Rolling seven dice over and over is how I passed time “playing” D&D. But I also played a game with the dice, one that I introduced in last week’s Lesson. That lesson’s code got things started. This Lesson finishes the project.
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You would think that I’d be deeply into Dungeons and Dragons, but no. I can’t stand the game. I find it tedious and predictable, boring. But I did enjoy rolling all those dice. Who knew that a 20-side die is a thing — and that rolling a “nat 20” is a big deal?
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Continuing my Base 36 series, from last week’s Lesson, the base35_string() function successfully converts a decimal value into its base 36 representation. To verify that the conversion works, another function is necessary to convert base 36 strings into their decimal equivalents.
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The next step in my Base 36 series is to translate a decimal value into its base 36 representation. In last week’s Lesson, code was presented to build a powers table and slice a decimal value into its base 36 components. This Lesson completes the task with a function, base36_sting() to build and output a base 36 value.
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To build a number in base 36, you need to know the powers of base 36. This information is required to output digits — 0 through 9 and then A through Z — in the proper order to represent a base 36 value. This task may seem complicated, but it’s the same process that takes place for any counting base.
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This month’s Exercise output values in various bases, but only those bases from 2 to 10. For other bases, especially those that alien beings might use, more effort is required. Therefore, I’d like to begin exploring a ridiculous counting base, base 36.
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The C11 standard added a few new keywords to the language. These are often called the “underscore keywords” because each is prefixed with an underscore. The second letter is often capitalized, as is the case with _Alignof.
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As you might suspect, searching a binary search tree (BST) involves a recursive function. This function must plow through the tree, finding a value in a specific node. Because the BST is organized, the search process works far more quickly than when the data is unorganized or set in a sequential array. In fact, the bsearch() function uses a similar scheme requiring that the data first be sorted before the function works its magic.
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A binary search tree works best when code is available to search the tree. Before doing so, I’d like to demonstrate how a tree is processed, one node at a time.
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Tree structures are yet another way to organize data. They’re similar to a linked list, but with the data organized by value into a series of branches and leaves. OMG! It’s like a tree!
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