Prediction = Power

An argument is made that predictive metrics provide a very powerful means for organizations to assess characteristics of their software systems and allow them to make critical decisions based on the value computed. Five different predictors are discussed aimed at different stages of the software lifecycle ranging from a metric that is based on an architecture review which is done at the earliest stages of development, before even low-level design has begun, to one designed to predict the risk of releasing a system in its current form. Other predictors discussed include the identification of characteristics of files that are likely to be particularly fault-prone, a metric to help a tester charged with regression testing to determine whether or not a particular selective regression testing algorithm is likely to be cost effective to run on a given software system and test suite, and a metric to help determine whether a system is likely to be able to handle a significantly increased workload while maintaining acceptable performance levels.