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Developing Computational Software

We would like to share some of the experiences we've had over the past 15 years working on critical software with a complex legacy component. It dates back to the 1980s and has evolved into a powerful system packed with domain knowledge and smart algorithms. Its "killer feature" is its ability to handle complex geometries. Over the years, the program has more than proven its value.

Do you recognize this: software that was developed long ago, has been extended and adapted for years, but no longer meets today’s standards? If so, then our lunch lecture on modernizing software on September 24 is for you.

Although there are still plenty of doubts about the real impact of AI, there is one sector where its effect can no longer be denied: software development. VORtech quickly started working with the new AI possibilities. But not without the necessary safeguards because there are indeed risks.

When Hans Voerknecht developed a new way to evaluate accessibility a few years ago, he quickly knew that this would require good software. Although he could program himself, he also realized that his strength lies in devising the calculation method and not in software development. That is why he partnered with VORtech.

These days, technology is becoming so complex that many systems are built in a partnership of specialized companies. This has the obvious benefit of using the best possible knowledge and experience, but it also has pitfalls. Here are six rules, illustrated with our experiences in a recent project.

Bas van ’t Hof from VORtech helped brain researchers by building software to compute how drugs spread through the brain. With this software, the researchers can now see what their theoretical work implies, allowing for more efficient drug development with fewer laboratory animals.

The 2023 edition in Amsterdam offered a showcase of everything that is going on in the field, from software management, digital twins, and machine learning to impressive applications.

In many companies, the workflow around simulations is a highly manual and error-prone process. Automating a simulation workflow saves time and effort. Moreover, it makes the process far more reliable, and it opens new possibilities.

Sphinx is a documentation tool for software projects that can create easily searchable HTML pages and excellent PDFs. It is well suited for documenting scientific code bases due to its support for LaTeX-style equations and numerous extensions for plots, diagrams and much more. It would be nice if we could integrate Sphinx with the common build system CMake so that we can automatically generate documentation. This blog describes an approach to do just that.

Documenting code is something nobody enjoys. But everyone agrees that some documentation is needed. What is the essential documentation and how can documenting be made easier?