Výsledky vyhľadávania - "Software testing and debugging"

  1. 1

    Test Automation in Open-Source Android Apps: A Large-Scale Empirical Study Autor Lin, Jun-Wei, Salehnamadi, Navid, Malek, Sam

    ISSN: 2643-1572
    Vydavateľské údaje: ACM 01.09.2020
    “…Automated testing of mobile apps has received significant attention in recent years from researchers and practitioners alike. In this paper, we report on the…”
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  2. 2

    Automated Directed Fairness Testing Autor Udeshi, Sakshi, Arora, Pryanshu, Chattopadhyay, Sudipta

    ISSN: 2643-1572
    Vydavateľské údaje: ACM 01.09.2018
    “…Fairness is a critical trait in decision making. As machine-learning models are increasingly being used in sensitive application domains (e.g. education and…”
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  3. 3

    QBugs: A Collection of Reproducible Bugs in Quantum Algorithms and a Supporting Infrastructure to Enable Controlled Quantum Software Testing and Debugging Experiments Autor Campos, Jose, Souto, Andre

    Vydavateľské údaje: IEEE 01.06.2021
    “… provide experimental subjects and an experimental infrastructure to ease the evaluation of new research…”
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  4. 4

    TerzoN: Human-in-the-Loop Software Testing with a Composite Oracle Autor Davis, Matthew C., Wei, Amy, Myers, Brad A., Sunshine, Joshua

    ISSN: 2994-970X, 2994-970X
    Vydavateľské údaje: New York, NY, USA ACM 19.06.2025
    “…Software testing is difficult, tedious, and may consume 28%–50% of software engineering labor. Automatic test generators aim to ease this burden but have…”
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  5. 5

    Prioritizing Test Inputs for Deep Neural Networks via Mutation Analysis Autor Wang, Zan, You, Hanmo, Chen, Junjie, Zhang, Yingyi, Dong, Xuyuan, Zhang, Wenbin

    ISBN: 1665402962, 9781665402965
    ISSN: 1558-1225
    Vydavateľské údaje: IEEE 01.05.2021
    “…Deep Neural Network (DNN) testing is one of the most widely-used ways to guarantee the quality of DNNs. However, labeling test inputs to check the correctness…”
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  6. 6

    On the Unnecessary Complexity of Names in X.509 and Their Impact on Implementations Autor Sun, Yuteng, Debnath, Joyanta, Hong, Wenzheng, Chowdhury, Omar, Chau, Sze Yiu

    ISSN: 2994-970X, 2994-970X
    Vydavateľské údaje: New York, NY, USA ACM 19.06.2025
    “…TheX.509 Public Key Infrastructure (PKI) provides a cryptographically verifiable mechanism for authenticating a binding of an entity’s public-key with its…”
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  7. 7

    No Bias Left Behind: Fairness Testing for Deep Recommender Systems Targeting General Disadvantaged Groups Autor Wu, Zhuo, Wang, Zan, Luo, Chuan, Du, Xiaoning, Chen, Junjie

    ISSN: 2994-970X, 2994-970X
    Vydavateľské údaje: New York, NY, USA ACM 22.06.2025
    “…Recommender systems play an increasingly important role in modern society, powering digital platforms that suggest a wide array of content, from news and music…”
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  8. 8

    AudioTest: Prioritizing Audio Test Cases Autor Li, Yinghua, Dang, Xueqi, Ouédraogo, Wendkûuni C., Klein, Jacques, Bissyandé, Tegawendé F.

    ISSN: 2994-970X, 2994-970X
    Vydavateľské údaje: New York, NY, USA ACM 22.06.2025
    “…Audio classification systems, powered by deep neural networks (DNNs), are integral to various applications that impact daily lives, like voice-activated…”
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  9. 9

    Learning-to-Rank vs Ranking-to-Learn: Strategies for Regression Testing in Continuous Integration Autor Bertolino, Antonia, Guerriero, Antonio, Miranda, Breno, Pietrantuono, Roberto, Russo, Stefano

    ISSN: 1558-1225
    Vydavateľské údaje: ACM 01.10.2020
    “… a comprehensive study comparing them against each other using subjects from the Apache Commons project…”
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  10. 10

    Abstraction-Aware Inference of Metamorphic Relations Autor Nolasco, Agustín, Molina, Facundo, Degiovanni, Renzo, Gorla, Alessandra, Garbervetsky, Diego, Papadakis, Mike, Uchitel, Sebastian, Aguirre, Nazareno, Frias, Marcelo F.

