2021 IEEE/ACM International Conference on Automation of Software Test (AST)最新文献_第2页

An Evolutionary Approach to Adapt Tests Across Mobile Apps 一种适应移动应用程序测试的进化方法

2021 IEEE/ACM International Conference on Automation of Software Test (AST) Pub Date : 2021-04-12 DOI: 10.1109/AST52587.2021.00016

L. Mariani, M. Pezzè, Valerio Terragni, D. Zuddas

引用次数: 10

Automated User Experience Testing through Multi-Dimensional Performance Impact Analysis 通过多维性能影响分析的自动化用户体验测试

2021 IEEE/ACM International Conference on Automation of Software Test (AST) Pub Date : 2021-04-08 DOI: 10.1109/AST52587.2021.00024

Chidera Biringa, Gökhan Kul

引用次数: 1

Extending Hierarchical Delta Debugging with Hoisting 用提升扩展分层增量调试

2021 IEEE/ACM International Conference on Automation of Software Test (AST) Pub Date : 2021-04-08 DOI: 10.1109/AST52587.2021.00015

Dániel Vince, Renáta Hodován, Daniella Bársony, Ákos Kiss

{"title":"Extending Hierarchical Delta Debugging with Hoisting","authors":"Dániel Vince, Renáta Hodován, Daniella Bársony, Ákos Kiss","doi":"10.1109/AST52587.2021.00015","DOIUrl":"https://doi.org/10.1109/AST52587.2021.00015","url":null,"abstract":"Minimizing failing test cases is an important pre-processing step on the path of debugging. If much of a test case that triggered a bug does not contribute to the actual failure, then the time required to fix the bug can increase considerably. However, test case reduction itself can be a time consuming task, especially if done manually. Therefore, automated minimization techniques have been proposed, the minimizing Delta Debugging (DDMIN) and the Hierarchical Delta Debugging (HDD) algorithms being the most well known. DDMIN does not need any information about the structure of the test case, thus it works for any kind of input. If the structure is known, however, it can be utilized to create smaller test cases faster. This is exemplified by HDD, which works on tree-structured inputs, pruning subtrees at each level of the tree with the help of DDMIN.In this paper, we propose to extend HDD with a reduction method that does not prune subtrees, but replaces them with compatible subtrees further down the hierarchy, called hoisting. We have evaluated various combinations of pruning and hoisting on multiple test suites and found that hoisting can help to further reduce the size of test cases by as much as 80% compared to the baseline HDD. We have also compared our results to other state-of-the-art test case reduction algorithms and found that HDD extended with hoisting can produce smaller output in most of the cases.","PeriodicalId":315603,"journal":{"name":"2021 IEEE/ACM International Conference on Automation of Software Test (AST)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128422081","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: 4

Automated Performance Testing Based on Active Deep Learning 基于主动深度学习的自动化性能测试

2021 IEEE/ACM International Conference on Automation of Software Test (AST) Pub Date : 2021-04-05 DOI: 10.1109/AST52587.2021.00010

Ali Sedaghatbaf, M. H. Moghadam, Mehrdad Saadatmand

{"title":"Automated Performance Testing Based on Active Deep Learning","authors":"Ali Sedaghatbaf, M. H. Moghadam, Mehrdad Saadatmand","doi":"10.1109/AST52587.2021.00010","DOIUrl":"https://doi.org/10.1109/AST52587.2021.00010","url":null,"abstract":"Generating tests that can reveal performance issues in large and complex software systems within a reasonable amount of time is a challenging task. On one hand, there are numerous combinations of input data values to explore. On the other hand, we have a limited test budget to execute tests. What makes this task even more difficult is the lack of access to source code and the internal details of these systems. In this paper, we present an automated test generation method called ACTA for black-box performance testing. ACTA is based on active learning, which means that it does not require a large set of historical test data to learn about the performance characteristics of the system under test. Instead, it dynamically chooses the tests to execute using uncertainty sampling. ACTA relies on a conditional variant of generative adversarial networks, and facilitates specifying performance requirements in terms of conditions and generating tests that address those conditions. We have evaluated ACTA on a benchmark web application, and the experimental results indicate that this method is comparable with random testing, and two other machine learning methods, i.e. PerfXRL and DN.","PeriodicalId":315603,"journal":{"name":"2021 IEEE/ACM International Conference on Automation of Software Test (AST)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117059484","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

