The technique assumes that you already tested similar applications in previous projects and collected metrics from those projects. Take inputs from subject matter experts who know the application (as well as testing) very well and use the metrics you have collected and arrive at the testing effort.Going into another quarterly planning meeting at work, I realized that I too am working on a long-term project. Building software and building a house aren't all that different – both are long-term projects where multiple teams need to coordinate with one another, and any homeowner will confirm, the project is never done.

validating software estimates-6

M = Most likely estimate (most likely duration and there may be some problem but most of the things will go right).

L = Pessimistic estimate (worst case scenario where everything goes wrong). Step 2 − Calculate unadjusted actor weights as Unadjusted Actor Weights = Total no. Step 4 − Calculate unadjusted use-case weights as Unadjusted Use-Case Weights = Total no.

So how can agile, a method based on frequent, continuous delivery exist with long-term, big-picture planning?

Is it possible to create a realistic forecast over a long period of time, knowing that the one constant is change?

This method speaks more on experience rather than any statistical formula.

This method was popularized by Barry Boehm to emphasize on the group iteration to reach a consensus where the team visualized different aspects of the problems while estimating the test effort.Only in the case of estimation techniques that use WBS, such as Wideband Delphi, Three-point Estimation, PERT, and WBS, you can obtain the values for the estimates of the testing activities.If you have obtained the estimates as Function Points (FP), then as per Caper Jones, Number of Test Cases = (Number of Function Points) × 1.2 Once you have the number of test cases, you can take productivity data from organizational database and arrive at the effort required for testing.When you are estimating a testing project, consider − PERT software testing estimation technique is based on statistical methods in which each testing task is broken down into sub-tasks and then three types of estimation are done on each sub-tasks.The formula used by this technique is − Test Estimate = (O + (4 × M) + E)/6 Where, O = Optimistic estimate (best case scenario in which nothing goes wrong and all conditions are optimal).Step 5 − Review all the testing requirements to make sure they are added in WBS. In Wideband Delphi Method, WBS is distributed to a team comprising of 3-7 members for re-estimating the tasks.