Search Results - (("Python programs") OR ("Python progress"))

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  2. 2

    An empirical study of fault localization in Python programs by Rezaalipour, Mohammad, Furia, Carlo A.

    ISSN: 1382-3256, 1573-7616
    Published: New York Springer US 01.07.2024
    “… This paper is the first multi-family large-scale empirical study of fault localization on real-world Python programs and faults. Using Zou et al…”
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    Journal Article
  3. 3

    Knowledge-Based Environment Dependency Inference for Python Programs by Ye, Hongjie, Chen, Wei, Dou, Wensheng, Wu, Guoquan, Wei, Jun

    ISSN: 1558-1225
    Published: ACM 01.05.2022
    “…Besides third-party packages, the Python interpreter and system libraries are also critical dependencies of a Python program…”
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    Conference Proceeding
  4. 4

    Advanced Python Programming: Accelerate your Python programs using proven techniques and design patterns by Nguyen, Quan

    Published: Birmingham Packt Publishing 2022
    “… libraries Key Features Benchmark, profile, and accelerate Python programs using optimization toolsScale…”
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    eBook
  5. 5

    An automated detection of confusing variable pairs with highly similar compound names in Java and Python programs by Aman, Hirohisa, Amasaki, Sousuke, Yokogawa, Tomoyuki, Kawahara, Minoru

    ISSN: 1382-3256, 1573-7616
    Published: New York Springer US 01.09.2023
    “…Variable names represent a significant source of information regarding the source code, and a successful naming of variables is key to producing readable code…”
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    Journal Article
  6. 6

    Writing python programs to map alleles related to genetic disease by Allbee, Quinn, Barber, Robert

    ISSN: 1470-8175, 1539-3429, 1539-3429
    Published: Hoboken, USA John Wiley & Sons, Inc 01.09.2021
    “… Students are asked to develop their own Python programs to identify the nature of alleles linked to disease…”
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    Journal Article
  7. 7

    Python programs to apply regularized derivatives in the magnetic tilt derivative and gradient intensity data processing: A graphical procedure to choose the regularization parameter by Melo, Janaína Anjos, Mendonça, Carlos Alberto, Marangoni, Yara Regina

    ISSN: 2590-1974, 2590-1974
    Published: Elsevier Ltd 01.09.2023
    Published in Applied computing and geosciences (01.09.2023)
    “…The Tikhonov regularization parameter is a key parameter controlling the smoothness degree and oscillations of a regularized unknown solution. Usual methods to…”
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    Journal Article
  8. 8

    High-Level Compiler Optimizations for Python Programs by Zhou, Tong

    ISBN: 9798265403469
    Published: ProQuest Dissertations & Theses 01.01.2024
    “…As Python becomes the de facto high-level programming language for many data analyt- ics and scientific computing domains, it becomes increasingly critical to…”
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    Dissertation
  9. 9

    PyReload: Dynamic Updating of Python Programs by Reloading by Tang, Wei, Zhang, Min

    ISSN: 2640-0715
    Published: IEEE 01.12.2018
    “… However, there are few studies on dynamic updating of Python. To our knowledge, there exists only one updating approach for Python programs…”
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    Conference Proceeding
  10. 10

    PyTsan: Automated Data Race Detection in Python Programs by Gong, Chaoyue

    ISBN: 9798290903026
    Published: ProQuest Dissertations & Theses 01.01.2025
    “…Python and its ecosystem have become integral to modern software development. Despite Python’s popularity, CPython, the reference implementation, has…”
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    Dissertation
  11. 11

    Leveraging Type Annotations for Effective Fuzzing of Python Programs by Xifaras, Samuel

    ISBN: 9798304993609
    Published: ProQuest Dissertations & Theses 01.01.2024
    “…Python is among the most popular programming languages, and it powers software systems across diverse domains. Ensuring Python-language systems can grow…”
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    Dissertation
  12. 12

    Test Coverage in Python Programs by Zhai, Hongyu, Casalnuovo, Casey, Devanbu, Prem

    ISSN: 2574-3864
    Published: IEEE 01.05.2019
    “…We study code coverage in several popular Python projects: flask, matplotlib, pandas, scikit-learn, and scrapy. Coverage data on these projects is gathered and…”
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    Conference Proceeding
  13. 13

    How Do Python Programs Use Inheritance? A Replication Study by Orru, Matteo, Tempero, Ewan, Marchesi, Michele, Tonelli, Roberto

    ISSN: 1530-1362
    Published: IEEE 01.12.2015
    “…In this work we present an empirical study on the use of inheritance in a curated corpus of Python systems. Replicating a study preformed on Java, we analyzed…”
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    Conference Proceeding Journal Article
  14. 14

    Random Forests as an extension of the classification trees with the R and Python programs by Rosa Fátima Medina-Merino, Carmen Ismelda Ñique-Chacón

    ISSN: 1993-4912
    Published: Universidad de Lima 01.12.2017
    Published in Interfases (01.12.2017)
    “…This article presents the application of the non-parametric Random Forest method through supervised learning, as an extension of classification trees. The…”
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    Journal Article
  15. 15

    Pythran: enabling static optimization of scientific Python programs by Guelton, Serge, Brunet, Pierrick, Amini, Mehdi, Merlini, Adrien, Corbillon, Xavier, Raynaud, Alan

    ISSN: 1749-4680, 1749-4699
    Published: 01.01.2015
    Published in Computational science & discovery (01.01.2015)
    “…Pythran is an open source static compiler that turns modules written in a subset of Python language into native ones. Assuming that scientific modules do not…”
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    Journal Article
  16. 16

    Detecting Code Smells in Python Programs by Zhifei Chen, Lin Chen, Wanwangying Ma, Baowen Xu

    Published: IEEE 01.11.2016
    “… Consequently, Python programs contain code smells which indicate potential comprehension and maintenance problems…”
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    Conference Proceeding
  17. 17

    Fault-Proneness of Python Programs Tested By Smelled Test Code by Fushihara, Yuki, Aman, Hirohisa, Amasaki, Sousuke, Yokogawa, Tomoyuki, Kawahara, Minoru

    ISSN: 2376-9521
    Published: IEEE 28.08.2024
    “…Software testing is one of the most crucial quality assurance activities, and test results are of great concern to software developers. However, the quality…”
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    Conference Proceeding
  18. 18

    An Error-Aware Automatic Grading Framework for Python Programs Based on Structural-Semantic Similarity by Han, Xue, Wang, Jinwei, Che, Jiayi, Wang, Jinwei

    Published: IEEE 26.12.2025
    “…Most automatic grading systems for Python rely on the built-in ast module to construct abstract syntax trees (ASTs), but they fail when programs contain syntax…”
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    Conference Proceeding
  19. 19

    An Empirical Study of Fault Localization in Python Programs by Rezaalipour, Mohammad, Furia, Carlo A

    ISSN: 2331-8422
    Published: Ithaca Cornell University Library, arXiv.org 20.03.2024
    Published in arXiv.org (20.03.2024)
    “… the capabilities of classic fault localization approaches remain open questions to investigate. This paper is the first multi-family large-scale empirical study of fault localization on real-world Python programs and faults. Using Zou et al…”
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    Paper
  20. 20

    Visual Spectrum-Based Fault Localization for Python Programs Based on the Differentiation of Execution Slices by Khan, Shehroz, Sudheerbabu, Gaadha, Staicu, Bianca Elena, Ahmad, Tanwir, Truscan, Dragos

    Published: IEEE 31.03.2025
    “…We present an automated fault localization technique that can assist developers to localize effectively faults in Python programs…”
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    Conference Proceeding