3.4 Statistical Quality Assurance

	Statistical quality assurance reflects a growing trend throughout industry to become more quantitative about
	quality. It implies the following steps:

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, correct the defects.

The Causes of errors are:

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)

3.4 Statistical Quality Assurance

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.

3.4 Statistical Quality Assurance

	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