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Analyzing the State Behavior of Programs
(MIT Artificial Intelligence Laboratory, 1988-08)
It is generally agreed that the unrestricted use of state can make a program hard to understand, hard to compile, and hard to execute, and that these difficulties increase in the presence of parallel hardware. This problem ...
Parallel Flow Graph Matching for Automated Program Recognition
(MIT Artificial Intelligence Laboratory, 1988-07)
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 ...
Support for Obviously Synchonizable Series Expressions in Pascal
(MIT Artificial Intelligence Laboratory, 1988-11)
Obviously synchronizable series expressions enable programmers to write algorithms as straightforward compositions of functions rather than as less comprehensible loops while retaining the significantly higher efficiency ...
A Counterexample to the Theory that Vision Recovers Three-Dimensional Scenes
(MIT Artificial Intelligence Laboratory, 1988-11)
The problem of three-dimensional vision is generally formulated as the problem of recovering the three-dimensional scene that caused the image. Here we present a certain line-drawing and show that it has the following ...
How to do Research At the MIT AI Lab
(MIT Artificial Intelligence Laboratory, 1988-10)
This document presumptuously purports to explain how to do research. We give heuristics that may be useful in pickup up specific skills needed for research (reading, writing, programming) and for understanding and enjoying ...
Program Improvement by Automatic Redistribution of Intermediate Results
(MIT Artificial Intelligence Laboratory, 1988-05)
The problem of automatically improving the performance of computer programs has many facets. A common source of program inefficiency is the use of abstraction techniques in program design: general tools used in a specific ...
A Proposal For An Intelligent Debugging Assistant
(MIT Artificial Intelligence Laboratory, 1988-01)
There are many ways to find bugs in programs. For example, observed input and output values can be compared to predicted values. An execution trace can be examined to locate errors in control flow. The utility of these and ...
The Novice's Guide to the UNIX at the AI Laboratory Version 1.0
(MIT Artificial Intelligence Laboratory, 1988-05)
This is a manual for complete beginners. It requires little knowledge of the MIT computer systems, and assumes no knowledge of the UNIX operating system. This guide will show you how to log onto the AI Lab's SUN system ...
Spurious Behaviors in Qualitative Prediction
(MIT Artificial Intelligence Laboratory, 1988-03)
I examine the scope and causes of the spurious behavior problem in two widely different approaches to qualitative prediction, Sacks' PLR and Kuipers' QSIM. QSIM's proliferation of spurious behaviors and PLR's limited ...
The New Idiot's Guide to OZ
(MIT Artificial Intelligence Laboratory, 1988-02)
This is a manual for complete beginners. It assumes no knowledge of the MIT computer systems. This guide will teach you how to log onto the computer called OZ, a DEC PDP-20 computer running the TWENEX (TOPS-20) operating ...