require developers to make decisions about which tool to choose in a given context. Data and analytics of the pros and cons can inform these decisions. Yet, in most cases, there is a dearth of empirical evidence on the effectiveness of existing practices and tool choices. We propose a general methodology to model the time- dependent effect of automation tool choice on four outcomes of interest: prevalence of issues, code churn, number of pull requests, and number of contributors, all with a multitude of controls. On a large data set of npm JavaScript projects, we extract the adoption events for popular tools in three task classes: linters, dependency managers, and coverage reporters. Using mixed methods approaches, we study the reasons for the adoptions and compare the adoption effects within each class, and sequential tool adoptions across classes. We find that some tools within each group are associated with more beneficial outcomes than others, providing an empirical perspective for the benefits of each. We also find that the order in which some tools are implemented is associated with varying outcomes.","PeriodicalId":6736,"journal":{"name":"2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)","volume":"3 1","pages":"476-487"},"PeriodicalIF":0.0,"publicationDate":"2019-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87091966","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: 27

SLF: Fuzzing without Valid Seed Inputs 没有有效种子输入的模糊测试

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) Pub Date : 2019-05-25 DOI: 10.1109/ICSE.2019.00080

Wei You, Xuwei Liu, Shiqing Ma, D. Perry, X. Zhang, Bin Liang

{"title":"SLF: Fuzzing without Valid Seed Inputs","authors":"Wei You, Xuwei Liu, Shiqing Ma, D. Perry, X. Zhang, Bin Liang","doi":"10.1109/ICSE.2019.00080","DOIUrl":"https://doi.org/10.1109/ICSE.2019.00080","url":null,"abstract":"Fuzzing is an important technique to detect software bugs and vulnerabilities. It works by mutating a small set of seed inputs to generate a large number of new inputs. Fuzzers' performance often substantially degrades when valid seed inputs are not available. Although existing techniques such as symbolic execution can generate seed inputs from scratch, they have various limitations hindering their applications in real-world complex software. In this paper, we propose a novel fuzzing technique that features the capability of generating valid seed inputs. It piggy-backs on AFL to identify input validity checks and the input fields that have impact on such checks. It further classifies these checks according to their relations to the input. Such classes include arithmetic relation, object offset, data structure length and so on. A multi-goal search algorithm is developed to apply class-specific mutations in order to satisfy inter-dependent checks all together. We evaluate our technique on 20 popular benchmark programs collected from other fuzzing projects and the Google fuzzer test suite, and compare it with existing fuzzers AFL and AFLFast, symbolic execution engines KLEE and S2E, and a hybrid tool Driller that combines fuzzing with symbolic execution. The results show that our technique is highly effective and efficient, out-performing the other tools.","PeriodicalId":6736,"journal":{"name":"2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)","volume":"25 1","pages":"712-723"},"PeriodicalIF":0.0,"publicationDate":"2019-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88886420","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: 50

View-Centric Performance Optimization for Database-Backed Web Applications 数据库支持的Web应用程序以视图为中心的性能优化

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) Pub Date : 2019-05-25 DOI: 10.1109/ICSE.2019.00104

Junwen Yang, Cong Yan, Chengcheng Wan, Shan Lu, Alvin Cheung

引用次数: 18

Grey-Box Concolic Testing on Binary Code 二进制码的灰盒聚类测试

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) Pub Date : 2019-05-25 DOI: 10.1109/ICSE.2019.00082

Jaeseung Choi, J. Jang, Choongwoo Han, S. Cha

引用次数: 59

Training Binary Classifiers as Data Structure Invariants 训练二元分类器作为数据结构不变量

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) Pub Date : 2019-05-25 DOI: 10.1109/ICSE.2019.00084

