Understanding Simple Picture Programs

Item

Title
en_US Understanding Simple Picture Programs
Creator
en_US Goldstein, Ira P.
Date
2004-10-20T20:04:57Z
Date Available
2004-10-20T20:04:57Z
Date Issued
en_US 1974-04-01
Identifier
en_US AITR-294
uri
http://hdl.handle.net/1721.1/6893
Abstract
en_US What are the characteristics of the process by which an intent is transformed into a plan and then a program? How is a program debugged? This paper analyzes these questions in the context of understanding simple turtle programs. To understand and debug a program, a description of its intent is required. For turtle programs, this is a model of the desired geometric picture. a picture language is provided for this purpose. Annotation is necessary for documenting the performance of a program in such a way that the system can examine the procedures behavior as well as consider hypothetical lines of development due to tentative debugging edits. A descriptive framework representing both causality and teleology is developed. To understand the relation between program and model, the plan must be known. The plan is a description of the methodology for accomplishing the model. Concepts are explicated for translating the global intent of a declarative model into the local imperative code of a program. Given the plan, model and program, the system can interpret the picture and recognize inconsistencies. The description of the discrepancies between the picture actually produced by the program and the intended scene is the input to a debugging system. Repair of the program is based on a combination of general debugging techniques and specific fixing knowledge associated with the geometric model primitives. In both the plan and repairing the bugs, the system exhibits an interesting style of analysis. It is capable of debugging itself and reformulating its analysis of a plan or bug in response to self-criticism. In this fashion, it can qualitatively reformulate its theory of the program or error to account for surprises or anomalies.
Extent
en_US 228 p.
19954783 bytes
15704356 bytes
Format
application/postscript
application/pdf
Language
en_US
Relation
en_US AITR-294
Item sets
AI Technical Reports (1964 - 2004)