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The Software Error Estimation Program (SWEEP), developed by the Software Productivity Consortium, is a predictive tool for calculating the error rate, including estimating the percentage of hidden errors. A hidden error is any error that remains in the program product, i.e. such an error that exists, but not yet detected. The value of the SWEEP model is that it simplifies the management and forecasting of errors in software intensive systems. This model supports the definition of error detection targets during software development and helps to track progress towards achieving these goals. By predicting the number of errors remaining in the software system, SWEEP monitors and helps to control the quality of software products. Below is a list of assumptions underlying the model:


  • All detected errors must be recorded at the time of their detection.
  • Errors are corrected after they are detected, and new errors are not introduced during the elimination of detected (reported) errors.
  • Error tracing must be performed uniformly throughout all phases of the life cycle.
  • Documentation errors should be monitored separately from program errors.
  • The input data of the SWEEP program should be regularly checked and updated.
  • The accuracy of SWEEP results will increase in proportion to the actual number of errors encountered at other stages of the development process.


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Familiarization with the three modes of using the SWEEP program


  1. Time-based model allows you to evaluate and track errors during system and complex testing phases.
  2. Stage-based model allows you to predict and track errors in several stages and can provide information about errors before executing any code.
  3. Planning support model allows the user to determine the objectives of detecting errors in a software project based on the experience of previous projects. Then, based on previously collected data, the model generates a bug detection profile that helps to achieve the stated goals.


SWEEP offers software testers a clear graphical representation of the detected errors and the forecast of the remaining errors.


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