Automated Validation of Large-scale Software Systems (SMU)


More information here

This talk will present an overview of our research on automated software validation (SV), i.e., methods/tools to support developers during software testing and debugging activities. The talk will present our application of input grammars for testing (a) the correctness of traditional software systems (e.g., compilers/interpreters like Mozilla Rhino and Google’s Closure) and (b) the fairness properties of Machine Learning based systems (e.g., NLP systems like Google BERT, StanfordNLP and AllenNLP). Finally, the talk will outline our ongoing work on building intelligent (or data-centric) SV methods, human-in-the-loop SV methods, and SV methods for interdisciplinary software systems.