Author Type

Graduate Student

Date of Award

1996

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Khoshgoftaar, Taghi M.

Abstract

Software systems that control military radar systems must be highly reliable. A fault can compromise safety and security, and even cause death of military personnel. In this experiment we identify fault-prone software modules in a subsystem of a military radar system called the Joint Surveillance Target Attack Radar System, JSTARS. An earlier version was used in Operation Desert Storm to monitor ground movement. Product metrics were collected for different iterations of an operational prototype of the subsystem over a period of approximately three years. We used these metrics to train a decision tree model and to fit a discriminant model to classify each module as fault-prone or not fault-prone. The algorithm used to generate the decision tree model was TREEDISC, developed by the SAS Institute. The decision tree model is compared to the discriminant model.

Extent

70 p.

Comments

College of Engineering and Computer Science|FAU Electronic Theses and Dissertations Collection|Thesis (M.S.)--Florida Atlantic University, 1996.|College of Engineering and Computer Science

Identifier

FADT15315

Format

pdf

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