Developing Software Size Estimating Relationships Based on Functional Descriptions of the Software.

Abstract

This thesis researched the ability to develop regression models to predict the number of source lines of code (LOC) based on functional descriptions of the software. LOC, a major cost driver in currently available software cost estimating models, has been consistently underestimated, thus lowering not only the software cost estimate but also the total cost estimate of the weapon system. Six software sizing data bases containing various functional variables were used. The variable included complexity, reliability, experience level of programmers, etc. For each data base, regression analysis was performed to derive the optimal model to predict LOC. Of the five data base containing complexity, it was statistically significant in three. The best developed model was for Armament Division's airborne computer programs. The correlation coefficient sq R was .6583 for the two variables in model. These were; (1) the system for which the program was developed and (2) the reliability needed in the program. The initial research has been accomplished, but more data and further research is needed.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1986
Accession Number
ADA174335

Entities

People

  • Mark J. Whetstone

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Engineered Resilient Systems
  • Materials and Manufacturing Processes
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Application Software
  • Business Administration
  • Computer Languages
  • Computer Programming
  • Computer Programs
  • Computers
  • Cost Analysis
  • Cost Estimates
  • Data Analysis
  • Data Science
  • Databases
  • Information Science
  • Language
  • Regression Analysis
  • Software Development
  • Statistical Analysis

Fields of Study

  • Computer science
  • Engineering

Readers

  • Computer Science/Computer Engineering/Data Science/Digital Signal Processing.
  • Life Cycle Cost Analysis