Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
Stochastic optimization problems provide a means to model uncertainty in the input data where the uncertainty is modeled by a probability distribution over the possible realizatio...
We present a possible world semantics for a call-by-value higherorder programming language with impredicative polymorphism, general references, and recursive types. The model is o...
Two decades ago, Megiddo and Dyer showed that linear programming in two and three dimensions (and subsequently any constant number of dimensions) can be solved in linear time. In ...
We report on GADGET, a new software test generation system that uses combinatorial optimization to obtain condition/decision coverage of C/C++ programs. The GADGET system is fully...