Recently, Static Single Assignment Form and Sparse Evaluation Graphs have been advanced for the efficient solution of program optimization problems. Each method is provided with an initial set of flow graph nodes that inherently affect a problem\u27s solution. Other relevant nodes are those where potentially disparate solutions must combine. Previously, these so-called {phi}-nodes were found by computing the iterated dominance frontiers of the initial set of nodes, a process that could take worst case quadratic time with respect to the input flow graph. In this paper we present an almost-linear algorithm for detemining exactly the same set of {phi}-nodes
Data-flow analysis computes its solutions over the paths in a control-flow graph. These paths---whet...
In this paper we analyze the complexity of algorithms for two problems that arise in automatic test ...
International audienceWe consider supervised learning problems where the features are embedded in a ...
Compiler optimizations need precise and scalable analyses to discover program properties. We propose...
The Maximum Concurrent Flow Problem (MCFP) is a polynomially bounded problem that has been used over...
AbstractThe sparse evaluation graph has emerged over the past several years as an intermediate repre...
This paper looks at several methods for solving network flow problems. The first chapter gives a bri...
Program analysis plays a major role in advanced compilers, yet traditional approaches to data flow a...
The computation of dominators in a flowgraph has applications in several areas, including program op...
In this thesis, a number of optimization problems are presented from algorithmic graph theory. This ...
We consider supervised learning problems where the features are embedded in a graph, such as gene ex...
© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Many large-scale and safety critical systems can be modeled as flow networks. Traditional approaches...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
AbstractThe “profitability” of code optimizations is defined in terms of a Markov model of program f...
Data-flow analysis computes its solutions over the paths in a control-flow graph. These paths---whet...
In this paper we analyze the complexity of algorithms for two problems that arise in automatic test ...
International audienceWe consider supervised learning problems where the features are embedded in a ...
Compiler optimizations need precise and scalable analyses to discover program properties. We propose...
The Maximum Concurrent Flow Problem (MCFP) is a polynomially bounded problem that has been used over...
AbstractThe sparse evaluation graph has emerged over the past several years as an intermediate repre...
This paper looks at several methods for solving network flow problems. The first chapter gives a bri...
Program analysis plays a major role in advanced compilers, yet traditional approaches to data flow a...
The computation of dominators in a flowgraph has applications in several areas, including program op...
In this thesis, a number of optimization problems are presented from algorithmic graph theory. This ...
We consider supervised learning problems where the features are embedded in a graph, such as gene ex...
© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Many large-scale and safety critical systems can be modeled as flow networks. Traditional approaches...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
AbstractThe “profitability” of code optimizations is defined in terms of a Markov model of program f...
Data-flow analysis computes its solutions over the paths in a control-flow graph. These paths---whet...
In this paper we analyze the complexity of algorithms for two problems that arise in automatic test ...
International audienceWe consider supervised learning problems where the features are embedded in a ...