2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST)最新文献_第3页

Organization Committee 组织委员会

2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2019-04-01 DOI: 10.1109/icst.2019.00007

引用次数: 0

BugsJS: a Benchmark of JavaScript Bugs BugsJS: JavaScript bug的基准测试

2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2019-04-01 DOI: 10.1109/ICST.2019.00019

Péter Gyimesi, Béla Vancsics, Andrea Stocco, D. Mazinanian, Árpád Beszédes, R. Ferenc, A. Mesbah

引用次数: 60

AADL-Based Safety Analysis Approaches for Safety-Critical Systems 基于aadl的安全关键系统安全分析方法

2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2019-04-01 DOI: 10.1109/ICST.2019.00058

Xiaomin Wei

引用次数: 0

SmokeOut: An Approach for Testing Clustering Implementations 冒烟:一种测试集群实现的方法

2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2019-04-01 DOI: 10.1109/ICST.2019.00057

Vincenzo Musco, Xin Yin, Iulian Neamtiu

{"title":"SmokeOut: An Approach for Testing Clustering Implementations","authors":"Vincenzo Musco, Xin Yin, Iulian Neamtiu","doi":"10.1109/ICST.2019.00057","DOIUrl":"https://doi.org/10.1109/ICST.2019.00057","url":null,"abstract":"Clustering is a key Machine Learning technique, used in many high-stakes domains from medicine to self-driving cars. Many clustering algorithms have been proposed, and these algorithms have been implemented in many toolkits. Clustering users assume that clustering implementations are correct, reliable, and for a given algorithm, interchangeable. We challenge these assumptions. We introduce SmokeOut, an approach and tool that pits clustering implementations against each other (and against themselves) while controlling for algorithm and dataset, to find datasets where clustering outcomes differ when they shouldn't, and measure this difference. We ran SmokeOut on 7 clustering algorithms (3 deterministic and 4 nondeterministic) implemented in 7 widely-used toolkits, and run in a variety of scenarios on the Penn Machine Learning Benchmark (162 datasets). SmokeOut has revealed that clustering implementations are fragile: on a given input dataset and using a given clustering algorithm, clustering outcomes and accuracy vary widely between (1) successive runs of the same toolkit; (2) different input parameters for that tool; (3) different toolkits.","PeriodicalId":446827,"journal":{"name":"2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122838651","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

On the Evolution of Keyword-Driven Test Suites 关键词驱动测试套件的演变

2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2019-04-01 DOI: 10.1109/ICST.2019.00040

Renaud Rwemalika, Marinos Kintis, Mike Papadakis, Yves Le Traon, Pierre Lorrach

{"title":"On the Evolution of Keyword-Driven Test Suites","authors":"Renaud Rwemalika, Marinos Kintis, Mike Papadakis, Yves Le Traon, Pierre Lorrach","doi":"10.1109/ICST.2019.00040","DOIUrl":"https://doi.org/10.1109/ICST.2019.00040","url":null,"abstract":"Many companies rely on software testing to verify that their software products meet their requirements. However, test quality and, in particular, the quality of end-to-end testing is relatively hard to achieve. The problem becomes challenging when software evolves, as end-to-end test suites need to adapt and conform to the evolved software. Unfortunately, end-to-end tests are particularly fragile as any change in the application interface, e.g., application flow, location or name of graphical user interface elements, necessitates a change in the tests. This paper presents an industrial case study on the evolution of Keyword-Driven test suites, also known as Keyword-Driven Testing (KDT). Our aim is to demonstrate the problem of test maintenance, identify the benefits of Keyword-Driven Testing and overall improve the understanding of test code evolution (at the acceptance testing level). This information will support the development of automatic techniques, such as test refactoring and repair, and will motivate future research. To this end, we identify, collect and analyze test code changes across the evolution of industrial KDT test suites for a period of eight months. We show that the problem of test maintenance is largely due to test fragility (most commonly-performed changes are due to locator and synchronization issues) and test clones (over 30% of keywords are duplicated). We also show that the better test design of KDT test suites has the potential for drastically reducing (approximately 70%) the number of test code changes required to support software evolution. To further validate our results, we interview testers from BGL BNP Paribas and report their perceptions on the advantages and challenges of keyword-driven testing.","PeriodicalId":446827,"journal":{"name":"2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131119185","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

Testing Android Incoming Calls 测试Android呼入

2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2019-04-01 DOI: 10.1109/ICST.2019.00053

