cognitive architectures (cas) are the core of artificial cognitive systems. a ca is supposed to specify the human brain at a level of abstraction suitable for explaining how it achieves the functions of the mind. over the years a number of distinct cas have been proposed by different authors and their limitations and potentials were investigated. these cas are usually classified as symbolic and...

BACKGROUND The format of a mathematics problem often influences students' problem-solving performance. For example, providing diagrams in conjunction with story problems can benefit students' understanding, choice of strategy, and accuracy on story problems. However, it remains unclear whether providing diagrams in conjunction with symbolic equations can benefit problem-solving performance as w...

Automated code generators for finite element local assembly have facilitated exploration of alternative implementation strategies within generated code. However, even for a theoretical performance indicator such as operation count, an optimal strategy for local assembly is unknown. We explore a code generation strategy based on symbolic integration and polynomial common sub-expression eliminati...

This thesis aims to address a number of program reasoning problems faced every day by programmers, using the technique of symbolic execution. Symbolic execution has the advantage of avoiding "infeasible" paths in the program (paths that cannot be exercised for any input), exploring which could provide spurious information about the program and mislead the programmer. However, as symbolic execut...

Recently symbolic execution (SE) [15] has been successfully proven to be an alternative to CEGAR for program verification offering the following benefits among others [12, 18]: (1) it does not explore infeasible paths avoiding expensive refinements, (2) it avoids expensive predicate image computations (e.g., Cartesian and Boolean abstractions [2]), and (3) it can recover from too-specific abstr...