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The most interesting fact that this data reveals is that the modal rates don t rise above 75 percent for any single technique, and the techniques average about 40 percent. Moreover, for the most common kind of defect detection, unit testing, the modal rate is only 30 percent. The typical organization uses a test-heavy defect-removal approach, and achieves only about 85% defect removal efficiency. Leading organizations use a wider variety of techniques and achieve defect removal efficiencies of 95 percent or higher (Jones 2000). The strong implication is that if project developers are striving for a higher defect-detection rate, they need to use a combination of techniques. A classic study by Glenford Myers confirmed this implication (Myers 1978b). Myers studied a group of programmers with a minimum of 7 and an average of 11 years of professional experience. Using a program with 15 known errors, he had each programmer look for errors using one of these techniques: Execution testing against the specification Execution testing against the specification with the source code Walkthrough/inspection using the specification and the source code

Myers found a huge variation in the number of defects detected in the program, ranging from 1.0 to 9.0 defects found. The average number found was 5.1, or about a third of those known. When used individually, no method had a statistically significant advantage over any of the others. The variety of errors people found was so great, however, that

Several researchers have tried to classify errors by type and determine the extent to which each kind of error occurs. Every programmer has a list of errors that have been particularly troublesome: off-by-one errors, forgetting to reinitialize a loop variable, and so on. The checklists presented throughout the book provide more details. Boris Beizer combined data from several studies, arriving at an exceptionally detailed error taxonomy (Beizer 1990). Following is a summary of his results:

Creating a View from a Query............................................................................................................... 267 Getting Information About Views from the Data Dictionary .................................................................. 269 Replacing and Dropping Views............................................................................................................. 271

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25.18% 22.44% 16.19% 9.88% 8.98% Structural Data Functionality as implemented Construction Integration

For a list of all the checklists in 3 the book, see the list of 4 checklists following the table 5 of contents.

10.3 What Can You Do with Views ...............................................................................271

With BBP, you can make maximum use of a Tablet PC by writing directly on the screen to increase engagement and dialog, as shown in Figure 3-21. s 7, 8, and 9 will show you a range of ways to sketch and use graphics to prompt interaction using a Tablet PC.

8.12% 2.76% 1.74% 4.71%

Unspecified Beizer reported his results to a precise two decimal places, but the research into error types has generally been inconclusive. Different studies report wildly different kinds of errors, and studies that report on similar kinds of errors arrive at wildly different results, results that differ by 50% rather than by hundredths of a percentage point.

Simplifying Data Retrieval .................................................................................................................... 271 Maintaining Logical Data Independence .............................................................................................. 273 Implementing Data Security ................................................................................................................. 274

Your visually engaging BBP slides are a great t with online meeting tools such as Microsoft Of ce Live Meeting, as shown in Figure 3-22. Because the slides are designed to be visually simple, they increase the need for people to pay attention to your voice on the other end of the telephone or computer speakers.

Given the wide variations in reports, combining results from multiple studies as Beizer has done probably doesn t produce meaningful data. But even if the data isn t conclusive, some of it is suggestive. Here are some of the suggestions that can be derived from it:

The scope of most errors is fairly limited One study found that 85% of errors could be corrected without modifying more than one routine (Endres 1975). Many errors are outside the domain of construction Researchers conducting a series of 97 interviews found that the three most common sources of errors were thin application-domain knowledge, fluctuating and conflicting requirements, and communication and coordination breakdown (Curtis, Krasner, and Iscoe 1988).

10.4 Data Manipulation via Views .................................................................................274

If you see hoof prints, think horses not zebras. The OS is probably not broken. And the database is probably just fine. Andy Hunt and Dave Thomas

3