Software Estimation: Demystifying the Black Art by Steve McConnell

By Steve McConnell

The software program is infamous for its bad estimates. For years, Code Complete's Steve McConnell has been attempting to repair that. In software program Estimation, he is introduced jointly all he is realized via educating millions of software program pros and development one of many world's major software program estimation instruments. this is often the definitive therapy: either formal innovations and the most important "rules of thumb.McConnell walks via assets of mistakes, unearths universal estimating pitfalls, and exhibits easy methods to enhance accuracy through the use of numerous the right way to refine your projections. you are going to find out how to "decompose" initiatives into smaller components (for example, modules rather than systems); after which recompose these parts into one coherent estimate.Next, he systematically addresses the demanding situations of estimating venture measurement, attempt, and time table. final yet no longer least, you will find life like counsel on offering estimates to administration, and surviving these inevitable, dreaded negotiations.

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Indeed, within the 10,000 LOC to 100,000 LOC range, the effect is usually not all that dramatic. But two factors make the effect more dramatic. One factor is greater difference in project size, and the other factor is project conditions that degrade productivity more quickly than average as project size increases. Figure 5-4 shows the range of outcomes for projects ranging from 10,000 LOC to 1,000,000 LOC. In addition to the nominal diseconomy, the graph also shows the worst-case diseconomy. 48 Chapter 5: Estimate Influences Chapter 5: Estimate Influences 49 Figure 5-4: Diseconomy of scale for projects with greater size differences and the worst-case diseconomy of scale.

One factor is greater difference in project size, and the other factor is project conditions that degrade productivity more quickly than average as project size increases. Figure 5-4 shows the range of outcomes for projects ranging from 10,000 LOC to 1,000,000 LOC. In addition to the nominal diseconomy, the graph also shows the worst-case diseconomy. 48 Chapter 5: Estimate Influences Chapter 5: Estimate Influences 49 Figure 5-4: Diseconomy of scale for projects with greater size differences and the worst-case diseconomy of scale.

Some of these decisions are about what the project will deliver; some are about what the project will not deliver. If these decisions change later, the Cone will widen. Tip "top" class="admon-body"> Don't assume that the Cone of Uncertainty will narrow itself. You must force the Cone to narrow by removing sources of variability from your project. 34 Chapter 4: Where Does Estimation Error Come From? Chapter 4: Where Does Estimation Error Come From? 35 Accounting for the Cone of Uncertainty in Software Estimates Studies of software estimates have found that estimators who start with single-point estimates and create ranges based on their original single-point numbers do not usually adjust their minimum and maximum values sufficiently to account for the uncertainty in the estimate, especially in circumstances that contain high uncertainty (Jørgensen 2002).

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