Title page for ETD etd-342321132974710

Type of Document

Dissertation

Author

Day II, Henry Jesse

Author's Email Address

HankDay@coastalnet.com

URN

etd-342321132974710

Title

AN INVESTIGATION OF SOFTWARE METRICS AFFECT ON COBOL PROGRAM RELIABILITY

Degree

PhD

Department

Accounting (Academic)

Advisory Committee

Advisor Name	Title
James O. Hicks	Committee Chair
Kai S. Koong	none
Robert M. Brown	none
Tarun K. Sen	none
Wayne E. Leininger	none

Keywords

reliability
metrics
COBOL

Date of Defense

1996-06-20

Availability

unrestricted

Abstract

The purpose of this research was to predict a

COBOL program's reliability from software

characteristics that are found in the program's source

code. The first step was to select factors based on the

human information processing model that are

associated with changes in computer program

reliability. Then these factors (software metrics) were

quantitatively studied to determine which factors affect

COBOL program reliability. Then a statistical model

was developed that predicts COBOL program

reliability. Reliability was selected because the

reliability of computer programs can be used by

systems professionals and auditors to make decisions.

Using the Human Information Processing Model to

study the act of creating a computer program, several

hypotheses were derived about program

characteristics and reliability. These hypotheses were

categorized as size, structure, and temporal

hypotheses. These characteristics were then used to

test several prediction models for the reliability of

COBOL programs. Program characteristics were

measured by a program called METRICS.

METRICS was written by the author using the Pascal

programming language. It accepts COBOL programs

as input and produces as output seventeen measures

of complexity. Actual programs and related data were

then gathered from a large insurance company over

the course of one year. The data were used to test the

hypotheses and to find a model for predicting the

reliability of COBOL programs. The operational

definition for reliability was the probability of a

program executing without abending. The size of a

program, its cyclomatic complexity, and the number of

times a program has been executed were used to

predict reliability. A regression model was developed

that predicted the reliability of a COBOL program

from a program's characteristics. The model had a

prediction error of 9.3%, a R2 of 15%, and an

adjusted R2 of 13%. The most important thing

learned from the research is that increasing the size of

a program's modules, not the total size of a program,

is associated with decreased reliability.

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