F. Molina, Renzo Degiovanni, Pablo Ponzio, Germán Regis, Nazareno Aguirre, M. Frias

{"title":"Training Binary Classifiers as Data Structure Invariants","authors":"F. Molina, Renzo Degiovanni, Pablo Ponzio, Germán Regis, Nazareno Aguirre, M. Frias","doi":"10.1109/ICSE.2019.00084","DOIUrl":"https://doi.org/10.1109/ICSE.2019.00084","url":null,"abstract":"We present a technique to distinguish valid from invalid data structure objects. The technique is based on building an artificial neural network, more precisely a binary classifier, and training it to identify valid and invalid instances of a data structure. The obtained classifier can then be used in place of the data structure's invariant, in order to attempt to identify (in)correct behaviors in programs manipulating the structure. In order to produce the valid objects to train the network, an assumed-correct set of object building routines is randomly executed. Invalid instances are produced by generating values for object fields that \"break\" the collected valid values, i.e., that assign values to object fields that have not been observed as feasible in the assumed-correct executions that led to the collected valid instances. We experimentally assess this approach, over a benchmark of data structures. We show that this learning technique produces classifiers that achieve significantly better accuracy in classifying valid/invalid objects compared to a technique for dynamic invariant detection, and leads to improved bug finding.","PeriodicalId":6736,"journal":{"name":"2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)","volume":"45 1","pages":"759-770"},"PeriodicalIF":0.0,"publicationDate":"2019-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74918467","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: 13

PIVOT: Learning API-Device Correlations to Facilitate Android Compatibility Issue Detection PIVOT:学习api -设备相关性以促进Android兼容性问题检测

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) Pub Date : 2019-05-25 DOI: 10.1109/ICSE.2019.00094

Lili Wei, Yepang Liu, S. Cheung

{"title":"PIVOT: Learning API-Device Correlations to Facilitate Android Compatibility Issue Detection","authors":"Lili Wei, Yepang Liu, S. Cheung","doi":"10.1109/ICSE.2019.00094","DOIUrl":"https://doi.org/10.1109/ICSE.2019.00094","url":null,"abstract":"The heavily fragmented Android ecosystem has induced various compatibility issues in Android apps. The search space for such fragmentation-induced compatibility issues (FIC issues) is huge, comprising three dimensions: device models, Android OS versions, and Android APIs. FIC issues, especially those arising from device models, evolve quickly with the frequent release of new device models to the market. As a result, an automated technique is desired to maintain timely knowledge of such FIC issues, which are mostly undocumented. In this paper, we propose such a technique, PIVOT, that automatically learns API-device correlations of FIC issues from existing Android apps. PIVOT extracts and prioritizes API-device correlations from a given corpus of Android apps. We evaluated PIVOT with popular Android apps on Google Play. Evaluation results show that PIVOT can effectively prioritize valid API-device correlations for app corpora collected at different time. Leveraging the knowledge in the learned API-device correlations, we further conducted a case study and successfully uncovered ten previously-undetected FIC issues in open-source Android apps.","PeriodicalId":6736,"journal":{"name":"2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)","volume":"22 1","pages":"878-888"},"PeriodicalIF":0.0,"publicationDate":"2019-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87621867","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: 35

Easy Modelling and Verification of Unpredictable and Preemptive Interrupt-Driven Systems 不可预测和抢占式中断驱动系统的简单建模与验证

2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE) Pub Date : 2019-05-25 DOI: 10.1109/ICSE.2019.00037

Minxue Pan, Shouyu Chen, Yu Pei, Tian Zhang, Xuandong Li

{"title":"Easy Modelling and Verification of Unpredictable and Preemptive Interrupt-Driven Systems","authors":"Minxue Pan, Shouyu Chen, Yu Pei, Tian Zhang, Xuandong Li","doi":"10.1109/ICSE.2019.00037","DOIUrl":"https://doi.org/10.1109/ICSE.2019.00037","url":null,"abstract":"The widespread real-time and embedded systems are mostly interrupt-driven because their heavy interaction with the environment is often initiated by interrupts. With the interrupt arrival being unpredictable and the interrupt handling being preemptive, a large number of possible system behaviours are generated, which makes the correctness assurance of such systems difficult and costly. Model checking is considered to be one of the effective methods for exhausting behavioural state space for correctness. However, existing modelling approaches for interrupt-driven systems are based on either calculus or automata theory, and have a steep learning curve. To address this problem, we propose a new modelling language called interrupt sequence diagram (ISD). By extending the popular UML sequence diagram notations, the ISD supports the modelling of interrupts' essential features visually and concisely. We also propose an automata-based semantics for ISD, based on which ISD can be transformed to a subset of hybrid automata so as to leverage the abundant off-the-shelf checkers. Experiments on examples from both real-world and existing literature were conducted, and the results demonstrate our approach's usability and effectiveness.","PeriodicalId":6736,"journal":{"name":"2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)","volume":"22 9","pages":"212-222"},"PeriodicalIF":0.0,"publicationDate":"2019-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91433790","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