Proceedings of the 2011 SIGPLAN/SIGBED conference on Languages, compilers and tools for embedded systems
Symbolic system synthesis in the presence of stringent real-time constraints
Proceedings of the 48th Design Automation Conference
Information Processing Letters
Active learning of combinatorial features for interactive optimization
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
Capturing performance assumptions using stochastic performance logic
ICPE '12 Proceedings of the 3rd ACM/SPEC International Conference on Performance Engineering
Verification conditions for source-level imperative programs
Computer Science Review
Integration of SMT-solvers in B and Event-B development environments
Science of Computer Programming
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Satisfiability Modulo Theories (SMT) is about checking the satisfiability of logical formulas over one or more theories. The problem draws on a combination of some of the most fundamental areas in computer science. It combines the problem of Boolean satisfiability with domains, such as, those studied in convex optimization and term-manipulating symbolic systems. It also draws on the most prolific problems in the past century of symbolic logic: the decision problem, completeness and incompleteness of logical theories, and finally complexity theory. The problem of modularly combining special purpose algorithms for each domain is as deep and intriguing as finding new algorithms that work particularly well in the context of a combination. SMT also enjoys a very useful role in software engineering. Modern software, hardware analysis and model-based tools are increasingly complex and multi-faceted software systems. However, at their core is invariably a component using symbolic logic for describing states and transformations between them. A well tuned SMT solver that takes into account the state-of-the-art breakthroughs usually scales orders of magnitude beyond custom ad-hoc solvers.