Computers are getting faster and faster; the operating systems are getting more sophisticated. Often, these improvements necessitate that we migrate the existing software to the new platform. In the ideal world, the migrated software should run perfectly well on a new platform; however, in reality, when we try that, thousands of errors appear, errors that need correcting. As a result, software migration is usually a very time-consuming process. A natural way to speed up this process is to take into account that errors naturally fall into different categories, and often, a common correction can be applied to all error from a given category. To efficiently use this idea, it is desirable to estimate the number of errors of different type. In this paper, we show how imprecise expert knowledge about such errors can be used to produce very realistic estimates.