Suchergebnisse - (static OR statni) python code analysis

  1. 1

    Evaluating Python Static Code Analysis Tools Using FAIR Principles von Hassan, Hassan Bapeer, Sarhan, Qusay Idrees, Beszedes, Arpad

    ISSN: 2169-3536, 2169-3536
    Veröffentlicht: IEEE 2024
    Veröffentlicht in IEEE access (2024)
    “… The quality of modern software relies heavily on the effective use of static code analysis tools …”
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    Journal Article
  2. 2

    Code Analysis with Static Application Security Testing for Python Program von Ma, Li, Yang, Huihong, Xu, Jianxiong, Yang, Zexian, Lao, Qidi, Yuan, Dong

    ISSN: 1939-8018, 1939-8115
    Veröffentlicht: New York Springer US 01.11.2022
    Veröffentlicht in Journal of signal processing systems (01.11.2022)
    “… With the increasing popularity of Python for project development, code security and quality have become severe issues for the past few years …”
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  3. 3

    Static Analysis of Corpus of Source Codes of Python Applications von Kapustin, D. A., Shvyrov, V. V., Shulika, T. I.

    ISSN: 0361-7688, 1608-3261
    Veröffentlicht: Moscow Pleiades Publishing 01.08.2023
    Veröffentlicht in Programming and computer software (01.08.2023)
    “… A static analysis method is one of the popular methods of software code analysis …”
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  4. 4

    Detecting and Explaining Python Name Errors von Wang, Jiawei, Li, Li, Liu, Kui, Du, Xiaoning

    ISSN: 0950-5849
    Veröffentlicht: Elsevier B.V 01.02.2025
    Veröffentlicht in Information and software technology (01.02.2025)
    “… To fill this gap, we propose in this work a static analysis-based approach called DENE (short for Detecting and Explaining Name Errors …”
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  5. 5

    Generative Type Inference for Python von Peng, Yun, Wang, Chaozheng, Wang, Wenxuan, Gao, Cuiyun, Lyu, Michael R.

    ISSN: 2643-1572
    Veröffentlicht: IEEE 11.09.2023
    “… Python is a popular dynamic programming language, evidenced by its ranking as the second most commonly used language on GitHub …”
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  6. 6

    Code2graph: Automatic Generation of Static Call Graphs for Python Source Code von Gharibi, Gharib, Tripathi, Rashmi, Lee, Yugyung

    ISSN: 2643-1572
    Veröffentlicht: ACM 01.09.2018
    “… However, there is a lack of software tools that can automatically analyze the Python source-code and construct its static call graph …”
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  7. 7

    KG4Py: A toolkit for generating Python knowledge graph and code semantic search von Liang, Lu, Li, Yong, Wen, Ming, Liu, Ying

    ISSN: 0954-0091, 1360-0494
    Veröffentlicht: Abingdon Taylor & Francis 31.12.2022
    Veröffentlicht in Connection science (31.12.2022)
    “… In KG4Py, we remove all duplicate files in 317 K Python files and perform static code analyses of these files by using a concrete syntax tree (CST …”
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  8. 8

    Methods and Benchmark for Detecting Cryptographic API Misuses in Python von Frantz, Miles, Xiao, Ya, Pias, Tanmoy Sarkar, Meng, Na, Yao, Danfeng

    ISSN: 0098-5589, 1939-3520
    Veröffentlicht: New York IEEE 01.05.2024
    Veröffentlicht in IEEE transactions on software engineering (01.05.2024)
    “… The current static code analysis tools for Python are unable to scan the increasing complexity of the source code …”
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  9. 9

    Towards Effective Static Type-Error Detection for Python von Oh, Wonseok, Oh, Hakjoo

    ISSN: 2643-1572
    Veröffentlicht: ACM 27.10.2024
    “… This empirical investigation revealed four key static-analysis features that are crucial for the effective detection of Python type errors in practice …”
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  10. 10

    Declarative static analysis for multilingual programs using CodeQL von Youn, Dongjun, Lee, Sungho, Ryu, Sukyoung

    ISSN: 0038-0644, 1097-024X
    Veröffentlicht: Bognor Regis Wiley Subscription Services, Inc 01.07.2023
    Veröffentlicht in Software, practice & experience (01.07.2023)
    “… Summary Declarative static program analysis has become one of the widely‐used program analysis techniques …”
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  11. 11

    VUDENC: Vulnerability Detection with Deep Learning on a Natural Codebase for Python von Wartschinski, Laura, Noller, Yannic, Vogel, Thomas, Kehrer, Timo, Grunske, Lars

    ISSN: 0950-5849, 1873-6025
    Veröffentlicht: Elsevier B.V 01.04.2022
    Veröffentlicht in Information and software technology (01.04.2022)
    “… Identifying potential vulnerable code is important to improve the security of our software systems …”
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  12. 12

    A Study of Large Language Models in Detecting Python Code Violations von Mohammed Salih, Hekar A., Sarhan, Qusay I.

