Speculative optimizers of modern compilers are designed on techniques for probabilistic static analyses of programs. For imperative and object-oriented multi-core programs, this paper focuses on the problem of revealing probabilistic dangling references. This important problem is treated in this paper via type systems. Besides being simply structured, the type systems provide suitable frameworks for proof-carrying code applications. One class of such applications is that ofmobile codes having limited resources.Using the proposed technique, each analysis case is supported by a correctness proof in the form of a type derivation. Most important concurrent constructs such as fork-join constructs, conditionally spawned cores, and parallel loops ...
Abstract- A compile-time analysis technique is developed to derive the probability with which a user...
The major specific contributions are: (1) We introduce a new compiler analysis to identify the memor...
We study the semantic foundation of expressive probabilistic programming languages, that support hig...
Forward inference techniques such as sequential Monte Carlo and particle Markov chain Monte Carlo fo...
A multitude of different probabilistic programming languages exists to-day, all extending a traditio...
Pointer analysis is a critical compiler analysis used to disambiguate the indirect memory ref-erence...
A multitude of different probabilistic programming languages exists today, all extending a tradition...
Abstraction is a fundamental tool for reasoning about a complex system. Program abstraction has been...
We present a formal framework for syntax directed probabilistic program analysis. Our focus is on pr...
This paper presents a new approach for optimizing multitheaded programs with pointer constructs. The...
AbstractThis paper presents a new approach for optimizing multitheaded programs with pointer constru...
[[abstract]]Speculative multithreading (SpMT) architecture can exploit thread-level parallelism that...
We present a semantics-based technique for analysing probabilistic properties of imperative programs...
AbstractWe present a semantics-based technique for analysing probabilistic properties of imperative ...
interpretation, Prolog, Parallelism This work presents a type inference system aimed at the parallel...
Abstract- A compile-time analysis technique is developed to derive the probability with which a user...
The major specific contributions are: (1) We introduce a new compiler analysis to identify the memor...
We study the semantic foundation of expressive probabilistic programming languages, that support hig...
Forward inference techniques such as sequential Monte Carlo and particle Markov chain Monte Carlo fo...
A multitude of different probabilistic programming languages exists to-day, all extending a traditio...
Pointer analysis is a critical compiler analysis used to disambiguate the indirect memory ref-erence...
A multitude of different probabilistic programming languages exists today, all extending a tradition...
Abstraction is a fundamental tool for reasoning about a complex system. Program abstraction has been...
We present a formal framework for syntax directed probabilistic program analysis. Our focus is on pr...
This paper presents a new approach for optimizing multitheaded programs with pointer constructs. The...
AbstractThis paper presents a new approach for optimizing multitheaded programs with pointer constru...
[[abstract]]Speculative multithreading (SpMT) architecture can exploit thread-level parallelism that...
We present a semantics-based technique for analysing probabilistic properties of imperative programs...
AbstractWe present a semantics-based technique for analysing probabilistic properties of imperative ...
interpretation, Prolog, Parallelism This work presents a type inference system aimed at the parallel...
Abstract- A compile-time analysis technique is developed to derive the probability with which a user...
The major specific contributions are: (1) We introduce a new compiler analysis to identify the memor...
We study the semantic foundation of expressive probabilistic programming languages, that support hig...