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ERIC Number: ED184562
Record Type: RIE
Publication Date: 1979-Jul
Reference Count: 0
Computer Science and Technology: Modeling and Measurement Techniques for Evaluation of Design Alternatives in the Implementation of Database Management Software. Final Report.
Deutsch, Donald R.
This report describes a research effort that was carried out over a period of several years to develop and demonstrate a methodology for evaluating proposed Database Management System designs. The major proposition addressed by this study is embodied in the thesis statement: Proposed database management system designs can be evaluated best through the integrated use of a limited prototype implementation for the DBMS design, a flexible measurement facility, and a predictive model based on the DBMS prototype. Included in the report are a review of the pertinent literature and related research; an overview of a performance prediction system with three components--a prototype implementation for a positional set processor DBMS, a measurement and analysis system, and a performance prediction model; a description of the DBMS prototype and measurement facility; discussion of the model concepts and parameters; a summary of the mathematical relationships imbedded in the performance prediction model; a review of the model evaluation problem and the status of ongoing verification, validation, and problem analyis activities; and research results and suggested future research directions. Appendices contain scripts demonstrating the set processor DBMS prototype and performance modelers. (Author/RAO)
Descriptors: Computer Science, Databases, Evaluation Methods, Management Systems, Models, Prediction, Systems Analysis, Systems Development
Superintendent of Documents, U.S. Government Printing Office, Washington, DC 20402 (Stock No. 003-003-02088-5, $5.50)
Publication Type: Dissertations/Theses; Reports - Research
Education Level: N/A
Sponsor: National Bureau of Standards (DOC), Washington, DC. Inst. for Computer Sciences and Technology.
Authoring Institution: N/A
Identifiers: Predictive Models
Note: Ph.D. Dissertation, University of Maryland.