2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST)最新文献_第2页

Testability Transformations For Existing APIs 现有api的可测试性转换

2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2020-10-01 DOI: 10.1109/ICST46399.2020.00025

Andrea Arcuri, Juan P. Galeotti

引用次数: 13

SPECMATE: Automated Creation of Test Cases from Acceptance Criteria SPECMATE:根据验收标准自动创建测试用例

2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2020-10-01 DOI: 10.1109/icst46399.2020.00040

Jannik Fischbach, Andreas Vogelsang, Dominik Spies, A. Wehrle, Maximilian Junker, Dietmar Freudenstein

引用次数: 19

An Empirical Evaluation of Mutation Operators for Deep Learning Systems 深度学习系统中突变算子的经验评价

2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2020-10-01 DOI: 10.1109/icst46399.2020.00018

Gunel Jahangirova, P. Tonella

{"title":"An Empirical Evaluation of Mutation Operators for Deep Learning Systems","authors":"Gunel Jahangirova, P. Tonella","doi":"10.1109/icst46399.2020.00018","DOIUrl":"https://doi.org/10.1109/icst46399.2020.00018","url":null,"abstract":"Deep Learning (DL) is increasingly adopted to solve complex tasks such as image recognition or autonomous driving. Companies are considering the inclusion of DL components in production systems, but one of their main concerns is how to assess the quality of such systems. Mutation testing is a technique to inject artificial faults into a system, under the assumption that the capability to expose (kilt) such artificial faults translates into the capability to expose also real faults. Researchers have proposed approaches and tools (e.g., Deep-Mutation and MuNN) that make mutation testing applicable to deep learning systems. However, existing definitions of mutation killing, based on accuracy drop, do not take into account the stochastic nature of the training process (accuracy may drop even when re-training the un-mutated system). Moreover, the same mutation operator might be effective or might be trivial/impossible to kill, depending on its hyper-parameter configuration. We conducted an empirical evaluation of existing operators, showing that mutation killing requires a stochastic definition and identifying the subset of effective mutation operators together with the associated most effective configurations.","PeriodicalId":235967,"journal":{"name":"2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128159482","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: 38

ICST 2020 Breaker Page ICST 2020断路器页面

2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2020-10-01 DOI: 10.1109/icst46399.2020.00003

引用次数: 0

ICST 2020 Commentary ICST 2020评论

2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2020-10-01 DOI: 10.1109/icst46399.2020.00001

引用次数: 0

Automated verification of compliance of non-functional requirements on mobile applications through metamorphic testing 通过变形测试自动验证移动应用程序的非功能需求的遵从性

2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2020-10-01 DOI: 10.1109/ICST46399.2020.00053

M. C. Júnior

{"title":"Automated verification of compliance of non-functional requirements on mobile applications through metamorphic testing","authors":"M. C. Júnior","doi":"10.1109/ICST46399.2020.00053","DOIUrl":"https://doi.org/10.1109/ICST46399.2020.00053","url":null,"abstract":"The growing use of mobile applications in almost every aspect of modern life, from banking to office systems, is making it is quality increasingly necessary. Thus, software testing activities have been increasingly in demand in this domain. However, mobile application testing imposes several new challenges and several peculiarities, such as limited power, interface adaptation, and privacy of user data. Most of these peculiarities are related to Non-Functional Requirements (NFRs) and conventional software testing approaches are ineffective. Based on this, the Metamorphic Testing (MT) is an approach that has been applied in many domains as a strategy for generating new test cases and an alternative to alleviate the oracle problem. Through the generation of Metamorphic Relations (MRs), generated from characteristics of the System Under Testing (SUT), it is possible to evaluate the presence of flaws. Recently, studies have been conducted to evaluate the applicability of MT to reveal performance flaws. The goal of this Ph.D. project proposal is to propose an approach to automate the verification of compliance of NFRs on mobile applications through MT. Also, we intend to develop a tool for applying the approach, and a set of criteria to improve the process of verifying NFRs through MT. Finally, we expect to evaluate the effectiveness of the approach on real mobile applications.","PeriodicalId":235967,"journal":{"name":"2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128320341","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

