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Assuring the safety and trustworthiness of autonomous systems is particularly difficult when learning-enabled components and open environments are involved. Formal methods provide strong guarantees but depend on complete models and static…
The paper examines the handling times of software vulnerabilities in CPython, the reference implementation and interpreter for the today's likely most popular programming language, Python. The background comes from the so-called…
Python has become the most popular programming language as it is friendly to work with for beginners. However, a recent study has found that most security issues in Python have not been indexed by CVE and may only be fixed by 'silent'…
The Python Battery Optimisation and Parameterisation (PyBOP) package provides methods for estimating and optimising battery model parameters, offering both deterministic and stochastic approaches with example workflows to assist users.…
Model checking is a fundamental technique for verifying finite state concurrent systems. Traditionally, model designs were initially created to facilitate the application of model checking. This process, representative of Model Driven…
The 2019 edition of Stack Overflow developer survey highlights that, for the first time, Python outperformed Java in terms of popularity. The gap between Python and Java further widened in the 2020 edition of the survey. Unfortunately,…
Monitoring is the study of a system at runtime, looking for input and output events to discover, check or enforce behavioral properties. Interactive debugging is the study of a system at runtime in order to discover and understand its bugs…
Despite its massive popularity as a programming language, especially in novel domains like data science programs, there is comparatively little research about fault localization that targets Python. Even though it is plausible that several…
Runtime verification (RV) has the potential to enable the safe operation of safety-critical systems that are too complex to formally verify, such as Robot Operating System 2 (ROS2) applications. Writing correct monitors can itself be…
Python is one of the most popular programming languages; as such, projects written in Python involve an increasing number of diverse security vulnerabilities. However, existing state-of-the-art analysis tools for Python only support a few…
Different security issues are a common problem for open source packages archived to and delivered through software ecosystems. These often manifest themselves as software weaknesses that may lead to concrete software vulnerabilities. This…
This paper presents FauxPy, a fault localization tool for Python programs. FauxPy supports seven well-known fault localization techniques in four families: spectrum-based, mutation-based, predicate switching, and stack trace fault…
Automated regression test generation has been extensively explored, yet generating high-quality tests for Python programs remains particularly challenging. Because of the Python's dynamic typing features, existing approaches, ranging from…
Large language models possess impressive capabilities in generating programs (e.g., Python) from natural language descriptions to execute robotic tasks. However, these generated programs often contain errors that violate externally given…
While attackers often distribute malware to victims via open-source, community-driven package repositories, these repositories do not currently run automated malware detection systems. In this work, we explore the security goals of the…
PyPOTS is an open-source Python library dedicated to data mining and analysis on multivariate partially-observed time series with missing values. Particularly, it provides easy access to diverse algorithms categorized into five tasks:…
We present Pylot, a platform for autonomous vehicle (AV) research and development, built with the goal to allow researchers to study the effects of the latency and accuracy of their models and algorithms on the end-to-end driving behavior…
Perception algorithms in autonomous vehicles are vital for the vehicle to understand the semantics of its surroundings, including detection and tracking of objects in the environment. The outputs of these algorithms are in turn used for…
As the need for large-scale data processing grows, distributed programming frameworks like PySpark have become increasingly popular. However, the task of converting traditional, sequential code to distributed code remains a significant…
The most commonly used open-source process mining software tools today are ProM and PM4Py, written in Java and Python, respectively. Such high-level, often interpreted, programming languages trade off performance with memory safety and…