My VLOEBERGHS chair 2022

VU Brussels kindly honored me with the VLOEBERGHS CHAIR LECTURES 21/22.

I spent the week of 16-20 May 2022 in Brussels for that reason.

In particular, I gave the inaugural lecture which I (eventually) titled as follows:


Software knowledge analytics

as a role model for making sense of the world


The lecture is now available on YouTube.

Camera capture didn't work in the room -- some Covid hiccup.

Enjoy the slides and the audio.

PDF of the slides is available, too.


In the inaugural lecture and the rest of the week, I covered a good bunch of use cases:

  • Software language usage
  • Software technology usage
  • Software developer profiling
  • Work-item prediction
  • Ownership management

I submitted these principles:

  • Hypothesis building
    • Set up falsifiable hypotheses together with the research questions.
    • Lay out the theory to back up those hypotheses/RQs to be reasonable and/or challenging.
  • Data extraction and integration
    • Follow an empirical approach — more artifact- than subject-based.
    • Justify chosen data sources and methods of data extraction and integration.
  • Mathematical modeling
    • Aim at the discovery of mathematical models.
    • Address problems such as “type I error”, “overfitting”, “skewed data”, and “multilevel”.
    • Enable (probabilisitic) reasoning regarding any data, hypotheses, models (c.f., previous principles).
  • Logical reasoning
    • Enrich data extraction and integration.
    • Perform (part of) the analysis by such reasoning.
  • Semantic (meta)data
    • Add programmatically useful documentation for all entities involved.
    • Leverage such documentation in logical reasoning for explainability and otherwise.
  • Continuous replication
    • Enable continuous validation in terms of reproducibility for any project.
    • Enable follow-up projects to layer on top of existing ones soundly.

I also discussed challenges (as in recurring issues calling for better and better approaches):
  • Handling weak data
  • Scaling for evolving data
  • Ontology engineering
  • Knowledge graph population
  • Managing threats to validity

"Most importantly", my lectures aimed to put these papers by my team in the best light:

I am grateful to the following VUB folks who initiated, supported, or endured my honorary chair appointment:


Being a guest of the Software Languages Lab at VUB was a great (learning and social) experience. In addition to Coen, with whom I have worked together in the past, there are several post- and predoctoral team members with topics that are really of interest to me -- with some of them I was able to talk in person:

Finally, I would like to acknowledge my own (current or former) PhD students whose work I integrated into the lecture series:

Throughout the week, I gave some extra presentations and we had good discussions on various SoftLang, PL, MSR, ESE topics. Just for the record, if I get under the bus -- we were also touching the topic of the bus factor -- here are more slide decks that I used in Brussels -- links to PDFs:

SoftLangler Ralf

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