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Python is known to be a versatile language, well suited both for beginners and advanced users. Some elements of the language are easier to understand than others: some are found in any kind of code, while some others are used only by…

Python, one of the most prevalent programming languages today, is widely utilized in various domains, including web development, data science, machine learning, and DevOps. Recent scholarly efforts have proposed a methodology to assess…

Open source software (OSS) development relies on diverse skill sets. However, to our knowledge, there are no tools which detect OSS-related skills. In this paper, we present a novel method to detect OSS skills and prototype it in a tool…

PyGSTi is a Python software package for assessing and characterizing the performance of quantum computing processors. It can be used as a standalone application, or as a library, to perform a wide variety of quantum characterization,…

In this paper, we present jscefr (pronounced jes-cee-fer), a tool that detects the use of different elements of the JavaScript (JS) language, effectively measuring the level of proficiency required to comprehend and deal with a fragment of…

The PySCF package has emerged as a powerful and flexible open-source platform for quantum chemistry simulations. However, the efficiency of electronic structure calculations can vary significantly depending on the choice of computational…

Numerical stability is a crucial requirement of reliable scientific computing. However, despite the pervasiveness of Python in data science, analyzing large Python programs remains challenging due to the lack of scalable numerical analysis…

Python is known to be used by beginners to professional programmers. Python provides functionality to its community of users through PyPI libraries, which allows developers to reuse functionalities to an application. However, it is unknown…

Software vulnerabilities are a fundamental cause of cyber attacks. Effectively identifying these vulnerabilities is essential for robust cybersecurity, yet it remains a complex and challenging task. In this paper, we present SafePyScript, a…

Code sharing and reuse is a widespread use practice in software engineering. Although a vast amount of open-source Python code is accessible on many online platforms, programmers often find it difficult to restore a successful runtime…

Neural Networks are notoriously difficult to inspect. We introduce comgra, an open source python library for use with PyTorch. Comgra extracts data about the internal activations of a model and organizes it in a GUI (graphical user…

Performance analysis is a critical step in the oft-repeated, iterative process of performance tuning of parallel programs. Per-process, per-thread traces (detailed logs of events with timestamps) enable in-depth analysis of parallel program…

This paper proposes an open source visual analytics tool consisting of several views and perspectives on eye movement data collected during code reading tasks when writing computer programs. Hence the focus of this work is on code and…

The key to speeding up applications is often understanding where the elapsed time is spent, and why. This document reviews in depth the full array of performance analysis tools and techniques available on Linux for this task, from the…

Call graph construction is the foundation of inter-procedural static analysis. PYCG is the state-of-the-art approach for constructing call graphs for Python programs. Unfortunately, PyCG does not scale to large programs when adapted to…

Software projects under version control grow with each commit, accumulating up to hundreds of thousands of commits per repository. Especially for such large projects, the traversal of a repository and data extraction for static source code…

We introduce \texttt{pycobra}, a Python library devoted to ensemble learning (regression and classification) and visualisation. Its main assets are the implementation of several ensemble learning algorithms, a flexible and generic interface…

We introduce pyGSL, a Python library that provides efficient implementations of state-of-the-art graph structure learning models along with diverse datasets to evaluate them on. The implementations are written in GPU-friendly ways, allowing…

We continuously interact with computerized systems to achieve goals and perform tasks in our personal and professional lives. Therefore, the ability to program such systems is a skill needed by everyone. Consequently, computational thinking…

Modern Python projects execute computational functions using native libraries and give Python interfaces to boost execution speed; hence, testing these libraries becomes critical to the project's robustness. One challenge is that existing…