Software Metrics: A Guide to Planning, Analysis, and ApplicationCRC Press, 2003. gada 26. sept. - 312 lappuses The modern field of software metrics emerged from the computer modeling and "statistical thinking" services of the 1980s. As the field evolved, metrics programs were integrated with project management, and metrics grew to be a major tool in the managerial decision-making process of software companies. Now practitioners in the software industry have |
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1.–5. rezultāts no 21.
ix. lappuse
... Defect Correlation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 Application 4: Causal Analysis ... Defect Discovery Economics . . . . . . . . 140 Reliability Hinterland ...
... Defect Correlation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128 Application 4: Causal Analysis ... Defect Discovery Economics . . . . . . . . 140 Reliability Hinterland ...
xii. lappuse
... Defects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 Process Defects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 Defect Classification . . . . . . . . . . . .
... Defects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 Process Defects. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 Defect Classification . . . . . . . . . . . .
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42. lappuse
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78. lappuse
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Software Metrics: A Guide to Planning, Analysis, and Application C. Ravindranath Pandian Priekšskatījums nav pieejams - 2003 |
Bieži izmantoti vārdi un frāzes
analysis application approach areas benefits better build calibration centers collection complex control chart correlation cost create curve cycle database decision defect defined density depends distribution effectiveness effort effort variance elements engineering Equation errors estimation estimation model example experience expressed factors fixing forecasting frequency function given goals graph human illustrated implementation improvement indicates influence integration knowledge known limits mapping maturity mean measurement ment methods metrics data metrics system natural nonlinear organization patterns percent performance phase planning plot possible practical prediction presented problem productivity project management regression relationship reliability represent requirements Review risk rules scale schedule shown in Exhibit shows Sigma simple standard statistical structure Test tion tracking trend types variable variance variation visual