Open Access
Parallel Flow Graph Matching for Automated Program Recognition
Patrick M. Ritto
- 01 Jul 1988
TL;DR: A flow graph matching algorithm has been implemented on the Connection Machine which employs parallel techniques to allow efficient subgraph matching to be performed in polynomial time.
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Abstract: A flow graph matching algorithm has been implemented on the Connection Machine which employs parallel techniques to allow efficient subgraph matching. By constructing many different matchings in parallel, the algorithm is able to perform subgraph matching in polynomial time in the size of the graphs. The automated program recognition system can use this algorithm to help make a more efficient flow graph parser. The process of automated program recognition involves recognizing familiar data structures and algorithmic fragments (called cliches) in a program so that a hierarchical description of the program can be constructed. The recognition is done by representing the program as a flow graph and parsing it with a graph grammar which encodes the clich6s. In order to find clich6s in the midst of unfamiliar code, it is necessary to run the parser on all possible subgraphs of the graph, thus starting the parser an exponential number of times. This is too inefficient for practical use on large programs, so this algorithm has been implemented to allow the matchings to be performed in polynomial time.
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Citations
Automated program recognition: a feasibility demonstration
TL;DR: A prototype recognition system which demonstrates the feasibility of automating program recognition, and is built on two previous advances: a graphical, programming-language-independent representation for programs, called the Plan Calculus, and an efficient graph parsing algorithm.
142
Patent
Computer network management
Michael Mead
- 17 Oct 2007
TL;DR: In this article, a method of identifying components of a computer infrastructure, comprising building a graph-based model of at least a part of the computer infrastructure and determining the presence within the built graph of a predetermined subgraph, and where it is so determined identifying the sub-graph within a built graph.
6
Determining the Limits of Automated Program Recognition
Linda M. Wills
- 01 Jun 1989
TL;DR: This work will build an experimental system that performs recognition on realistic programs on the order of thousands of lines and formally analyze the complexity of the recognition process, to help determine how guidance can be applied most profitably to improve the efficiency of program recognition.
3
References
Automated program recognition: a feasibility demonstration
TL;DR: A prototype recognition system which demonstrates the feasibility of automating program recognition, and is built on two previous advances: a graphical, programming-language-independent representation for programs, called the Plan Calculus, and an efficient graph parsing algorithm.
142
Parallel Algorithms for Computer Vision on the Connection Machine
James J. Little
- 01 Nov 1986
TL;DR: The Connection Machine is a fine-grained parallel computer having up to 64K processors that supports both local communication among the processors, which are situated in a two-dimensional mesh, and high-bandwidth communication among processors at arbitrary locations, using a message- passing network.
62
The Programmer''s Apprentice Project: A Research Overview
Charles Rich,Richard C. Waters +1 more
- 01 Nov 1987
TL;DR: The goal of the Programmer''s Apprentice project is to develop a theory of how expert programmers analyze, synthesize, modify, explain, specify, verify, and document programs.
18
Inspection Methods in Programming: Cliches and Plans
Charles Rich
- 01 Dec 1987
TL;DR: A formalism, called the Plan Calculus, is defined and used to represent programming cliches in a convenient, canonical, and programming-language independent fashion.
17
•Book
The Connection Machine
W. Daniel Hillis
- 01 Jan 1985
TL;DR: The Connection Machine describes a fundamentally different kind of computer that Daniel Hillis and others are now developing to perform tasks that no conventional, sequential machine can solve in a reasonable time.