Výsledky vyhledávání - (( (stated OR state) python code analysis ) OR ( (static OR stateeeeeen) python code analysis ))*

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  1. 1

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

    ISSN: 0098-5589, 1939-3520
    Vydáno: New York IEEE 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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  2. 2

    galpy: A python LIBRARY FOR GALACTIC DYNAMICS Autor Bovy, Jo

    ISSN: 1538-4365, 0067-0049, 1538-4365
    Vydáno: United States 01.02.2015
    “…I describe the design, implementation, and usage of galpy, a python package for galactic-dynamics calculations…”
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  3. 3

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

    ISSN: 0950-5849
    Vydáno: Elsevier B.V 01.01.2025
    Vydáno v 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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  4. 4

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

    ISSN: 1558-1225
    Vydáno: 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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  5. 5

    PyCG: Practical Call Graph Generation in Python Autor Salis, Vitalis, Sotiropoulos, Thodoris, Louridas, Panos, Spinellis, Diomidis, Mitropoulos, Dimitris

    ISBN: 1665402962, 9781665402965
    ISSN: 1558-1225
    Vydáno: IEEE 01.05.2021
    “… We propose a pragmatic, static approach for call graph generation in Python. We compute all assignment relations between program identifiers of functions, variables, classes, and modules through an inter-procedural analysis…”
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  6. 6

    MTpy: A Python toolbox for magnetotellurics Autor Krieger, Lars, Peacock, Jared R.

    ISSN: 0098-3004, 1873-7803
    Vydáno: Elsevier Ltd 01.11.2014
    Vydáno v Computers & geosciences (01.11.2014)
    “… Written in Python, the code is open source, containing sub-packages and modules for various tasks within the standard MT data processing and handling scheme…”
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  7. 7

    CryptoPyt: Unraveling Python Cryptographic APIs Misuse with Precise Static Taint Analysis Autor Guo, Xiangxin, Jia, Shijie, Lin, Jingqiang, Ma, Yuan, Zheng, Fangyu, Li, Guangzheng, Xu, Bowen, Cheng, Yueqiang, Ji, Kailiang

    ISSN: 2576-9103
    Vydáno: IEEE 09.12.2024
    “… Based on PCAST, we design and implement CryptoPyt, a static code analysis tool that leverages precise taint analysis and 17 cryptographic misuse rules to automatically…”
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  8. 8

    Analyzing LLM-Generated Code According to Four ISO/IEC 5055:2021 Categories Autor Krebs, Rasmus, Mazumdar, Somnath

    ISSN: 2169-3536, 2169-3536
    Vydáno: Piscataway IEEE 2025
    Vydáno v IEEE access (2025)
    “… This paper addresses a gap in current research by evaluating Python code generated by nine state-of-the-art LLMs according to the four main code quality categories…”
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  9. 9

    Interactive Cross-Language Pointer Analysis for Resolving Native Code in Java Programs Autor Zhang, Chenxi, Liang, Yufei, Tan, Tian, Xu, Chang, Kan, Shuangxiang, Sui, Yulei, Li, Yue

    ISSN: 1558-1225
    Vydáno: IEEE 26.04.2025
    “… While JNI mechanism significantly enhances the Java platform's capabilities, it also presents challenges for static analysis of Java programs due to the complex behaviors introduced by native code…”
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  10. 10

    TESTING THE DYNAMIC EXECUTION OF PYTHON PROGRAM CODE DURING THE CERTIFICATION TESTING (DEVELOPMENT) STAGE IN THE CERTIFICATION SYSTEM OF THE MINISTRY OF DEFENSE OF RUSSIA Autor V.V. Samarov

    ISSN: 2307-4205
    Vydáno: Penza State University Publishing House 01.06.2023
    “…" (State Technical Commission of Russia, Moscow, 1999) 1, hereinafter – RD NDV, along with static analysis, a dynamic analysis should be carried…”
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  11. 11

    Inspect4py: A Knowledge Extraction Framework for Python Code Repositories Autor Filgueira, Rosa, Garijo, Daniel

