There are no easy answers to any of these questions and we can not and should not make up numbers out of thin air (although I have seen some do just that). Primarily, there are two ways to do estimates.

Estimating the estimates: This approach of doing estimate is merely a speculation or taking a guess. It is not to say that these are wild guesses. On the contrary, this are rather informed guesses and the information comes from previous projects. Thus, estimates are done using the previous projects as a baseline. One can argue that this makes it a valid estimate. There is some truth to this argument and besides estimates are not meant to be concrete. But if the purpose of doing estimates is to come as close as possible to an absolute, then there is a chance that this approach will fall short. If estimated numbers are far a part from the actual numbers, then we are probably not doing a good job on our estimates and as a result we will be writing too few or too many test cases than we should. In order to take the guessing out of estimates, we do need to create some kind of documents which will help us to do a better estimate where estimated numbers will reflect the actual numbers (within an acceptable difference). A difference of up to 5 to 10 percent may be considered acceptable.

Documenting the estimates: The discussion of documenting the process of doing estimates will lead us to create some simple metrics which are easy to use. I have discussed one such metric in my previous article (A discussion on process, metrics, automation & outsourcing) some time ago. I needed to have some kind of measuring unit which would tell me the depth and breadth of my test coverage in detail. With that in mind I had created a metric which looks something like this (after some minor changes).

This metric serves two purposes. First, it describes all the possible test scenarios and thus put the focus on test coverage and second, the document also serves as a guide to do an estimate on how many test cases we need to write for these user stories. It is always a good idea to have a quick review of this document to see if we are duplicating or missing a test scenario. It is also possible that we may want to combine two or more test scenarios into one test case and thus changing the number of test cases we need to write. For example, in case of the last user story (3.1.3.1.3), we may want to have a Data Driven Test case (DDT) where all the test scenarios are listed in a spreadsheet and thus making it one test case instead of eleven. This metric is fairly easy to create, easy to follow and easy to maintain.

In addition, we may also want to use the following metric to identify the regression test cases associated withthese user stories. This metric is not driven by user stories or requirements as it is the case for the previous metric. Here the layout is completely different and focus is on different controls (Buttons, edit fields, combobox, spin control etc.). Below is the example of an estimate for the same user stories.

Here the total number of estimated test cases is 34 and it includes the regression test cases. Since one of the user stories (3.1.3.1.3: Line Number edit field only accepts numeric ) has to do with the changes made in "Go to Line" dialog, it is crucial that we run all other test cases (GUI and functional) associated with the dialog and this metric allows us to identify those test cases. The important thing to remember is that these metrics are dynamic, meaning changes can be made as needed. For example, if new controls are introduced (i.e. scroll bars, check boxes etc), we can add them to the list. Once these metrics are in place, doing an estimate comes to be a simple matter of plugging the numbers in the appropriate columns. With such ease of use of these metrics, there is no reason for the trajectory of doing an estimate should include any speculation.