STATISTICAL QUALITY ASSURANCE

Software quality can be achieved through competent analysis, design, coding, and testing, as well as through the application of formal technical reviews, a testing strategy, better control of software work products and the changes made to them, and the application of accepted software engineering standards. In addition, quality can be defined in terms of a broad array of quality factors and measured (indirectly) using a variety of indices and metrics.

A syntax and semantics can be defined for every programming language, and work is underway to develop a similarly rigorous approach to the specification of software requirements. If the requirements model (specification) and the programming language can be represented in a rigorous manner, it should be possible to apply mathematic proof of correctness to demonstrate that a program conforms exactly to its specifications.

Steps required to perform statistical SQA :

1. Information about software defects is collected and categorized.

2. An attempt is made to trace each defect to its underlying cause (e.g., non-conformance to specifications, design error, violation of standards, poor communication with the customer).

3. Using the Pareto principle (80 percent of the defects can be traced to 20 percent of all possible causes), isolate the 20 percent (the "vital few").

4. Once the vital few causes have been identified, move to correct the problems that have caused the defects.

This relatively simple concept represents an important step towards the creation o: an adaptive software engineering process in which changes are made to improve those elements of the process that introduce error.

Statistical quality assurance techniques for software have been shown to provide substantial quality improvement . In some cases, software organizations have achieved a 50 percent reduction per year in defects after applying these techniques

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