Effort estimation can be done, based on different techniques available like Function Point Analysis, COCOMO, Use Case Point Analysis, Test Case Point Analysis, Metrics based.
Effort estimation is basically done any of the above techniques for different test activities like Test Case Preparation, Automation Script Creation and Test Execution.
Metrics based and very commonly used effort estimation procedure in doing effort estimation for Yahoo Mail application.
Identify the requirements (Login Page, Inbox, Compose, Address)
Classify the requirements in different complexity (Simple, Average, High)
Based on the past experience, metrics will be collected on how much time it took to write test case for simple, average and high functionality. Similarly it is collected for other testing activities.
Now multiply your complexity with the time factor which you derived from metrics to calculate the effort.
Don't report the total has your total effort, always use buffer time, it various based on the domain, tool and other factors. Example we use 20% on the previous total. This buffer will save you on risk and other deadline factors
Now add the buffer time and the effort calculated from metrics, and this is the Total effort for the activity.
Test Case Point Analysis: You can use this effort estimation technique for Test Automation and Test Execution.
1. Identify the total number of test cases to be automated or executed.
2. Classify the steps into High, Medium and Low complexity based on the business process it performs.
3. Based on the previous experience (metrics based) on how much time it would take to execute High complexity steps. You can have the average time.
4. Multiply this average time with total number of steps and get the total
5. Add the buffer time with the total to get Final estimation time. This buffer time will vary based on the application, domain and other factors.
Most of these effort estimation techniques use Metrics Based, which you are going to calculate the actual time for all effort and then take the average.
Source: SoftwareQA Blogspot
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