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Wednesday, September 23, 2009

Statistical Quality Assurance - Overview

Statistical quality assurance reflects a growing trend throughout industry to become more quantitative about quality. And what does Statistical quality assurance means. Well, those big word imply the following series of steps steps that form the process:

- Information about software defects is collected and categorized.
- An attempt is made to trace each defect to its underlying cause.
- Using the Pareto principle (80 percent of the defects can be traced to 20 percent,
and isolate the 20 percent).
- Once the vital few causes have been identified, the defects are corrected.

Causes of errors:
- incomplete or erroneous specification (IES).
- misinterpretation of customer communication (MCC).
- intentional deviation from specification (IDS).
- violation of programming standards (VPS).
- error in data representation (EDR).
- inconsistent module interface (IMI).
- error in design logic (EDL).
- incomplete or erroneous testing (IET).
- inaccurate or incomplete documentation (IID).
- error in programming language translation of design (PLT).
- ambiguous or inconsistent human-computer interface (HCI).
- miscellaneous (MIS).

In conjunction with the collection of defect information, software developers can calculate an error index (EI) for each major step in the software engineering process. After analysis, design, coding, testing, and release, the following data are collected:
Ei = the total no. of errors uncovered during the ith step in the process.
Si = the no. of serious errors.
Mi = the no. of moderate errors.
Ti = the no. of minor errors.
PS = the size of the product at the ith step.
At each step in the software engineering process, a phase index (PI i ) is computed:
PI i = ws (Si/Ei) + wm(Mi/Ei) + wt(Ti/Ei)
Error index (EI) can be computed as follows:
EI = (PI 1 + 2 PI 2 + 3 PI 3 + iPI I)/PS

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