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The function is receiving a single parameter, which is the value of our local variable As you would expect, the parameter is passed using the evaluation stack One thing that s worth mentioning is that the code is passing an integer to this function, which prints text If you look at the line from where this call is made, you will see the following: void [mscorlib]System Console::WriteLine(int32) This is the prototype of the specific function being called Notice that the parameter it takes is an int32, not a string as you would expect Like many other functions in the class library, WriteLine is overloaded and has quite a few different versions that can take strings, integers, floats, and so on In this particular case, the version being called is the int32 version just as in C++, the automated selection of the correct overloaded version was done by the compiler.

After calling WriteLine, the routine again loads two values onto the stack: the local variable and the constant 1 This is followed by an invocation of the add instruction, which adds two values from the evaluation stack and writes the result back into it So, the code is adding 1 to the local variable and saving the result back into it (in line IL_000d) This brings you back to IL_000e, which is where you left off before when you started looking at this loop Clearly, this is a very simple routine All it does is loop between IL_0004 and IL_0011 and print the current value of the counter It will stop once the counter value is greater than 10 (remember the conditional branch from lines IL_000e through IL_0011) Not very challenging, but it certainly demonstrates a little bit about how IL works..

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One reason, presumably, is that the more detailed the event tree is, the less extreme the conditional probabilities which need to be estimated Both event trees and fault trees require a strict structuring of a problem into sequences This is what allows probabilities to be decomposed into manageable pieces and provides the accounting scheme by which those probabilities are put together In the process of decomposing a problem, however, it is sometimes convenient to start not with highly structured event or fault trees, but with an in uence diagram An in uence diagram is a graphical device for exploring the interrelationships of events, processes, and uncertainties Once the in uence diagram has been constructed, it can be readily transformed into event or fault trees Stedinger et al (1996) show how in uence diagrams can be used in assessing hydrologic risks of dam projects..

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Decomposition of a probability estimation problem relies on disaggregating failure sequences into component parts. Usually, these are the smallest sized pieces that can be de ned realistically and analyzed using available models and procedures. Decomposition can be used for any failure mode that is reasonably well understood. Clearly, decomposition cannot be used for failure modes for which mechanistic understanding is lacking. Internal erosion leading to piping is arguably one such, poorly understood failure mode. In most cases, the extent of decomposition, that is the size of the individual events into which a failure sequence is divided, is a decision left to the panel of experts. Most real problems can be analyzed at different levels of disaggregation. Considerations in arriving at an appropriate level of disaggregation include the availability of data pertinent to the components, the availability of models or analytical techniques for the components, the extent of intuitive familiarity experts have for the components, and the magnitude of probabilities associated with the components. Typically, best practice dictates disaggregating a failure sequence to the greatest degree possible, subject to the constraint of being able to assign probabilities to the individual components. Usually, it is a good practice to

Before proceeding to examine obfuscated IL code, let us proceed to another, slightly more complicated sample. This one (like pretty much every .NET program you ll ever meet) actually uses a few objects, so it s a more relevant example of what a real program might look like. Let s start by disassembling this program s Main entry point, printed in Listing 12.2.

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