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检索条件"任意字段=5th IEEE International Conference on Software Testing, Verification and Validation, ICST 2012"

共 131 条记录，以下是1-10 订阅

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Editorial for the special issue of STVR on the 5th ieee international conference on software testing, verification, and validation (icst 2012)

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software testing verification & RELIABILITY 2014年第5期24卷 339-340页

作者： Bertolino, Antonia Labiche, Yvan ISTI CNR Pisa Pisa Italy Carleton Univ Ottawa ON K1S 5B6 Canada

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Does Going Beyond Branch Coverage Make Program Repair Tools More Reliable? 17

Does Going Beyond Branch Coverage Make Program Repair Tools ...

引用

17th ieee international conference on software testing, verification, and validation (icst)

作者： Nilizadeh, Amirfarhad Leavens, Gary T. Pasareanu, Corina S. Le, Xuan-Bach D. Cok, David R. Univ Cent Florida Orlando FL 32816 USA Carnegie Mellon Univ Moffett Field CA USA NASA Ames Res Ctr Moffett Field CA 94035 USA Univ Melbourne Melbourne Vic Australia Safer Software Consulting LLC Rochester NY USA

ISBN: (纸本)9798350308198;9798350308181

Automated program repair (APR) tools generally use a test suite to localize bugs and validate patches. these patches may pass the test suite but still be incorrect, which is called overfitting. To better understand the relationship between code coverage and overfitting, we aim to quantify the reduction in overfitting achieved by having more tests to cover branches multiple times, once 100% branch coverage is reached. We also investigate whether having more such tests increases the chances that the generated patch is exact, meaning that the patched program is syntactically the same as the original, high quality correct code in our dataset. Our experiments used three different test suites, each covering all branches in the code: test suites that cover each branch at least 1, 3, or 5 times. We used seven well-known APR tools for Java on a dataset of buggy programs equipped with formal specifications. Using formal methods allows us to reliably and objectively check for overfitting. Our experimental results indicate that enlarging the test suite beyond 100% coverage of branches reduces overfitting. However, beyond a certain threshold, expanding the test suite to cover branches repeatedly does not reduce overfitting.

关键词： Automated Program Repair software testing Overfitting Branch Coverage Formal Methods

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Active Model Learning for software Interrogation and Diagnosis

Active Model Learning for Software Interrogation and Diagnos...

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17th ieee international conference on software testing, verification, and validation (icst)

作者： Porter, Adam A. Karr, Alan F. Univ Maryland Dept Comp Sci College Pk MD 20742 USA Fraunhofer USA Ctr Mid Atlantic Riverdale MD 20737 USA Temple Univ Dept Stat Operat & Data Sci Philadelphia PA USA

ISBN: (纸本)9798350344806;9798350344790

We propose extension of the concept of software correctness, and the associated task of software testing, to include interrogation and diagnosis, whereby actionable knowledge about the limitations and performance of the software is gleaned. the new paradigm is especially relevant for AI-based systems such as classifiers and large language models (LLMs) that involve interactions among complex software, underlying training/reference data and the analysis/input data. In this context, the need for both interrogation-to identify problematic outputs when there may be no measure of correctness-and diagnosis-to determine where the problem lies-is evident. To make our rhetoric concrete, we present two case studies. Classifier boundaries enable characterization of robustness of classifier output and fragility of inputs. Cliques in metagenomic assembly provide novel insight into the software as well as the potential for performance improvement.

关键词： classifier uncertainty DNA reads metagenomic assembly

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QEX: Automated testing Observability and QA Developer Experience Framework 16

QEX: Automated Testing Observability and QA Developer Experi...

引用

16th ieee international conference on software testing, verification and validation (icst)

作者： Locke, Huang Luohua Keshia, Yap Kai Ting Yu, Joseph Chu Ken Chua, Hock Yao Shopee Pte Ltd 5 Sci Pk Dr Singapore 118265 Singapore

ISBN: (纸本)9781665456661

Automated testing is now applied on a large scale, especially in organizations that embrace a continuous integration and continuous delivery (CI/CD) software development process [1], [2]. While numerous studies have demonstrated the impact of automated testing on software development, there is currently no standardised industrial framework for providing a comprehensive high-level overview on testing activity across projects. this is vital for developing and maintaining test frameworks, and thereby a crucial part of the Quality Assurance (QA) Developer Experience [3]. In this paper, we present QEX, which is a model for integrating common testing data sources to obtain observability on test development in a way that provides transparent and actionable insights to relevant stakeholders. It is most suitable for enterprise contexts where testing is performed on a large scale. We provide an open-source implementation that is used at our company, together with an evaluation of its performance and possible ways to extend it further.