A. C. Paiva, Marco A. Gonçalves, André R. Barros

{"title":"Testing Android Incoming Calls","authors":"A. C. Paiva, Marco A. Gonçalves, André R. Barros","doi":"10.1109/ICST.2019.00053","DOIUrl":"https://doi.org/10.1109/ICST.2019.00053","url":null,"abstract":"Mobile applications are increasingly present in our daily lives. Being increasingly dependent on apps, we all want to make sure apps work as expected. One way to increase confidence and quality of software is through testing. However, the existing approaches and tools still do not provide sufficient solutions for testing mobile apps with features different from the ones found in desktop or web applications. In particular, there are guidelines that mobile developers should follow and that may be tested automatically but, as far as we know, there are no tools that are able do it. The iMPAcT tool combines exploration, reverse engineering and testing to check if mobile apps follow best practices to implement specific behavior called UI Patterns. Examples of UI Patterns within this catalog are: orientation, background-foreground, side drawer, tab-scroll, among others. For each of these behaviors (UI Patterns), the iMPAcT tool has a corresponding Test Pattern that checks if the UI Pattern implementation follows the guidelines. This paper presents an extension to iMPAcT tool. It enables to test if Android apps work properly after receiving an incoming call, i.e., if the state of the screen after the call is the same as before getting the call. It formalizes the problem, describes the overall approach, describes the architecture of the tool and reports an experiment performed over 61 public mobile apps.","PeriodicalId":446827,"journal":{"name":"2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114448175","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

Using Data Flow-Based Coverage Criteria for Black-Box Integration Testing of Distributed Software Systems 基于数据流覆盖标准的分布式软件系统黑盒集成测试

2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2019-04-01 DOI: 10.1109/ICST.2019.00051

Dominik Hellhake, Tobias Schmid, S. Wagner

{"title":"Using Data Flow-Based Coverage Criteria for Black-Box Integration Testing of Distributed Software Systems","authors":"Dominik Hellhake, Tobias Schmid, S. Wagner","doi":"10.1109/ICST.2019.00051","DOIUrl":"https://doi.org/10.1109/ICST.2019.00051","url":null,"abstract":"Modern automotive E/E systems are implemented as distributed real-time software systems. The constantly growing complexity of safety-relevant software functions leads to an increased importance of testing during system integration of such systems. Systematic metrics are required to guide the testing process during system integration by providing coverage measures and stopping criteria but few studied approaches exist. For this purpose, we introduce a data-flow based observation scheme which captures the interplay behavior of involved ECUs during test execution and failure occurrences. In addition, we introduce a data flow-based coverage criterion designed for black box integration. By applying the observation scheme to test cases and associated faults found during execution, we first analyze similarities in data flow coverage. By further analyzing the data flow of failures, that slipped through the phase of system integration testing, we evaluate the usefulness of test gaps identified by using the suggested coverage criterion. We found major differences in the usage of data flow between undetected failures and existing test cases. In addition, we found that for the studied system under test the occurrence of failures is not necessarily a direct consequence of the test execution due to functional dependencies and side effects. Overall, these findings highlight the potential and limitations of data flow-based measures to be formalized as coverage or stopping criteria for the integration testing of distributed software systems.","PeriodicalId":446827,"journal":{"name":"2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122044746","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

Testing for Implicit Inconsistencies in Documentation and Implementation 测试文档和实现中的隐性不一致性

2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2019-04-01 DOI: 10.1109/ICST.2019.00059

Devika Sondhi

引用次数: 0

[Copyright notice] (版权)

2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2019-04-01 DOI: 10.1109/icst.2019.00003

引用次数: 0

An Empirical Study on the Use of Defect Prediction for Test Case Prioritization 缺陷预测用于测试用例优先级的实证研究

2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2019-04-01 DOI: 10.1109/ICST.2019.00041

David Paterson, José Campos, Rui Abreu, G. M. Kapfhammer, G. Fraser, Phil McMinn

{"title":"An Empirical Study on the Use of Defect Prediction for Test Case Prioritization","authors":"David Paterson, José Campos, Rui Abreu, G. M. Kapfhammer, G. Fraser, Phil McMinn","doi":"10.1109/ICST.2019.00041","DOIUrl":"https://doi.org/10.1109/ICST.2019.00041","url":null,"abstract":"Test case prioritization has been extensively re-searched as a means for reducing the time taken to discover regressions in software. While many different strategies have been developed and evaluated, prior experiments have shown them to not be effective at prioritizing test suites to find real faults. This paper presents a test case prioritization strategy based on defect prediction, a technique that analyzes code features – such as the number of revisions and authors — to estimate the likelihood that any given Java class will contain a bug. Intuitively, if defect prediction can accurately predict the class that is most likely to be buggy, a tool can prioritize tests to rapidly detect the defects in that class. We investigated how to configure a defect prediction tool, called Schwa, to maximize the likelihood of an accurate prediction, surfacing the link between perfect defect prediction and test case prioritization effectiveness. Using 6 real-world Java programs containing 395 real faults, we conducted an empirical evaluation comparing this paper's strategy, called G-clef, against eight existing test case prioritization strategies. The experiments reveal that using defect prediction to prioritize test cases reduces the number of test cases required to find a fault by on average 9.48% when compared with existing coverage-based strategies, and 10.4% when compared with existing history-based strategies.","PeriodicalId":446827,"journal":{"name":"2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST)","volume":" 28","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132095054","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: 32