Extreme mutation testing in practice: An industrial case study 实践中的极端突变检测:一个工业案例研究

2021 IEEE/ACM International Conference on Automation of Software Test (AST) Pub Date : 2021-03-15 DOI: 10.1109/AST52587.2021.00021

M. Betka, S. Wagner

{"title":"Extreme mutation testing in practice: An industrial case study","authors":"M. Betka, S. Wagner","doi":"10.1109/AST52587.2021.00021","DOIUrl":"https://doi.org/10.1109/AST52587.2021.00021","url":null,"abstract":"Mutation testing is used to evaluate the effectiveness of test suites. In recent years, a promising variation called extreme mutation testing emerged that is computationally less expensive. It identifies methods where their functionality can be entirely removed, and the test suite would not notice it, despite having coverage. These methods are called pseudo-tested. In this paper, we compare the execution and analysis times for traditional and extreme mutation testing and discuss what they mean in practice. We look at how extreme mutation testing impacts current software development practices and discuss open challenges that need to be addressed to foster industry adoption. For that, we conducted an industrial case study consisting of running traditional and extreme mutation testing in a large software project from the semiconductor industry that is covered by a test suite of more than 11,000 unit tests. In addition to that, we did a qualitative analysis of 25 pseudo-tested methods and interviewed two experienced developers to see how they write unit tests and gathered opinions on how useful the findings of extreme mutation testing are. Our results include execution times, scores, numbers of executed tests and mutators, reasons why methods are pseudo-tested, and an interview summary. We conclude that the shorter execution and analysis times are well noticeable in practice and show that extreme mutation testing supplements writing unit tests in conjunction with code coverage tools. We propose that pseudo-tested code should be highlighted in code coverage reports and that extreme mutation testing should be performed when writing unit tests rather than in a decoupled session. Future research should investigate how to perform extreme mutation testing while writing unit tests such that the results are available fast enough but still meaningful.","PeriodicalId":315603,"journal":{"name":"2021 IEEE/ACM International Conference on Automation of Software Test (AST)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123763451","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: 4

A Survey of Video Game Testing 电子游戏测试调查

2021 IEEE/ACM International Conference on Automation of Software Test (AST) Pub Date : 2021-03-11 DOI: 10.1109/AST52587.2021.00018

Cristiano Politowski, Fábio Petrillo, Yann-Gaël Guéhéneuc

引用次数: 29

Automatic Property-based Testing of GraphQL APIs GraphQL api基于属性的自动测试

2021 IEEE/ACM International Conference on Automation of Software Test (AST) Pub Date : 2020-12-14 DOI: 10.1109/AST52587.2021.00009

Stefan Karlsson, Adnan vCauvsevi'c, Daniel Sundmark

引用次数: 17

Program Committee 项目委员会

2021 IEEE/ACM International Conference on Automation of Software Test (AST) Pub Date : 2018-06-01 DOI: 10.1109/icdm.2018.00008

Janice G. Thorpe

{"title":"Program Committee","authors":"Janice G. Thorpe","doi":"10.1109/icdm.2018.00008","DOIUrl":"https://doi.org/10.1109/icdm.2018.00008","url":null,"abstract":"Thorpe Communication a variety of courses Her main academic interests include online education, instructional communication, and assessment of student learning. She is the Director of the Online program, Course Director for Research Methods, as well as the Assessment Director for the Communication Department at UCCS. Janice recieved a BA from the University of Tennessee in Education, a BS from the University of Colorado Denver in Communication, and a PhD from the University of Colorado Denver in Education - Research, Evaluation, and Measurement. throughout her academic career whether working as Director of Composition, Co-Directing the Denver Writing Project, serving as Chair of Faculty Assembly, or developing a campus-wide mentoring program. At the heart of her work is a desire to empower people through increased access to written literacy. Joanne's most recent co-authored book, Writing and School Reform (2017), focuses on the barriers to accessing written literacy in the articulation from high school to college. She is currently working in the areas of critical media literacy and digital ethics in an effort to expand our theoretical and pedagogical responses to the current challenges and opportunities of mass digital writing.","PeriodicalId":315603,"journal":{"name":"2021 IEEE/ACM International Conference on Automation of Software Test (AST)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123080319","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: 0

Title Page i 第1页

2021 IEEE/ACM International Conference on Automation of Software Test (AST) Pub Date : 1900-01-01 DOI: 10.1109/ast52587.2021.00001

引用次数: 0