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

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/sx61dp556

Descriptions

Attribute NameValues
Creator
Abstract or Summary
  • 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 Copyright
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Academic Affiliation
Non-Academic Affiliation
Subject
Rights Statement
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
Additional Information
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2012-10-12T18:51:18Z (GMT) No. of bitstreams: 1 YangSherry1997.pdf: 15495013 bytes, checksum: f8524f6d4f80d961077a254574776d33 (MD5)
  • description.provenance : Made available in DSpace on 2012-10-12T18:51:18Z (GMT). No. of bitstreams: 1 YangSherry1997.pdf: 15495013 bytes, checksum: f8524f6d4f80d961077a254574776d33 (MD5) Previous issue date: 1996-11-04
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2012-10-12T16:56:50Z (GMT) No. of bitstreams: 1 YangSherry1997.pdf: 15495013 bytes, checksum: f8524f6d4f80d961077a254574776d33 (MD5)
  • description.provenance : Submitted by Kirsten Clark (kcscannerosu@gmail.com) on 2012-10-10T22:02:02Z No. of bitstreams: 1 YangSherry1997.pdf: 15495013 bytes, checksum: f8524f6d4f80d961077a254574776d33 (MD5)

Relationships

Parents:

This work has no parents.

Last modified

Downloadable Content

Download PDF

Items