    ISSN: 2410-9355, 2307-549X
    Veröffentlicht: Koya University 01.10.2025
    Veröffentlicht in ARO (Koya) (01.10.2025)
    “… Common static code analysis tools for Python, such as Pylint and Flake8, are widely used to enforce code quality by detecting coding violations without executing the code …”
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  13. 13

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

    ISSN: 1558-1225
    Veröffentlicht: 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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  14. 14

    Principled and practical static analysis for Python: Weakest precondition inference of hyperparameter constraints von Rak‐amnouykit, Ingkarat, Milanova, Ana, Baudart, Guillaume, Hirzel, Martin, Dolby, Julian

    ISSN: 0038-0644, 1097-024X
    Veröffentlicht: Bognor Regis Wiley Subscription Services, Inc 01.03.2024
    Veröffentlicht in Software, practice & experience (01.03.2024)
    “… ‐precondition analysis for Python to extract inter‐argument constraints. The analysis is mostly static, but to make it tractable for typical Python idioms, it selectively switches to the concrete domain for some cases …”
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  15. 15

    PyAnalyzer: An Effective and Practical Approach for Dependency Extraction from Python Code von Jin, Wuxia, Xu, Shuo, Chen, Dawei, He, Jiajun, Zhong, Dinghong, Fan, Ming, Chen, Hongxu, Zhang, Huijia, Liu, Ting

    ISSN: 1558-1225
    Veröffentlicht: ACM 14.04.2024
    “… Dependency extraction based on static analysis lays the ground-work for a wide range of applications …”
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  16. 16

    SecureQwen: Leveraging LLMs for vulnerability detection in python codebases von Mechri, Abdechakour, Ferrag, Mohamed Amine, Debbah, Merouane

    ISSN: 0167-4048
    Veröffentlicht: Elsevier Ltd 01.01.2025
    Veröffentlicht in Computers & security (01.01.2025)
    “… Identifying vulnerabilities in software code is crucial for ensuring the security of modern systems …”
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  17. 17

    Detecting Memory Errors in Python Native Code by Tracking Object Lifecycle with Reference Count von Ma, Xutong, Yan, Jiwei, Zhang, Hao, Yan, Jun, Zhang, Jian

    ISSN: 2643-1572
    Veröffentlicht: IEEE 11.09.2023
    “… Third-party Python modules are usually implemented as binary extensions by using native code (C/C++ …”
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  18. 18

    Towards an understanding of memory leak patterns: an empirical study in Python von Chen, Jie, Yu, Dongjin, Hu, Haiyang

    ISSN: 0963-9314, 1573-1367
    Veröffentlicht: New York Springer US 01.12.2023
    Veröffentlicht in Software quality journal (01.12.2023)
    “… Indeed, runtime leak detection is time consuming and usually done after the fact, while manual code inspection requires rich developer experience …”
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  19. 19

    Static analysis driven enhancements for comprehension in machine learning notebooks von Venkatesh, Ashwin Prasad Shivarpatna, Sabu, Samkutty, Chekkapalli, Mouli, Wang, Jiawei, Li, Li, Bodden, Eric

    ISSN: 1382-3256, 1573-7616
    Veröffentlicht: New York Springer US 01.09.2024
    “… Jupyter notebooks have emerged as the predominant tool for data scientists to develop and share machine learning solutions, primarily using Python as the programming language …”
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  20. 20

    DeVAIC: A tool for security assessment of AI-generated code von Cotroneo, Domenico, De Luca, Roberta, Liguori, Pietro

    ISSN: 0950-5849
    Veröffentlicht: Elsevier B.V 01.01.2025
    Veröffentlicht in Information and software technology (01.01.2025)
    “… This research work introduces DeVAIC (Detection of Vulnerabilities in AI-generated Code), a tool to evaluate the security of AI-generated Python code, which overcomes the challenge of examining incomplete code …”
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