ATDx: A tool for providing a data-driven overview of architectural technical debt in software-intensive systems

Architectural technical debt (ATD) in software-intensive systems is mostly invisible to software developers, can be widespread throughout entire code-bases, and its remediation cost is often steep. In recent years, numerous approaches have been proposed to identify, keep track, and ultimately manage ATD. The variety of approaches available opens a new problem, namely how to gain an encompassing overview of the ATD identified in a software-intensive system. With this paper we make available the ATDx tool, an implementation of ATDx written in Python, designed in a plug-in fashion. ATDx is an approach designed to provide a data-driven, intuitive, and actionable overview of the ATD present in a portfolio of software projects. ATDx is based on third-party source code analysis tools, architectural issue severity calculation via clustering, and aggregation of measurements into different architectural technical debt dimensions. The ATDx tool allows users to automatically run the ATDx analysis, generate reports containing the ATDx analysis results, and is integrated with GitHub. In addition to the tool, we provide two already implemented plugins, allowing users to run the ATDx tool out-of-the-box. GitHub repository: https://github.com/S2-group/ATDx Video: https://youtu.be/ULT9fgxuB7E