Dealing with Uncertainty in Software Systems

David S. Rosenblum
Provost's Chair Professor of Computer Science at the National University of Singapore (NUS)

Date: Tuesday 23rd July
Location: T3-013, Lero, Tierney Building, UL
Time: 14:30 pm


A key challenge in modern-day software development is dealing with the high degree of uncertainty in both the environment in which software operates and in the intended function of the software itself. This uncertainty is exacerbated by the increasing use of machine learning, deep learning, and other ochastic and approximate computational techniques in software systems, which cause the systems to produce behaviors that may be undesirable but nevertheless are not bugs in the traditional software engineering sense. An example of such behavior is a recommender system that produces an unsuitable recommendation to a user; the user may not like the recommendation, but a bad recommendation is not necessarily evidence of a fault in the system implementation. In this talk I will present two works from my own research on dealing with uncertainty. First, I will describe research involving the application of perturbation theory for dealing with uncertain probability parameters used in stochastic models for probabilistic verification. Second, I will describe research involving the application of data fuzzing for evaluating the robustness of recommender algorithms.

About The  Speaker

David S. Rosenblum is Provost's Chair Professor of Computer Science at the National University of Singapore (NUS). He received his Ph.D. from Stanford University and joined NUS in April 2011 after holding positions as Member of the Technical Staff at AT&T Bell Laboratories (Murray Hill); Associate Professor at the University of California, Irvine; Principal Architect and Chief Technology Officer of PreCache (a technology startup funded by Sony Music); and Professor of Software Systems at University College London. David's research interests span many problems in software engineering, distributed systems and ubiquitous computing, and his current research focuses on probabilistic verification, uncertainty in software testing, and machine learning. He is a Fellow of the ACM and IEEE. He recently completed service as Editor-in-Chief of the ACM Transactions on Software Engineering and Methodology (ACM TOSEM), and he was previously Chair of the ACM Special Interest Group in Software Engineering (ACM SIGSOFT). He has received two "test-of-time" awards for his research papers, including the ICSE 2002 Most Influential Paper Award for his ICSE 1992 paper on assertion checking, and the inaugural ACM SIGSOFT Impact Paper Award in 2008 for his ESEC/FSE 1997 on Internet-scale event observation and notification (co-authored with Alexander L. Wolf). He also received the ACM SIGSOFT Distinguished Service Award in 2018.