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Part of the reason for these seemingly low productivity figures is that industry average numbers like these factor non-programmer time into the lines-of-codeper-day figure. Tester time, project manager time, and administrative support time are all included. Non-coding activities like requirements development and architecture work are also typically factored into those lines-of-code-per-day figures. But none of that is what takes up so much time. The single biggest activity on most projects is debugging and correcting code that doesn t work properly. Debugging and associated rework consume about 50 percent of the time on a traditional, naive software-development cycle. (See Section 3.1 for more details.) Reducing debugging by preventing errors improves productivity. Therefore, the most obvious method of shortening a development

Karen Morton is an Oracle performance optimization specialist with nearly 20 years experience working with the Oracle database. She works with companies around the world teaching application optimization in both classroom settings and shoulder-to-shoulder consulting engagements. She is a frequent speaker at conferences and user groups, an Oracle ACE, and a member of the OakTable network. She blogs at http://karenmorton.blogspot.com.

schedule is to improve the quality of the product and decrease the amount of time spent debugging and reworking the software. This analysis is confirmed by field data. In a review of 50 development projects involving over 400 work-years of effort and almost 3 million lines of code, a study at NASA s Software Engineering Laboratory found that increased quality assurance was associated with decreased error rate but no increase or decrease in overall development cost (Card 1987). A study at IBM produced similar findings: Software projects with the lowest levels of defects had the shortest development schedules and the highest development productivity. ...Software defect removal is actually the most expensive and time-consuming form of work for software (Jones 2000). The same effect holds true on a smaller scale. In a 1985 study, 166 professional programmers wrote programs from the same specification. The resulting programs averaged 220 lines of code and a little under five hours to write. The fascinating result was that programmers who took the median time to complete their programs produced programs with the greatest number of errors. The programmers who took more or less than the median time produced programs with significantly fewer errors (DeMarco and Lister 1985). Figure 20-2 graphs the results:

Now that you have chosen a story thread to help new information pass through the eye of the needle, you can increase the ef ciency of working memory by introducing a pattern for the story to follow. You can do this by adding a motif, or recurring theme, to the rst ve slides. A motif is one of the most powerful techniques you can apply to your presentations. It carries your ideas all the way through your story in a coherent way and adds color and interest to your language. It also makes the job of searching for graphics to add to your slides signi cantly easier because you can map the motif to your visuals. A motif might seem like a nice-to-have addition to make the presentation colorful and interesting, but research shows that it can provide much more than just a pretty face to your presentation. Working memory cannot possibly process all of the new information it experiences, and without a clear structure to organize the new information, it has to create a structure from scratch a very inef cient process. But with a structure that works, you can help working memory select, organize, and integrate the new information much more effectively. The structures that happen to work best are ones the audience already holds in long-term memory they might take the form of a familiar metaphor, an organizing system like 1-2-3, or any number of familiar story themes. See Also For more information about metaphor and its impact on the way people think, see George Lakoff s work, including Metaphors We Live By, 2nd ed. (with Mark Johnson; University of Chicago Press, 2002).

Figure 20-2 Neither the fastest nor the slowest development approach produces the software with the most defects.