Detecting Higher-Order Merge Conflicts in Large Software Projects 在大型软件项目中检测高阶合并冲突

2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2020-10-01 DOI: 10.1109/icst46399.2020.00043

Thorsten Wuensche, A. Andrzejak, Sascha Schwedes

{"title":"Detecting Higher-Order Merge Conflicts in Large Software Projects","authors":"Thorsten Wuensche, A. Andrzejak, Sascha Schwedes","doi":"10.1109/icst46399.2020.00043","DOIUrl":"https://doi.org/10.1109/icst46399.2020.00043","url":null,"abstract":"Merge conflicts can occur when multiple developers work concurrently on the same source code corpus. Diverging textual changes (in the same lines of code) are typically easy to resolve with help of common tools like Git. More challenging are higher-order merge conflicts. They arise as the result of unintended interactions between changes in different parts of the source code. Higher-order merge conflicts can be caused by a combination of changes, and so even thorough testing of the individual development branches might not be able to identify them. We suggest an approach based on static analysis and a prototypical tool to detect potential higher-order merge conflicts. Our method identifies potentially dangerous dependencies between changed code fragments in a call graph. An evaluation on SAP HANA, a very large industrial product in C++, shows that the approach is able to identify 62% of higher-order merge conflicts causing build failures over 22 months project development time. The same prototype finds no instance of higher-order merge conflicts causing test failures in SAP HANA during a two month development period. In summary, our method scales well and can identify higher-order merge conflicts which escape traditional testing.","PeriodicalId":235967,"journal":{"name":"2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129012877","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

Poster: Is Euclidean Distance the best Distance Measurement for Adaptive Random Testing? 海报:欧几里得距离是自适应随机测试的最佳距离度量吗?

2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2020-10-01 DOI: 10.1109/icst46399.2020.00049

Rubing Huang, Chenhui Cui, Weifeng Sun, D. Towey

引用次数: 9

Agent-based Testing of Extended Reality Systems 基于agent的扩展现实系统测试

2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2020-10-01 DOI: 10.1109/icst46399.2020.00051

R. Prada, I. Prasetya, Fitsum Meshesha Kifetew, F. Dignum, T. Vos, Jason Lander, Jean-Yves Donnart, Alexandre Kazmierowski, Joseph Davidson, Pedro M. Fernandes

引用次数: 3

An Empirical Analysis of Blind Tests 盲测的实证分析

2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST) Pub Date : 2020-10-01 DOI: 10.1109/icst46399.2020.00034

Kesina Baral, Jeff Offutt

{"title":"An Empirical Analysis of Blind Tests","authors":"Kesina Baral, Jeff Offutt","doi":"10.1109/icst46399.2020.00034","DOIUrl":"https://doi.org/10.1109/icst46399.2020.00034","url":null,"abstract":"Modern software engineers automate as many tests as possible. Test automation allows tests to be run hundreds or thousands of times: hourly, daily, and sometimes continuously. This saves time and money, ensures reproducibility, and ultimately leads to software that is better and cheaper. Automated tests must include code to check that the output of the program on the test matches expected behavior. This code is called the test oracle and is typically implemented in assertions that flag the test as passing if the assertion evaluates to true and failing if not. Since automated tests require programming, many problems can occur. Some lead to false positives, where incorrect behavior is marked as correct, and others to false negatives, where correct behavior is marked as incorrect. This paper identifies and studies a common problem where test assertions are written incorrectly, leading to incorrect behavior that is not recognized. We call these tests blind because the test does not see the incorrect behavior. Blind tests cause false positives, essentially wasting the tests. This paper presents results from several human-based studies to assess the frequency of blind tests with different software and different populations of users. In our studies, the percent of blind tests ranged from a low of 39% to a high of 95%.","PeriodicalId":235967,"journal":{"name":"2020 IEEE 13th International Conference on Software Testing, Validation and Verification (ICST)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122356810","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