An Experiment in Software Error Data Collection and Analysis

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Authors
Schneidewind, N.F.
Hoffmann, Heinz-Michael
Subjects
Abstract data types
clusters for the implementation of data abstraction
dependency among clusters
dialogues
efficient code for very high level languages
programming languages
programming methodology
set languages
very high level languages
Advisors
Date of Issue
1979-05
Date
May 1979
Publisher
IEEE
Language
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.
Type
Article
Description
Includes a correction to the previous article published.
Series/Report No
Department
Organization
Identifiers
NPS Report Number
Sponsors
Funder
This research was supported in part by the Naval Air Development Center, Warminster, PA.
Format
Citation
IEEE Transactions on Software Engineering, Vol. SE-5, No. 3, May 1979.
Distribution Statement
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.
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