    ISSN: 2574-3864
    Vydáno: ACM 01.05.2022
    “…This work presents inspect4py, a static code analysis framework designed to automatically extract the main features, metadata and documentation of Python code repositories…”
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  12. 12

    MRSimulator: A cross-platform, object-oriented software package for rapid solid-state NMR spectral simulation and analysis Autor Srivastava, Deepansh J, Giammar, Matthew, Venetos, Maxwell C, McCarthy-Carney, Lexi, Grandinetti, Philip J

    ISSN: 1089-7690
    Vydáno: United States 07.12.2024
    Vydáno v The Journal of chemical physics (07.12.2024)
    “…The open-source Python package, MRSimulator, is presented as a simple-to-use, fast, versatile, and extendable package capable of simulating one- and higher-dimensional Nuclear Magnetic Resonance (NMR…”
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  13. 13

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

    ISSN: 2994-970X, 2994-970X
    Vydáno: 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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  14. 14

    Treefix: Enabling Execution with a Tree of Prefixes Autor Souza, Beatriz, Pradel, Michael

    ISSN: 1558-1225
    Vydáno: IEEE 26.04.2025
    “…The ability to execute code is a prerequisite for various dynamic program analyses…”
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  15. 15

    Legacy Code, Live Risk: Empirical Evidence of Malware Detection Gaps Autor Huang, Gang-Cheng, Lai, Tai-Hung

    ISSN: 2076-3417, 2076-3417
    Vydáno: Basel MDPI AG 01.11.2025
    Vydáno v Applied sciences (01.11.2025)
    “… Our results reveal significant detection gaps: loaders compiled in legacy languages (Fortran, COBOL) consistently evade static and dynamic antivirus engines that easily flag their C…”
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  16. 16

    SAGA: Detecting Security Vulnerabilities Using Static Aspect Analysis Autor Marquer, Yoann, Bianculli, Domenico, Briand, Lionel C

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 21.01.2026
    Vydáno v arXiv.org (21.01.2026)
    “… However, existing state-of-the-art analysis tools for Python only support a few vulnerability types…”
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  17. 17

    Is Quantization a Deal-Breaker? Empirical Insights From Large Code Models Autor Afrin, Saima, Xu, Bowen, Mastropaolo, Antonio

    ISSN: 2576-3148
    Vydáno: IEEE 07.09.2025
    “…). While recent studies have established quantization as a promising approach for optimizing large code models (LCMs…”
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  18. 18

    Facial Emotion-Based Stress Analysis Using Python Autor Shaheed, Mohammad, Venkateshwarlu, Dr. S China, Nagaraju, Dr. V Siva, Bhavani, Ms. P Ganga

    ISSN: 2582-3930, 2582-3930
    Vydáno: 31.05.2025
    “…In the current fast-paced world, tracking mental health has become imperative. This project demonstrates a real- time stress detection and analysis system based on facial emotion recognition through deep learning approaches…”
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  19. 19

    Serenity: Library Based Python Code Analysis for Code Completion and Automated Machine Learning Autor Zhao, Wenting, Ibrahim, Abdelaziz, Dolby, Julian, Srinivas, Kavitha, Helali, Mossad, Mansour, Essam

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 05.01.2023
    Vydáno v arXiv.org (05.01.2023)
    “… This flexibility, however, makes static analysis very hard. While creating a sound, or a soundy, analysis for Python remains an open problem, we present in this work Serenity…”
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  20. 20

    Next-Generation Refactoring: Combining LLM Insights and IDE Capabilities for Extract Method Autor Pomian, Dorin, Bellur, Abhiram, Dilhara, Malinda, Kurbatova, Zarina, Bogomolov, Egor, Bryksin, Timofey, Dig, Danny

    ISSN: 2576-3148
    Vydáno: IEEE 06.10.2024
    “… Given that Large Language Models (LLMs) have been trained on large code corpora, if we harness their familiarity with the way developers form functions, we could suggest refactorings that developers are likely to accept…”
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