Search Results - (( (state OR state:mn) python code analysis ) 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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CpGtools: a python package for DNA methylation analysis by Wei, Ting, Nie, Jinfu, Larson, Nicholas B, Ye, Zhenqing, Eckel-Passow, Jeanette E, Robertson, Keith D, Kocher, Jean-Pierre A, Wang, Liguo

“…Abstract Motivation DNA methylation can be measured at the single CpG level using sodium bisulfite conversion of genomic DNA followed by sequencing or array…”
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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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Pastas: Open Source Software for the Analysis of Groundwater Time Series by Collenteur, Raoul A., Bakker, Mark, Caljé, Ruben, Klop, Stijn A., Schaars, Frans

“…), and the detection of trends and outliers. Pastas is a new and open source Python package for the analysis of hydrogeological time series…”
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Detecting Memory Errors in Python Native Code by Tracking Object Lifecycle with Reference Count by Ma, Xutong, Yan, Jiwei, Zhang, Hao, Yan, Jun, Zhang, Jian

“… To detect such problems, state-of-the-art approaches have made groundbreaking contributions to identifying inappropriate final refcount values before returning from native code to Python…”
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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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Evaluating Large Language Models in Class-Level Code Generation by Du, Xueying, Liu, Mingwei, Wang, Kaixin, Wang, Hanlin, Liu, Junwei, Chen, Yixuan, Feng, Jiayi, Sha, Chaofeng, Peng, Xin, Lou, Yiling

“…, function-level or statement-level code generation), which mainly asks LLMs to generate one single code unit (e.g…”
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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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Environmental and health risk assessment of polycyclic aromatic hydrocarbons and toxic elements in the red sea using Monte Carlo simulation by Sayed, F. Alshaima, Eid, Mohamed Hamdy, El-Sherbeeny, Ahmed M., Abdel-Gawad, Gouda Ismail, Mohamed, Essam A., Abukhadra, Mostafa R.

“…This research evaluates the environmental and health risks linked to potentially toxic elements (PTEs) and PAHs along the western coast of the Gulf of Suez,…”
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Quantifying the interpretation overhead of Python by Zhang, Qiang, Xu, Lei, Zhang, Xiangyu, Xu, Baowen

“…•Quantitative overhead analysis for the Python interpreter based on sampling.•Overhead decomposition from both opcode and project composition perspectives…”
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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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ProPy: Prolog-based Fault Localization Tool for Python by Morin, Janneke, Ghosh, Krishnendu

“… By examining which statements of the program were executed in successful versus unsuccessful test cases, then extract insight into the "suspiciousness" of areas of the program…”
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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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