A Study of Software Metrics
Gurdev Singh, Dilbag Singh, Vikram Singh · 2011
Poor size estimation is one of the main reasons major software-intensive acquisition programs ultimately fail. Size is the critical factor in determining cost, schedule, and effort. The failure to accurately predict (usually too small) results in budget overruns and late deliveries which undermine confidence and erode support for your program. Size estimation is a complicated activity, the results of which must be constantly updated with actual counts throughout the life cycle. Size measures include source lines-of-code, function points, and feature points. Complexity is a function of size, which greatly impacts design errors and latent defects, ultimately resulting in quality problems, cost overruns, and schedule slips. Complexity must be continuously measured, tracked, and controlled. Another factor leading to size estimate inaccuracies is requirements creep which also must be baseline and diligently controlled. Software metrics measure different aspects of software complexity and therefore play an important role in analyzing and improving software quality. Pervious research has indicated that they provide useful information on external quality aspects of software such as its maintainability, reusability and reliability. Software metrics provide a mean of estimating the efforts needed for testing. Software metrics are often categorized into products and process metrics.