An Experiment in Software Error Data Collection and Analysis
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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.
Includes a correction to the previous article published.
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Schneidewind, Norman F. (1979-08);Several research studies have shown a strong relationship between complexity, as measured by the structural properties of a program, and its error properties, as measured by number and types of errors and error detection ...
Schneidewind, Norman F.; Green, Thomas F. (1975);The relationship between computer program complexity and error detection capability is investigated by representing a program as a directed graph and simulating the detection and correction of errors. Variables of interest ...
Schneidewind, N.F. (1979);The history of developing and using a simulation model for the study of software error processes, complexity and structure is traced. Strong and weak points of simulation as they relate to model validity, accuracy and ...