Accession Number : ADA115501

Title :   Software Quality Metrics: A Software Management Monitoring Method for Air Force Logistics Command in Its Software Quality Assurance Program for the Quantitative Assessment of the System Development Life Cycle under Configuration Management.

Descriptive Note : Master's thesis,


Personal Author(s) : Jarzombek,Stanley J , Jr

PDF Url : ADA115501

Report Date : Mar 1982

Pagination or Media Count : 327

Abstract : Software Quality Assurance (SQA) is recognized as an essential function needed to monitor the software system development life cycle (SDLC). The framework established for Software Quality Metrics (SQM) provides goal-directed system specifications and the ability to quantitatively assess the quality of the system under development. The Automated Measurement Tool (AMT), which operationalizes the application of SQM, functions as the core of a Decision Support System, providing quantitative measures and various levels of reports. A literature survey of SQA aids enabled the recommendation of a minimum set of tools and techniques to be used by the SQA program for monitoring the SDLC, which has been envisioned as an iterative process controlled by management. Recognizing the functional impact of specific information as the key to objectively monitoring and controlling the software system development, the decision-making model was conceptualized as three subsystems within each phase of the SDLC: scanning (afferent), organizing (intelligence), and decision (efferent). The use of checklists by system developers highlights a prescriptive method of goal-directed development. The thesis provides justification for using SQM by reviewing the need and demonstrating how the concepts can now be used. (Author)

Descriptors :   *Computer programs, *Quality assurance, *Systems analysis, *Configuration management, *Management planning and control, Systems engineering, Life cycles, Management information systems, Automation, Measurement, Logistics planning, Decision making, Test methods, Quantitative analysis, Theses

Subject Categories : Administration and Management
      Computer Programming and Software
      Mfg & Industrial Eng & Control of Product Sys

Distribution Statement : APPROVED FOR PUBLIC RELEASE