An Experiment in Software Error Data Collection and Analysis
Abstract
The propensity to make programming errors and the rates
of error detection and correction are dependent on program complexity.
Knowledge of these relationships can be used to avoid errorprone
structures in software design and to devise a testing strategy
which is based on anticipated difficulty of error detection and correction.
An experiment in software error data collection and analysis was
conducted in order to study these relationships under conditions where
the error data could be carefully defined and collected. Several complexity
measures which can be defined in terms of the directed graph
representation of a program, such as cyclomatic number, were analyzed
with respect to the following error characteristics: errors found, time
between error detections, and error correction time. Signifiant relationships
were found between complexity measures and error charateristics.
The meaning of directed grph structural properties in terms of
the complexity of the programming and testing tasks was examined.
Description
Includes a correction to the previous article published.
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.Collections
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