关键词： Observability Framework Testware Maintainability software testing Automated testing software Metrics Quality Metrics Quality Evolution Developer Experience Monitoring

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Poster: Improving Spectrum Based Fault Localization For Python Programs Using Weighted Code Elements 16

Poster: Improving Spectrum Based Fault Localization For Pyth...

引用

16th ieee international conference on software testing, verification and validation (icst)

作者： Sarhan, Qusay Idrees Beszedes, Arpad Univ Szeged Dept Software Engn Szeged Hungary Univ Duhok Dept Comp Sci Duhok Iraq

ISBN: (纸本)9781665456661

In this paper, we present an approach for improving Spectrum-Based Fault Localization (SBFL) by integrating static and dynamic information about code elements. this is achieved by giving more importance to code elements that include mathematical operators compared to other types of elements (e.g., declaration, selection, iteration, or function call) and appear in failed tests. the intuition is that these elements are more likely to have bugs than others. the proposed approach is applicable to any SBFL formula without requiring any modifications to their structures because the weighting is done on the ranking list and not on the formulas. the experimental results of a preliminary study show that our approach achieved a much better performance in terms of average ranking compared to the underlying SBFL formulas. It also improved the Top-N categories;it doubled the number of cases in which the faulty method became the top-ranked element, and in all cases the fault became part of Top-5 of the ranking list.

关键词： Debugging fault localization spectrum-based fault localization importance weight suspiciousness score

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An End-to-End Test Case Prioritization Framework using Optimized Machine Learning Models

An End-to-End Test Case Prioritization Framework using Optim...

引用

17th ieee international conference on software testing, verification, and validation (icst)

作者： Khan, Md Asif Azim, Akramul Liscano, Ramiro Smith, Kevin Chang, Yee-Kang Seferi, Gkerta Tauseef, Qasim Ontario Tech Univ Dept Elect Comp & Software Engn Oshawa ON L1G 0C5 Canada Int Business Machines Corp IBM Armonk NY USA

ISBN: (纸本)9798350344806;9798350344790

Regression testing in software development is challenging due to the large number of test cases and continuous integration (CI) practices. Recently, test case prioritization (TCP) using machine learning (ML) has been shown to efficiently execute regression tests. this study introduces an automated, end-to-end, self-contained ML-based framework, TCP-Tune, tailored exclusively for TCP. the framework utilizes open-source version control system data to combine code-change-related features with test execution results. this integration allows the automated optimization of hyperparameters across different ML models to improve the TCP. the framework also effectively visualizes and utilizes multiple evaluation metrics to evaluate the performance of the model over several builds. Unlike existing implementations, which rely on various frameworks, TCP-Tune enables the effortless incorporation of features from multiple sources and fine-tuned models, thereby providing optimum test prioritization in the ever-changing field of software development. Our approach has helped to provide efficient TCP through experimental assessments of a real-life, large-scale CI system.

关键词： test case prioritization hyperparameter tuning regression testing machine learning

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On the Current State of Academic software testing Education in Sweden 16

On the Current State of Academic Software Testing Education ...

引用

16th ieee international conference on software testing, verification and validation (icst)

作者： Barrett, Ayodele A. Enoiu, Eduard Paul Afzal, Wasif Malardalen Univ Vasteras Sweden

ISBN: (纸本)9798350333350

Well-trained software development personnel, in the art and science of software testing, will effectively and efficiently develop quality software products with potentially fewer, less critical defects. thus software testing education is considered to be an important part of curricula for a university degree in Computer Science or Information Systems. the objective of this paper is to determine how much dedicated knowledge in the field of software testing is taught within Swedish universities. To achieve this objective, a systematic search of syllabi for software testing-related courses was done. From 25 Swedish universities offering Computer Science (or related) degrees, 14 currently offer dedicated courses in software testing. Some findings include: 32% of the individual courses were offered at the undergraduate level;28% of the universities offer courses for specialised testing training;and, for the vast majority of the universities, dedicated software testing courses account for about 5% of the total degree credits. While some universities fare better than others, the overall state of academic software testing education in Sweden is limited but promising

