Explain statistical methods for software metric estimation and evaluation

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Software metrics are treaded as part of an engineering discipline – metrics should be evaluated to determine whether they measure what they purpose to measure prior to use them. There are fours metrics methodologies that have been validation analyses performance on specific metrics or metric system.

Among these validations are the following: Function points are derived using an empirical relationship based on countable (direct) measures of software information domain and assessments of soft ware complexity. The function interpreted to be probability that a defect is de tected by time y. R (y) is the probability that is no failure during the time interval of length of y, where R (y) = 1-F (y) [2]. Halstead uses the primitive measure to de velop expressions for the overall program length; potential minimum volume for an algorithm; the actual volume (number of bits required to specify); the program level (a measure of software complexity); language level (a constant for a given language); and other features such as development effort, development time, and even the projected number of faults in the software. Evaluation of metrics against syn tactic complexity is properties.

Software measurements have the following characteristics:

It has mathematically defined criteria, which can be applied to measure software quality.

The criteria are: consistency, association, discriminative power and Tracking .

It is developed from the point of view of the metric user who has requirements for as sessing, controlling, and predicting quality.

It defines a metrics validation process that integrates quality factor, metric, and functions .