On my way to the #INTERNETWARE 2024 conference in Macau, giving a keynote on “Advances in Language-Based Testing” https://conf.researchr.org/details/internetware-2024/internetware-2024-research/3/Keynote-1-Advances-in-Language-Based-Testing

Told you so. #Crowdstrike

(WSR 2005 - https://thomas-zimmermann.com/publications/files/sliwerski-wsr-2005.pdf)

REVEALED: FSE 2025 Call for Papers Adapts to New Realities

Input grammars for fuzzing and test generation! We introduce symbolic parsing, a technique to extract input grammars _statically_ from code, without requiring any input samples. First experiments show an accuracy of 99-100%. Find us Thu 17:00 at FSE 2024: https://2024.esec-fse.org/details/fse-2024-ideas--visions-and-reflections/15/Look-Ma-No-Input-Samples-Mining-Input-Grammars-from-Code-with-Symbolic-Parsing

This “new ideas” paper is available as open access in the ACM DL: https://dl.acm.org/doi/10.1145/3663529.3663790

A benchmark for Python testing and repair tools! Our new TESTS4PY benchmark includes 73 bugs from seven real-world #Python applications, including oracles and support for both system and unit test generation. Demo at #FSE2024 on Wednesday 16:00-18:00: https://2024.esec-fse.org/details/fse-2024-demonstrations/3/Tests4Py-A-Benchmark-for-System-Testing
The paper is also available in the ACM Digital Library:
https://dl.acm.org/doi/10.1145/3663529.3663798

Efficient code coverage for Android! Our new ANDROLOG tool gets fine-grained coverage from #Android apps, instrumenting up to 98% of recent Android apps. Designed for simplicity, it is available as open source. See our demo at #FSE2024 on Wednesday 16:00-18:00: https://2024.esec-fse.org/details/fse-2024-demonstrations/11/AndroLog-Android-Instrumentation-and-Code-Coverage-Analysis
The paper is also available in the ACM DL: https://dl.acm.org/doi/10.1145/3663529.3663806

On my way to Porto de Galinhas, Brazil, visiting #AIWARE and #FSE 2024: https://conf.researchr.org/home/fse-2024

Learning models from programs! Given a program P, our MODELIZER learns a model M that mocks P's behavior, producing P's output for a given input. But M is also reversible, predicting inputs for which P produces a given output - with up to 95.4% accuracy: https://arxiv.org/abs/2407.08597 🧵

On this day, 50 years ago, as an eight-year old, I was sitting in Beirut with a Russian flight crew watching live how Germany won the 1974 FIFA World Cup Final
https://andreas-zeller.info/2014/07/07/this-day-in-my-history-1974-world-cup.html

Wrote my first #Dockerfile today. Achievement unlocked!
https://github.com/uds-se/fuzzingbook/blob/master/binder/Dockerfile

This allows the readers of @TheFuzzingBook and @TheDebuggingBook to (again) work with #JupyterLab right in their browser, say at https://mybinder.org/v2/gh/uds-se/fuzzingbook/HEAD?labpath=docs%2Fnotebooks/Grammars.ipynb

I am co-founding a new startup! #InputLab creates test data for thousands of formats from electronic invoices to retail orders, covering all input features. We just passed the initial evaluation toward up to 800k€ public funding to start as a #CISPA spin-off in September.

We are #hiring – and we are looking out for #collaboration partners and early #adopters from industry and public service. Check us out at https://inputlab.net! #startup #XML #softwaretesting

Are you attending the Singapore Summer School on Fuzzing? Here's what my students and I have planned for Monday, fitting into more great talks and tutorials by Abhishek Arya, Marcel Böhme, Lim Min Kwang, Mathias Payer, and
Thuan Pham. Details at https://fuzzing.comp.nus.edu.sg