关键词： software testing software testing education Sweden

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Test Cost Reduction for 5G and Beyond using Machine Learning 16

Test Cost Reduction for 5G and Beyond using Machine Learning

引用

16th ieee international conference on software testing, verification and validation (icst)

作者： Havakeshian, Maryam Labiche, Yvan Nejati, Shiva Desjardins, Stephane Haghighi, Kourosh Carleton Univ Ottawa ON Canada Univ Ottawa Ottawa ON Canada Ericsson Ottawa ON Canada

ISBN: (纸本)9798350333350

software testing is essential, but expensive, especially for significant issues, feature-rich systems such as telecommunication systems evolving toward 50 and beyond. there is a need in this domain for effective testing techniques to ensure that a minimal number of test cases assess the most important combinations of system functions with respect to domain-specific criteria. Our approach aims to address this challenge by first automatically mapping existing test cases to the combinations of system capabilities they exercise and visualizing the mappings using decision tree learners. then, the approach uses a combination of the engineers' feedback (domain-specific criteria), mapping data, and test execution logs to propose new test cases covering newly-added capabilities or better exercising/verifying existing ones while ensuring the efficacy at fault detection, code coverage, equipment cost, test execution time, redundancy avoidance, among other things.

关键词： 5G Systems Machine Learning software testing

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Repairing DNN Architecture: Are We there Yet? 16

Repairing DNN Architecture: Are We There Yet?

引用

16th ieee international conference on software testing, verification and validation (icst)

作者： Kim, Jinhan Humbatova, Nargiz Jahangirova, Gunel Tonella, Paolo Yoo, Shin Korea Adv Inst Sci & Technol Sch Comp Daejeon South Korea Univ Svizzera Italiana USI Software Inst Lugano Switzerland Kings Coll London Dept Informat London England

ISBN: (纸本)9781665456661

As Deep Neural Networks (DNNs) are rapidly being adopted within large software systems, software developers are increasingly required to design, train, and deploy such models into the systems they develop. Consequently, testing and improving the robustness of these models have received a lot of attention lately. However, relatively little effort has been made to address the difficulties developers experience when designing and training such models: if the evaluation of a model shows poor performance after the initial training, what should the developer change? We survey and evaluate existing state-of-the-art techniques that can be used to repair model performance, using a benchmark of both real-world mistakes developers made while designing DNN models and artificial faulty models generated by mutating the model code. the empirical evaluation shows that random baseline is comparable with or sometimes outperforms existing state-of-the-art techniques. However, for larger and more complicated models, all repair techniques fail to find fixes. Our findings call for further research to develop more sophisticated techniques for Deep Learning repair.

关键词： deep learning real faults program repair hyperparameter tuning

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validation of Mutation testing in the Safety Critical Industry through a Pilot Study 16

Validation of Mutation Testing in the Safety Critical Indust...

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16th ieee international conference on software testing, verification and validation (icst)

作者： Vercacmmen, Sten Borg, Markus Demeyer, Serge Univ Antwerp Dept Comp Sci Antwerp Belgium Lund Univ Dept Comp Sci Lund Sweden

ISBN: (纸本)9798350333350

Mutation testing is the state-of-the-art technique to evaluate the fault -detection capabilities of a test suite, but its adoption has been limited. In this paper, we aim to investigate where mutation testing fits within the existing test strategies, whether the mutation analysis can be done in a timely manner, and which pain points remain to be tackled for industrial integration. For this, we performed open format interviews with two companies developing safety critical software. Our first case had no experience with mutation testing, allowing us to analyse and aid them with the setup, integration, and the mutation analysis. Our second case has 5 years of experience with mutation testing, providing us with a mature view on mutation testing in practice. Our study found that mutation testing can be combined with continuous integration and offload the work of the human reviewer by providing an initial code-quality review. Equivalent mutants appear to be a less prevalent obstacle, although flaky mutants are a concern that needs to be addressed. Overall, the industrial perception of mutation testing is evolving as more organisations recognise the potential benefits of the technique and work to address its limitations and challenges.

关键词： mutation testing validation safety critical industry pilot study

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