Performance Ripple Effect Analysis for Large-Scale Software Maintenance.

Abstract

This report analyzes the possible ripple effect of software modifications during the maintenance phase on the performance of the system, and leads to the development of a maintenance technique for predicting which performance requirements in the system may be affected by a proposed modification. This report formalizes the technique outlined in our previous report entitled, Performance Considerations in the Maintenance Phase of Large-Scale Software Systems. This technique enables maintenance personnel to incorporate performance considerations in their criteria for selecting the types and locations of software modifications to be made. After the maintenance changes have been implemented, this technique can also be useful to the retesting effort of the system by identifying which performance requirements must be reverified to insure that they have not been violated by the maintenance activity. This technique is applicable to all types of large-scale software systems possessing performance requirements, including multiprocessing systems. In the development of this technique, mechanisms for the propagation of performance changes from one part of the system to another are identified. Performance attributes and critical software sections are also identified.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1980
Accession Number
ADA084351

Entities

People

  • James S. Collofello
  • Stephen Sik-Sang Yau

Organizations

  • Northwestern University

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Command And Control
  • Computations
  • Computer Programming
  • Computer Programs
  • Computers
  • Databases
  • Engineering
  • Engineers
  • Estimators
  • Figure Of Merit
  • Life Cycle Costs
  • Life Cycles
  • Maintenance Costs
  • Maintenance Personnel
  • New York
  • Software Development
  • Test And Evaluation

Fields of Study

  • Computer science
  • Engineering

Readers

  • Instructional Design and Training Evaluation.
  • Parallel and Distributed Computing.
  • Software Engineering