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| Annex 1 | |||
| 5.9.2.2 Model of Error Seeding |
Modell der Fehlereinstreuung
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1 Identification/Definition of the Method
/Dunn, 1984/
2 Brief Characteristic of the Method
In the model of Error Seeding, a predefined number of artificially generated errors is "sown" in the program code. After that, test runs are used to detect the errors and to examine the ratio between actual and artificial errors based on the total number of detected errors. Naturally, the artificially generated errors are not known to the testers. In a first approach, the number of undetected errors can be estimated as follows:
FU = FG · (FE / FEG)
| where | FU | = number of undetected errors |
| FG | = number of not seeded errors detected | |
| FE | = number of seeded errors | |
| FEG | = number of seeded errors detected |
3 Literature
| /Dunn, 1984/ | description of the model |
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| /Goel, 1985/ | brief description of the model |
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