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May 30, 2023 •274 likes •541 views

S oftware Analysis And Transformation Organising a research team around the research software around the research team in software engineering Motivation, experiences, lessons Jurgen J. Vinju B Master SE National Centre Mathematics &

  1. S oftware Analysis And Transformation Organising a research team around the research software around the research team in software engineering Motivation, experiences, lessons Jurgen J. Vinju B

  2. Master SE • National Centre Mathematics & Computer Science • Programming languages and systems SWAT ATEAMS • Algol, Python • ASF+SDF, Rascal • MonetDB, W3C • Software Improvement Group (spin-off) • Software Quality Assessment & Monitoring • Reverse Engineering • CWI SWAT ≡ INRIA ATEAMS • all about source code • supporting the tasks of programmers to {make,maintain} better software, cheaper • understanding and controlling software complexity • Master Software Engineering @{Universiteit van Amsterdam, VU, HvA} SWAT - S oftWare Analysis And Transformation

  3. Team Research collaboration HR methods Research Societal Research Impact team(s) field Funding External collaboration Education SWAT - S oftWare Analysis And Transformation

  4. domain- pragmatic code = data dependent Software Analysis & Transformation creative, undecidable multi-faceted innovative infeasible SWAT - S oftWare Analysis And Transformation

  5. Software is wonderful , literally amazing. Our imagination is our only real constraint. SWAT - S oftWare Analysis And Transformation

  6. Understand this little piece of code [Kees van der Laan] 6

  7. Analysis 7

  8. Analyse 8

  9. Understanding software •Simple code •Simple question •Complex domain-specific analysis •Answer: absurd art [Penrose,Escher] 9

  10. the source code of ls ls.c 3894 lines 77 pages 541 choices “its complicated”

  11. Internal Research collaboration People methods Research Societal Research Impact team(s) field Funding External collaboration Education SWAT - S oftWare Analysis And Transformation

  12. Rascal enable more € and better tools PL “valorisation” (application) experiment (empirical methods) Tools € SE knowledge exchange Research Industry (necessary domain knowledge) 12

  13. results in education industry different support uptake domains PL SE surprisingly, Forensics Finance it works! High-tech project + contract community fun funding ATEAMS/SWAT very well evaluated 13

  14. 14

  15. A research team is not a software team 15

  16. fewer resources = more investment in efficiency (accidentally) sold as research output 16

  17. team members prioritise for academic output which is not software 17

  18. “win-win” situation needs weekly recalibration short-term goals has highest priority while long-term tactics enables it all 18

  19. seniors take long term perspective: maintenance, engineering documentation, UX, teaching material community management 19

  20. giving more control to phd students: - failure modes - learning from students - team spirit 20

  21. taking losses: - throwing away code - weekends and holidays - rotten low hanging fruit - [illusion of] self-interest 21

  22. We want (even) more: intuition for software by society patience with solving hard problems interaction with domain experts empirical evidence out-of-the-box thinking online social interaction 22

  23. We need less: code (surprise!) competition for attention commercial rationalisation 23

  24. Summary: we take more risk we burn more energy but we have more impact we make more mistakes and have more problems but also more solutions and more fun ; we create . 24

  25. http://www.usethesource.io Rascal http://www.rascal-mpl.org Tools € Research Industry 25

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