This paper introduces an analysis technique, commutativity analysis, for automatically parallelizing computations that manipulate dynamic, pointer-based data structures. Commutati...
Analysis of dynamic data structure usage is useful for both program understanding and for improving the accuracy of other program analyses. Static analysis techniques, however, su...
Dynamic data distributions offer a number of performance benefits, but require more sophisticated compiler support and incur run-time overhead. We investigate attainable benefits ...
The aim of binding-time analysis is to determine when variables, expressions, statements, etc. in a program can be evaluated by classifying these into static (compile-time) and dy...
In the past years, the theory and practice of machine learning and data mining have been focused on static and finite data sets from where learning algorithms generate a static m...