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the tuple is a text description of what the flag does. This will be printed to the console in the case of a mistake in the command-line arguments. It also serves as a useful note to the programmer. The Arg module exposes two functions for parsing arguments: parse, which parses the command passed in on the command line, and parse_argv, which requires the arguments to be passed directly to it. Both should be passed a list of type argspec describing the commandline arguments expected, a function that will be passed all the command-line arguments not prefixed with -, and finally a string to describe the usage. The module also exposes a third function usage, which can be passed a list of type argspec and will just directly write out the usage. The following example demonstrates an argument parser built in this manner. The parameters collected from the command line are stored in identifiers for later use, in this case being written to the console. #light let let let let let myFlag = ref true myString = ref "" myInt = ref 0 myFloat = ref 0.0 (myStringList : string list ref) = ref []

humans and the coders think it s more technology. It s one of those things where, in the end, fraud is so nondeterministic that you need a human or a quantum computer to look at it and sort of make a final decision, because, in the end, it s people s money. You don t really want some computer saying, $2.00 for you, nothing for you. You need a human with a brain to say, Hmm. This looks like fraud, but I really don t think it is. Then there are various processes and exception handling where you say, Even though it s fraud, you don t handle it because . . . We got really good at it later on. Initially, we sorted things by loss, but then we started sorting things by expected loss. We d estimate the probability of losses programmatically, and then we d get the amount of money in question calculated, figure out the expected loss, and then sort the cases for the investigators by expected loss. The investigators would only have to deal with the top 5 percent. You d never go through the entire queue of things for them to judge, but, because they judge things pretty quickly, they would go through half the queue, and they would inevitably start with the ones we thought were the highest possible loss. So, the highest probable, the highest possible. That was one of the techniques that we used to guide development.

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Livingston: Were any of your competitors doing anything similar Levchin: We kept the stuff under wraps for a very long time. We never really

let argList = [ ("-set", Arg.Set myFlag, "Sets the value myFlag"); ("-clear", Arg.Clear myFlag, "Clears the value myFlag"); ("-str_val", Arg.String(fun x -> myString := x), "Sets the value myString"); ("-int_val", Arg.Int(fun x -> myInt := x), "Sets the value myInt"); ("-float_val", Arg.Float(fun x -> myFloat := x), "Sets the value myFloat"); ] if Sys.argv.Length <> 1 then Arg.parse argList (fun x -> myStringList := x :: !myStringList) "Arg module demo" else Arg.usage argList "Arg module demo" exit 1 printfn "myFlag: %b" !myFlag printfn "myString: %s" !myString printfn "myInt: %i" !myInt printfn "myFloat: %f" !myFloat printfn "myStringList: " print_any !myStringList

showed IGOR to anyone. We never talked about it in the press. I was definitely very paranoid. Initially, when we built it, we had a conference room where there was the IGOR terminal, and people would go in there, use it, and leave. There were no other copies available. Eventually, various federal and state authorities wanted to use it too, because they started to see that we were getting pretty good at this stuff. We would invite them in, and they would have to go into the room and use it and leave. They couldn t take it with them, couldn t print.

As many of you already know, it is quite possible that you will be integrating data from a variety of sources, and some of those sources may not have adopted XML as their data structure. Perhaps their system was designed and implemented prior to the XML revolution. Regardless of the reason, it may fall to you to import their data on their terms and structure. One common format that we all find ourselves dealing with is the flat file. Flat files come in all shapes and flavors: comma-separated, tab-delimited, pipe-separated, or just plain-old text in a single string. The list of available file construction methods can go on for quite some time. Fortunately with BizTalk, we have the tools to fight the madness. The Flat File Schema Wizard allows you to virtually dissect the incoming file and end with a manageable schema that is quick and easy to validate.

Livingston: Did you patent this technique Levchin: I didn t really want to patent it because, for one, I don t like software

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