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solution naive. This is the ability to see and document exactly what is in front of you and turning off the lter that everybody has that allows them to think that they have the solution to the problem when they see something that matches their preconceived expectations. You might be thinking that more than 90 percent of the time when you see a discrepancy, you will be able to recognize it as either a symptom or a cause of the problem, but in my experience, the actual number is much closer to 25 percent. By not looking around naively, you probably will miss the shorted pins, incorrect wiring, or incorrectly typed instructions (i.e., addwf register, w instead of addwf register, f). Being solution na ve is a skill that I ve seen in only one or two people who have truly mastered it over the course of my life. As humans, we tend to remember what we want to do and tend to see that rst and miss what is actually in front of us. In cases where the application starts up and then fails, the importance of keeping notes detailing what has happened is critical. For example, if you had an RS-232 interface that locked up, you would have to gure out if the problem was based on time, data values, or data volume (the number of incoming characters). Once this determination is made, then you can go ahead and look for the problem by simulating the data input and taking advantage of this parameter. In trying to nd a problem, don t be afraid of creating a small application to force the problem. If you can come up with an automated way of causing the error, then you have correctly characterized the situation and can translate this knowledge to a simulator to observe from the software s perspective exactly what is happening within the application code. The goal of characterizing the problem is to document exactly how the circuit is operating and what its inputs are so that you can reproduce these conditions (to make sure that the problem is xed once you have made changes) and work at hypothesizing about what is actually happening. Going back to the example of the leaking basement, both my coworker and I noticed that rainwater collected at the base of the house and did not drain off. For my part, I documented that when the basement started ooding, there was standing water on the outside wall and collecting in the basement window wells. We both called on builders and asked if this was part of the problem. The builders replied that the standing water was a symptom of the weeping tiles and drain pipe not doing the job. This description helped me to create a better document stating what the expected state actually was and describing the difference between the expected state (water falling on this wall would be carried away by the weeping tiles and the drain pipe and not stand in puddles against the wall and in the drain pipe) versus the actual state, which was the standing water.
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Hypothesize and Test Your Hypothesis
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Once you have the expected state documented and your problem characterized, you should be able to make a hypothesis on what causes the problem. This is the most important step because comparing the characterization data you collected against the expected information should point you toward the problem and the potential for a x. Before going on and trying to x the application using the hypothesis, you should try
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to test it out either as a thought experiment or on actual hardware to see if you can reproduce the problem and have it behave exactly as on the failed board. An important part of making your hypothesis is deciding what the problem actually is. When making your hypothesis, you should rst list all the observations that seem to be pertinent to the problem at hand. One of the problems with the YAP-II programmer was that ASCII control characters were being accepted from the command prompt instead of being ignored. To build my hypothesis on what the problem was, I sifted through my notes on the problem (characterization of the problem) comparing them against the expected operation of the programmer and came up with the following observations:
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