Search Results - (( (statement OR state) python code analysis ) OR ( (stated OR statement) python code analysis ))

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

“… 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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Assessing code readability in Python programming courses using eye‐tracking by Segedinac, Milan, Savić, Goran, Zeljković, Ivana, Slivka, Jelena, Konjović, Zora

“… This paper assesses the readability of Python code statements commonly used in undergraduate programming courses…”
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Mitigating the Uncertainty and Imprecision of Log-Based Code Coverage Without Requiring Additional Logging Statements by Xu, Xiaoyan, Cogo, Filipe R., McIntosh, Shane

“…Understanding code coverage is an important precursor to software maintenance activities (e.g., better testing…”
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GraphPyRec: A novel graph-based approach for fine-grained Python code recommendation by Zong, Xing, Zheng, Shang, Zou, Haitao, Yu, Hualong, Gao, Shang

“… Significant progress has been made in code recommendation for static languages in recent years, but it remains challenging for dynamic languages like Python as accurately determining data flows…”
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Stress-Constrained Topology Optimization for Commercial Software: A Python Implementation for ABAQUS by Fernandes, Pedro, Ferrer, Àlex, Gonçalves, Paulo, Parente, Marco, Pinto, Ricardo, Correia, Nuno

“…, using validated FEM commercial software. The methodology was validated by comparing the sensitivity analysis with the results obtained through finite differences and solving two benchmark problems with the following optimizers…”
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Python for Everyone: Learn and polish your coding skills in Python (English Edition) by Saurabh Chandrakar, Dr. Nilesh Bhaskarrao Bahadure

“…A hands-on guide that will help you to write clean and efficient code in Python Key Features…”
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Data Science Fundamentals with R, Python, and Open Data by Cremonini, Marco

“…Introduction to essential concepts and techniques of the fundamentals of R and Python needed to start data science projectsOrganized with a strong focus on open data, This book discusses concepts…”
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Robustness Analysis of Watermarking Techniques for LLM-Generated Code by Cao, Di, Liu, Shigang, Zhang, Jun, Xiang, Yang

“… This work systematically evaluates two state-of-the-art watermarking paradigms: SWEET, which embeds token-level statistical biases, and CodeMark, which leverages semantic-preserving transformations at the statement level…”
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Visualization of Aqueous Geochemical Data Using Python and WQChartPy by Yang, Jing, Liu, Honghua, Tang, Zhonghua, Peeters, Luk, Ye, Ming

“… This method note presents WQChartPy, an open‐source Python package developed to plot a total of 12 diagrams for analysis of aqueous geochemical data…”
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Artificial intelligence programming with Python: from zero to hero by Xiao, Perry

“…A hands-on roadmap to using Python for artificial intelligence programming In Practical Artificial Intelligence Programming with Python…”
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Learning to Generate Pseudo-Code from Source Code Using Statistical Machine Translation by Oda, Yusuke, Fudaba, Hiroyuki, Neubig, Graham, Hata, Hideaki, Sakti, Sakriani, Toda, Tomoki, Nakamura, Satoshi

“…Pseudo-code written in natural language can aid the comprehension of source code in unfamiliar programming languages…”
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Understanding the Robustness of Transformer-Based Code Intelligence via Code Transformation: Challenges and Opportunities by Li, Yaoxian, Qi, Shiyi, Gao, Cuiyun, Peng, Yun, Lo, David, Lyu, Michael R., Xu, Zenglin

“…Transformer-based models have demonstrated state-of-the-art performance in various intelligent coding tasks such as code comment generation and code completion…”
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The Python workshop: a practical, no-nonsense introduction to Python development by Andrew Bird, Bird, Dr Lau Cher Han, Han, Mario Corchero Jimenez, Jimenez, Graham Lee, Lee, Corey Wade, Wade

“…Cut through the noise and get real results with a step-by-step approach to learning Python 3…”
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NAS Parallel Benchmarks with Python: a performance and programming effort analysis focusing on GPUs by Di Domenico, Daniel, Lima, João V. F., Cavalheiro, Gerson G. H.

“… As a counterpoint to that trend, this paper presents a performance and programming effort analysis with Python, an interpreted and high-level language, which was applied to develop the kernels…”
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Semi-Supervised Code Translation Overcoming the Scarcity of Parallel Code Data by Zhu, Ming, Karim, Mohimenul, Lourentzou, Ismini, Yao, Danfeng Daphne

“… MIRACLE leverages static analysis and compilation to generate synthetic parallel code datasets with enhanced quality and alignment to address the challenge of data scarcity…”
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Beyond Functional Correctness: An Empirical Evaluation of Large Language Models for Text-to-Code Generation by Nogueira, Rodrigo Pato, Vieira, Marco, Campos, Joao R.

“…Large Language Models (LLMs) have become increasingly popular for text-to-code generation, a task that involves converting natural language descriptions into code…”
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Rhodium: Python Library for Many-Objective Robust Decision Making and Exploratory Modeling by Hadjimichael, Antonia, Gold, David, Hadka, David, Reed, Patrick

“…Rhodium is an open source Python library for robust decision making (RDM), many-objective robust decision making (MORDM…”
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A Large-Scale Study of Test Coverage Evolution by Hilton, Michael, Bell, Jonathan, Marinov, Darko

“…Statement coverage is commonly used as a measure of test suite quality. Coverage is often used as a part of a code review process…”
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Towards Identifying Code Proficiency Through the Analysis of Python Textbooks by Rojpaisarnkit, Ruksit, Robles, Gregorio, Kula, Raula Gaikovina, Wang, Dong, Ragkhitwetsagul, Chaiyong, Gonzalez-Barahona, Jesus M., Matsumoto, Kenichi

“… This method involves assigning levels of competence to Python constructs-for instance, placing simple 'print' statements at the most basic level and abstract base classes at the most…”
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Enhancing LLMs Interactions for Python: A Smart API Framework for Extracting and Utilizing Semantic Code Information by Ahmad, Nouman, Zhang, Changsheng

“… In order to recognize import statements, custom functions, and class declarations, as well as how they are used within modules and classes, our system uses libest to parse and analyze Python source files…”
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