Dependency Directed Reasoning for Complex Program Understanding

Item

Title
en_US Dependency Directed Reasoning for Complex Program Understanding
Creator
en_US Shrobe, Howard Elliot
Date
2004-10-20T20:04:41Z
Date Available
2004-10-20T20:04:41Z
Date Issued
en_US 1979-04-01
Identifier
en_US AITR-503
uri
http://hdl.handle.net/1721.1/6890
Abstract
en_US Artificial Intelligence research involves the creation of extremely complex programs which must possess the capability to introspect, learn, and improve their expertise. Any truly intelligent program must be able to create procedures and to modify them as it gathers information from its experience. [Sussman, 1975] produced such a system for a 'mini-world'; but truly intelligent programs must be considerably more complex. A crucial stepping stone in AI research is the development of a system which can understand complex programs well enough to modify them. There is also a complexity barrier in the world of commercial software which is making the cost of software production and maintenance prohibitive. Here too a system which is capable of understanding complex programs is a necessary step. The Programmer's Apprentice Project [Rich and Shrobe, 76] is attempting to develop an interactive programming tool which will help expert programmers deal with the complexity involved in engineering a large software system. This report describes REASON, the deductive component of the programmer's apprentice. REASON is intended to help expert programmers in the process of evolutionary program design. REASON utilizes the engineering techniques of modelling, decomposition, and analysis by inspection to determine how modules interact to achieve the desired overall behavior of a program. REASON coordinates its various sources of knowledge by using a dependency-directed structure which records the justification for each deduction it makes. Once a program has been analyzed these justifications can be summarized into a teleological structure called a plan which helps the system understand the impact of a proposed program modification.
Extent
en_US 293 p.
21640370 bytes
16994996 bytes
Format
application/postscript
application/pdf
Language
en_US
Relation
en_US AITR-503
Item sets
AI Technical Reports (1964 - 2004)