Graduate Thesis Or Dissertation
 

Generalizing abstractions in form-based visual programming languages : from direct manipulation to static representation

Public Deposited

Contenu téléchargeable

Télécharger le fichier PDF
https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/sx61dp556

Descriptions

Attribute NameValues
Creator
Abstract
  • We believe concreteness, direct manipulation and responsiveness in a visual programming language increase its usefulness. However, these characteristics present a challenge in generalizing programs for reuse, especially when concrete examples are used as one way of achieving concreteness. In this thesis, we present a technique to solve this problem by deriving generality automatically through the analysis of logical relationships among concrete program entities from the perspective of a particular computational goal. Use of this technique allows a fully general form-based program with reusable abstractions to be derived from one that was specified in terms of concrete examples and direct manipulation. Also addressed in this thesis is how to statically represent the generalized programs. In general, we address how to design better static representations. A weakness of many interactive visual programming languages is their static representations. Lack of an adequate static representation places a heavy cognitive burden on a VPL's programmers, because they must remember potentially long dynamic sequences of screen displays in order to understand a previously-written program. However, although this problem is widely acknowledged, research on how to design better static representations for interactive VPLs is still in its infancy. Building upon the cognitive dimensions developed for programming languages by cognitive psychologists Green and others, we have developed a set of concrete benchmarks for VPL designers to use when designing new static representations. These benchmarks provide design-time information that can be used to improve a VPL's static representation.
Resource Type
Date Available
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Academic Affiliation
Non-Academic Affiliation
Subject
Déclaration de droits
Publisher
Peer Reviewed
Language
Digitization Specifications
  • File scanned at 300 ppi (Monochrome, 256 Grayscale) using Capture Perfect 3.0 on a Canon DR-9050C in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
Replaces

Des relations

Parents:

This work has no parents.

Dans Collection:

Articles

La vignette Titre Date de téléchargement Visibilité actes
file details YangSherry1997.pdf 2017-08-03 Public Télécharger