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  1. 1

    Domain Knowledge Matters: Improving Prompts with Fix Templates for Repairing Python Type Errors by Peng, Yun, Gao, Shuzheng, Gao, Cuiyun, Huo, Yintong, Lyu, Michael R.

    ISSN: 1558-1225
    Published: ACM 14.04.2024
    “…As a dynamic programming language, Python has become increasingly popular in recent years…”
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    Conference Proceeding
  2. 2

    Discovering Repetitive Code Changes in Python ML Systems by Dilhara, Malinda, Ketkar, Ameya, Sannidhi, Nikhith, Dig, Danny

    ISSN: 1558-1225
    Published: ACM 01.05.2022
    “… Despite the extraordinary rise in popularity of Python-based ML systems, they do not benefit from these advances…”
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    Conference Proceeding
  3. 3

    PyTy: Repairing Static Type Errors in Python by Chow, Yiu Wai, Di Grazia, Luca, Pradel, Michael

    ISSN: 1558-1225
    Published: ACM 14.04.2024
    “… As more and more code bases get type-annotated, static type checkers detect an increasingly large number of type errors…”
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    Conference Proceeding
  4. 4

    A Python Instrument Control and Data Acquisition Suite for Reproducible Research by Koerner, Lucas J., Caswell, Thomas A., Allan, Daniel B., Campbell, Stuart I.

    ISSN: 0018-9456, 1557-9662
    Published: New York The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 01.04.2020
    “… The National Synchrotron Light Source-II (NSLS-II) has generated an open-source Python data acquisition, management, and analysis software suite that automates X-ray…”
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    Journal Article
  5. 5

    Bloat beneath Python’s Scales: A Fine-Grained Inter-Project Dependency Analysis by Drosos, Georgios-Petros, Sotiropoulos, Thodoris, Spinellis, Diomidis, Mitropoulos, Dimitris

    ISSN: 2994-970X, 2994-970X
    Published: New York, NY, USA ACM 12.07.2024
    “… In this work, we conduct a large-scale, fine-grained analysis to understand bloated dependency code in the PyPI ecosystem…”
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    Journal Article
  6. 6

    SpotFlow: Tracking Method Calls and States at Runtime by Hora, Andre

    ISSN: 2574-1934
    Published: ACM 14.04.2024
    “… In this paper, we propose SpotFlow, a tool to ease the runtime analysis of Python programs. With Spot-Flow, practitioners and researchers can easily extract information…”
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    Conference Proceeding
  7. 7

    CoverUp: Effective High Coverage Test Generation for Python by Altmayer Pizzorno, Juan, Berger, Emery D.

    ISSN: 2994-970X, 2994-970X
    Published: New York, NY, USA ACM 19.06.2025
    “… We evaluate our prototype CoverUp implementation across a benchmark of challenging code derived from open-source Python projects and show that CoverUp substantially improves on the state of the art…”
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    Journal Article
  8. 8

    SNPAAMapper-Python: A highly efficient genome-wide SNP variant analysis pipeline for Next-Generation Sequencing data by Li, Chang, Ma, Kevin, Xu, Nicole, Fu, Chenjian, He, Andrew, Liu, Xiaoming, Bai, Yongsheng

    ISSN: 2624-8212, 2624-8212
    Published: Frontiers Media S.A 12.09.2022
    Published in Frontiers in artificial intelligence (12.09.2022)
    “… In this study, we updated SNPAAMapper, a variant annotation pipeline by converting perl codes to python for generating annotation output with an improved computational efficiency and updated…”
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    Journal Article
  9. 9

    Restoring Reproducibility of Jupyter Notebooks by Wang, Jiawei, Kuo, Tzu-yang, Li, Li, Zeller, Andreas

    Published: ACM 01.10.2020
    “…Jupyter notebooks-documents that contain live code, equations, visualizations, and narrative text-now are among the most popular means to compute, present, discuss and disseminate scientific findings…”
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    Conference Proceeding
  10. 10

    Lost in Translation: A Study of Bugs Introduced by Large Language Models While Translating Code by Pan, Rangeet, Ibrahimzada, Ali Reza, Krishna, Rahul, Sankar, Divya, Wassi, Lambert Pougeum, Merler, Michele, Sobolev, Boris, Pavuluri, Raju, Sinha, Saurabh, Jabbarvand, Reyhaneh

    ISSN: 1558-1225
    Published: ACM 14.04.2024
    “… The prerequisite for advancing the state of LLM-based code translation is to understand their promises and limitations over existing techniques…”
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    Conference Proceeding
  11. 11

    MolProbity: More and better reference data for improved all‐atom structure validation by Williams, Christopher J., Headd, Jeffrey J., Moriarty, Nigel W., Prisant, Michael G., Videau, Lizbeth L., Deis, Lindsay N., Verma, Vishal, Keedy, Daniel A., Hintze, Bradley J., Chen, Vincent B., Jain, Swati, Lewis, Steven M., Arendall, W. Bryan, Snoeyink, Jack, Adams, Paul D., Lovell, Simon C., Richardson, Jane S., Richardson, David C.

