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To be fair, after making this declaration, I did present some information on how to develop stimulus les successfully and what to look for; but I think the information was pretty sketchy, and I think that I could have done better explaining how to nd and x application problems.

You will nd that following the steps and procedures I layout for you in this chapter will allow you to x problems faster than if you just look for the rst problem and try to nail it. This will seem like a paradox because I will be pushing for you to characterize and understand exactly what is happening and what the symptoms are telling you. With this information and hypothesizing on what the defect is, you will nd that you will understand exactly what is happening and why your x should eliminate the problem. Thus, instead of blindly going ahead and simulating the application in a three-step process, I will present to you the following failure analysis process to understand, nd, correct, and release xes to problems in your application:

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Visuals grab attention immediately. The audience silently ask themselves, What s that Why is it there And if you ve chosen a great prop, they ll remember it for a long time. When computer paper came in long sheets separated by perforations, I saw a speaker begin her talk on interviewing techniques by talking about how much information was available on the topic. She told us she had printed out only the most appropriate information she found on interviewing. To make her point, she held up the rst sheet of the ream of paper on the oor beside her and began walking around the stage. She created a huge paper trail that visually made her point. If she were to do that talk today, she could start by sharing the number of hits she got on Google. Since Google returns about 3,470,000 hits for interviewing techniques, she could use a jar of something small like gumballs or dried beans to represent the number of hits. That would certainly create a visual impact.

Document the expected state. Characterize the problem. Hypothesize about what the cause of the problem is. Propose corrective actions. Test different xes. Release the corrective action.

This process is not limited to PIC software or hardware. It works very well for all problems that you may encounter in your everyday life. A few years ago a coworker and I had similar problems with our 50-year-old houses when rain hit the side of our houses, our basements would start to ood. My coworker has spent $30,000 on the problem so far and still has problems, whereas I followed the process outlined in this chapter and spent less than $1,500 right at the beginning to x the problem and haven t had a problem since.

Engineers and programmers have one thing in common: They re both lousy at documenting their work. There are many reasons for this de ciency, including the schedule doesn t allow for the time to be taken during the development process to document the project, the design isn t nished and the documentation won t be accurate for the nal version so there s no reason to bother, it s somebody else s responsibility, or the plain truth, it s boring and generally unrewarding to do. This means that chances are that nobody has spelled out exactly what the system is supposed to do. Not having a good description of what the system is supposed to do (its expected state) makes it virtually impossible to x the problem. I would argue that you can t claim to have a problem if you can t point to a document that states how the application is supposed to work and be able to explain how the actual application deviates from its expected, documented operation. This step probably will seem redundant or even trivial; for example, you might have a situation where your application catches on re it will seem unnecessary to document that it should not burst into ames. However, documenting the expected operation and state of the application will provide you with the

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