- Advanced Track
- Hybrid
Sustainability, maintainability, testability and ease of use of research software, while gaining importance, often fall short in scientific practice. Applying principles of software engineering and design can greatly improve software quality, thereby enabling others to readily use it, to understand and reproduce results. Ultimately, this enhances the overall scientific quality of the published results.
In this course, we dive into the practical aspects of software engineering and design specifically tailored for scientific software, in order to make it more extensible, maintainable and testable. The principles we discuss can be applied to various types of codes such as software for numerical simulation as well as scripts for data processing.
We take the viewpoint of an academic software developer that is exposed to an existing code base with the task to add further functionality. Approaches to dealing with common obstacles like missing tests, interposed functional aspects and inherited technical dept will be discussed. Based on the lessons learned, we also explore how to structure and deploy software used for e.g. data processing.
During practical hands-on sessions, participants will interactively learn how to utilize software development techniques to tackle the aforementioned issues in practice in order to enhance the quality and reproducibility of their software.
This workshop will be held as a hybrid event at Philipps University Marburg and online.
This workshop provides a foundational introduction to Object-Oriented Programming (OOP) in Python and the essential role of version control with Git in scientific workflows. It focuses on implementing software design principles to create modular, testable code, combining theoretical frameworks with a practical exercise to ensure immediate applicability to research software.
There will be a lunch break and a coffee break in the morning and afternoon.
Your Benefits
This HeFDI Code School series adresses the need of especially early career researchers on learning how to create good scientific software and increase the quality of their code for better reusability and sustainability.
Participants of these workshops will learn about
- software design principles for modular and testable code
- practical application of design principles in different example codes
- OOP in Python
- usage and importance of version control system git
- code refactoring
- testing and validation techniques
- test automation
- practical & Transfer Exercises
Instructors
The instructors are Christian Iwainsky, Marcel Giar and Tim Jammer.
Language
The workshops will be held in English.
Prerequisites
The workshop is designed for any users and authors of research software. No knowledge of high performance computing is necessary.
Participants need a working knowledge of writing and reading Python code.
Bring your own device with a working Python installation (preferably Python >= 3.11).
Publications
Code examples and the slides can be found on GitLab.