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SHallow REcurrent Decoders (SHRED) provide a deep learning strategy for modeling high-dimensional dynamical systems and/or spatiotemporal data from dynamical system snapshot observations. PySHRED is a Python package that implements SHRED…
An open source symbolic tool for vector fields analysis 'SymFields' is developed in Python. The SymFields module is constructed upon Python symbolic module sympy, which could only conduct scaler field analysis. With SymFields module, you…
Python applications depend on third-party native libraries that may be vendored within package distributions or installed on the host system. When vulnerabilities are discovered in these native libraries, determining which Python packages…
In this paper, we present the CPG analysis platform, which enables the translation of source code into a programming language-independent representation, based on a code property graph. This allows security experts and developers to capture…
A critical issue faced by open-source software projects is the risk of key personnel leaving the project. This risk is exacerbated in large projects that have been under development for a long time and experienced growth in their…
Software development effort estimation (SDEE) generally involves leveraging the information about the effort spent in developing similar software in the past. Most organizations do not have access to sufficient and reliable forms of such…
In today's fast-paced tech industry, there is a growing need for tools that evaluate a programmer's job readiness based on their coding performance. This study focuses on predicting the potential of Codeforces users to secure various levels…
In recent years, the growing complexity and scale of source code have rendered manual software vulnerability detection increasingly impractical. To address this challenge, automated approaches leveraging machine learning and code embeddings…
Many software development organizations still lack support for obtaining intellectual control over their software development processes and for determining the performance of their processes and the quality of the produced products.…
A large scale collection of both semantic and natural language resources is essential to leverage active Software Engineering research areas such as code reuse and code comprehensibility. Existing machine learning models ingest data from…
In recent years, Predictive Process Mining (PPM) techniques based on artificial neural networks have evolved as a method for monitoring the future behavior of unfolding business processes and predicting Key Performance Indicators (KPIs).…
We present PyOECP, a Python-based flexible open-source software for estimating and modeling the complex permittivity obtained from the open-ended coaxial probe (OECP) technique. The transformation of the measured reflection coefficient to…
Software quality is an important problem for technology companies, since it substantially impacts the efficiency, usefulness, and maintainability of the final product; hence, code review is a must-do activity for software developers. During…
Open Source Software (OSS) has been a popular form in software development. In this paper, we use statistical approaches to derive OSS quality estimation models. Our objective is to build estimation models for the number of defects with…
Python is very popular because it can be used for a wider audience of developers, data scientists, machine learning experts and so on. Like other programming languages, there are beginner to advanced levels of writing Python code. However,…
Software developers use Application Programming Interfaces (APIs) of libraries and frameworks extensively while writing programs. In this context, the recommendations provided in code completion pop-ups help developers choose the desired…
Software visualization seeks to represent software artifacts graphical-ly in two or three dimensions, with the goal of enhancing comprehension, anal-ysis, maintenance, and evolution of the source code. In this context, visualiza-tions…
Signature-based methods have recently gained significant traction in machine learning for sequential data. In particular, signature kernels have emerged as powerful discriminators and training losses for generative models on time-series,…
The advent of quantum computing poses a significant challenge as it has the potential to break certain cryptographic algorithms, necessitating a proactive approach to identify and modernize cryptographic code. Identifying these…
Open source software (OSS), playing an increasingly critical role nowadays, has been commonly adopted and integrated in various software products. For many practitioners, selecting and adopting suitable OSS can help them greatly. Though…