    ISSN: 2994-970X, 2994-970X
    Vydavateľské údaje: New York, NY, USA ACM 12.07.2024
    “…Metamorphic testing is a valuable technique that helps in dealing with the oracle problem. It involves testing software against specifications of its intended…”
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  11. 11

    Pushing the Limit of 1-Minimality of Language-Agnostic Program Reduction Autor Xu, Zhenyang, Tian, Yongqiang, Zhang, Mengxiao, Zhao, Gaosen, Jiang, Yu, Sun, Chengnian

    ISSN: 2475-1421, 2475-1421
    Vydavateľské údaje: New York, NY, USA ACM 06.04.2023
    “…Program reduction has demonstrated its usefulness in facilitating debugging language implementations in practice, by minimizing bug-triggering programs. There…”
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  12. 12

    FAST approaches to scalable similarity-based test case prioritization Autor Miranda, Breno, Cruciani, Emilio, Verdecchia, Roberto, Bertolino, Antonia

    ISBN: 9781450356381, 1450356389
    ISSN: 1558-1225
    Vydavateľské údaje: New York, NY, USA ACM 27.05.2018
    “…Many test case prioritization criteria have been proposed for speeding up fault detection. Among them, similarity-based approaches give priority to the test…”
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  13. 13

    An empirical study of the effects of test-suite reduction on fault localization Autor Yanbing Yu, Jones, J.A., Harrold, M.J.

    ISBN: 1424444861, 9781424444861, 1605580791, 9781605580791
    ISSN: 0270-5257
    Vydavateľské údaje: IEEE 01.01.2008
    “…Fault-localization techniques that utilize information about all test cases in a test suite have been presented. These techniques use various approaches to…”
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  14. 14

    Evaluating SZZ Implementations Through a Developer-Informed Oracle Autor Rosa, Giovanni, Pascarella, Luca, Scalabrino, Simone, Tufano, Rosalia, Bavota, Gabriele, Lanza, Michele, Oliveto, Rocco

    ISBN: 1665402962, 9781665402965
    ISSN: 1558-1225
    Vydavateľské údaje: IEEE 01.05.2021
    “…) a golden set linking bug-fixing and bug-inducing commits. In both cases, these manual evaluations are performed by researchers with limited knowledge of the studied subject systems…”
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  15. 15

    RoScript: A Visual Script Driven Truly Non-Intrusive Robotic Testing System for Touch Screen Applications Autor Qian, Ju, Shang, Zhengyu, Yan, Shuoyan, Wang, Yan, Chen, Lin

    ISSN: 1558-1225
    Vydavateľské údaje: ACM 01.10.2020
    “…Existing intrusive test automation techniques for touch screen applications (e.g., Appium and Sikuli) are difficult to work on many closed or uncommon systems,…”
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  16. 16

    Improving Fault Localization by Integrating Value and Predicate Based Causal Inference Techniques Autor Kucuk, Yigit, Henderson, Tim A. D., Podgurski, Andy

    ISBN: 1665402962, 9781665402965
    ISSN: 1558-1225
    Vydavateľské údaje: IEEE 01.05.2021
    “…/failure, and so they are subject to confounding bias that distorts the scores they produce…”
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  17. 17

    Automated Energy Optimization of HTTP Requests for Mobile Applications Autor Ding Li, Yingjun Lyu, Jiaping Gui, Halfond, William G. J.

    ISSN: 1558-1225
    Vydavateľské údaje: ACM 14.05.2016
    “…Energy is a critical resource for apps that run on mobile devices. Among all operations, making HTTP requests is one of the most energy consuming. Previous…”
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  18. 18

    Formal Specification and Testing for Reinforcement Learning Autor Varshosaz, Mahsa, Ghaffari, Mohsen, Johnsen, Einar Broch, Wąsowski, Andrzej

    ISSN: 2475-1421, 2475-1421
    Vydavateľské údaje: New York, NY, USA ACM 30.08.2023
    “…The development process for reinforcement learning applications is still exploratory rather than systematic. This exploratory nature reduces reuse of…”
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  19. 19

    AI-driven Java Performance Testing: Balancing Result Quality with Testing Time Autor Traini, Luca, Di Menna, Federico, Cortellessa, Vittorio

    ISSN: 2643-1572
    Vydavateľské údaje: ACM 27.10.2024
    “… During this phase, performance measurements are subject to severe fluctuations, which may adversely affect quality of performance test results…”
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  20. 20

    Operation is the Hardest Teacher: Estimating DNN Accuracy Looking for Mispredictions Autor Guerriero, Antonio, Pietrantuono, Roberto, Russo, Stefano

    ISBN: 1665402962, 9781665402965
    ISSN: 1558-1225
    Vydavateľské údaje: IEEE 01.05.2021
    “…Deep Neural Networks (DNN) are typically tested for accuracy relying on a set of unlabelled real world data (operational dataset), from which a subset is…”
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