    ISSN: 0961-8368, 1469-896X, 1469-896X
    Published: United States Wiley Subscription Services, Inc 01.01.2018
    Published in Protein science (01.01.2018)
    “… There have been many infrastructure improvements, including rewrite of previous Java utilities to now use existing or newly written Python utilities in the open…”
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    Journal Article
  12. 12

    Detecting and Explaining Anomalies Caused by Web Tamper Attacks via Building Consistency-based Normality by Liao, Yifan, Xu, Ming, Lin, Yun, Teoh, Xiwen, Xie, Xiaofei, Feng, Ruitao, Liauw, Frank, Zhang, Hongyu, Dong, Jin Song

    ISSN: 2643-1572
    Published: ACM 27.10.2024
    “… However, their frontend can be manipulable by the clients (e.g., the frontend code can be modified to bypass some validation steps…”
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    Conference Proceeding
  13. 13

    Python Data Analyst's Toolkit - Learn Python and Python-Based Libraries with Applications in Data Analysis and Statistics by Rajagopalan, Gayathri

    ISBN: 9781484263983, 1484263987, 9781484263990, 1484263995
    Published: Berkeley, CA Apress, an imprint of Springer Nature 2021
    “… The code is presented in Jupyter notebooks that can further be adapted and extended. This book is divided into three parts - programming with Python, data analysis and visualization, and statistics…”
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    eBook
  14. 14

    ThinCurr: An open-source 3D thin-wall eddy current modeling code for the analysis of large-scale systems of conducting structures by Hansen, Christopher, Battey, Alexander, Braun, Anson, Miller, Sander, Lagieski, Michael, Stewart, Ian, Sweeney, Ryan, Paz-Soldan, Carlos

    ISSN: 0010-4655
    Published: United States Elsevier B.V 01.10.2025
    Published in Computer physics communications (01.10.2025)
    “… The new code, part of the broader Open FUSION Toolkit, is open-source and designed for ease of use without sacrificing capability and speed through a combination of Python, Fortran, and C/C++ components…”
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    Journal Article
  15. 15
  16. 16

    Python for MATLAB Development - Extend MATLAB with 300,000+ Modules from the Python Package Index by Danial, Albert

    ISBN: 9781484272220, 1484272226, 1484272234, 9781484272237
    Published: Berkeley, CA Apress, an imprint of Springer Nature 2022
    “…This book shows you how to enhance MATLAB with Python solutions to a vast array of computational problems in science, engineering, optimization, statistics, finance, and simulation…”
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    eBook
  17. 17

    Unleashing the Giants: Enabling Advanced Testing for Infrastructure as Code by Sokolowski, Daniel, Spielmann, David, Salvaneschi, Guido

    ISSN: 2574-1934
    Published: ACM 14.04.2024
    “…Infrastructure as Code (IaC) programs are written in imperative programming languages like Python or TypeScript while declar-atively defining the target state of software deployments, which the IaC solution then sets up, e.g…”
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    Conference Proceeding
  18. 18

    ChangeGuard: Validating Code Changes via Pairwise Learning-Guided Execution by Gröninger, Lars, Souza, Beatriz, Pradel, Michael

    ISSN: 2994-970X, 2994-970X
    Published: New York, NY, USA ACM 19.06.2025
    “…Code changes are an integral part of the software development process. Many code changes are meant to improve the code without changing its functional behavior, e.g…”
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    Journal Article
  19. 19

    GSEApy: a comprehensive package for performing gene set enrichment analysis in Python by Fang, Zhuoqing, Liu, Xinyuan, Peltz, Gary

    ISSN: 1367-4811, 1367-4803, 1367-4811
    Published: England Oxford University Press 01.01.2023
    Published in Bioinformatics (Oxford, England) (01.01.2023)
    “…Abstract Motivation Gene set enrichment analysis (GSEA) is a commonly used algorithm for characterizing gene expression changes…”
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    Journal Article
  20. 20

    Symmetry‐mode analysis for local structure investigations using pair distribution function data by Hamilton, Parker K., Moya, Jaime M., Hallas, Alannah M., Morosan, E., Baral, Raju, Frandsen, Benjamin A.

    ISSN: 1600-5767, 0021-8898, 1600-5767
    Published: 5 Abbey Square, Chester, Cheshire CH1 2HU, England International Union of Crystallography 01.08.2023
    Published in Journal of applied crystallography (01.08.2023)
    “…Symmetry‐adapted distortion modes provide a natural way of describing distorted structures derived from higher‐symmetry parent phases. Structural refinements…”
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    Journal Article