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3. Assign the Logic Flow to Individual Methods and Classes
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Think of an algorithm test as more finely grained than a normal unit test. In fact, it may help to think of algorithm tests as being sub-atomic. Like operating a string puppet, the idea behind algorithm tests is (figuratively speaking) to throw a line around each step in the process, and give it a little tug. It s micro-control, as you want to monitor each state change within the algorithm to ensure that it did what you expected based on the design. As individual functions tend to involve more than one state change, this means that your unit test needs to monitor something smaller than a single function.
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Another way to think of micro-controlling tests is in terms of the bubblegum factory example from 6 (see Figure 6-11). In that example, controllers (software functions) included things like Slice and dice the bubblegum, with gum slabs in and slivers out. An algorithmic design of this picture would set up a slicing loop, with an initial slab size and desired sliver width/number of slivers. The test would then track each individual slicing operation in the loop, in addition to the loop construction, preparation, and finishing up of the output. It turns out that, even though each function in theory just does one thing, that one thing is composed of many, smaller operations. An algorithm test confirms that each of these smaller operations does what it s meant to.
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You may wonder how a unit test can test something smaller than a single function call. Generally a function consists of Input value process Expected result. The test sets up the input value via a test fixture, starts the process by calling the function, and then validates the expected result. The process itself is atomic; so how do you get inside it
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Proving that there s a book available on every subject, see Fuzzing: Brute Force Vulnerability Discovery, and the accompanying web page: http://fuzzing.org/. OWASP also has a page about fuzz testing: www.owasp.org/index.php/Fuzzing.
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CHAPTER 12 UNIT TESTING ALGORITHMS
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There are essentially two ways to get inside an atomic process: Inject a spy object into the object under test Divide the function into yet-smaller functions, and write individual unit tests for each one
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Which method you choose depends on what you want to achieve from the test, of course. If you use a spy object to monitor state changes and report on them afterwards, you re effectively monitoring the overall process from start to end; it s an integration test on a pico scale. Conversely, subdividing the function into smaller functions (like blasting the rocks in a game of Asteroids) means you ll be testing each function separately; each one becomes an isolated unit with its own input value, process, and expected result.
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A SEEMINGLY SIMPLE METHOD MAY NOT BE PROVABLY CORRECT
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Here s a Java method that sums together all the values in an array of integers:
public int sumArray(int... values) { int count = 0; for (int value : values) { count += value; } return count; }
The code s pretty simple: it just loops through the values array, adds each value in turn to a running total, and then returns the result. A normal unit test would pass in an array of values and assert that the result is correct like this:
@Test public void sumArray() { LoopingExample looper = new LoopingExample(); int result = looper.sumArray(2,2); assertEquals(4, result); }
However, how many different sets of arrays would you need to pass in i.e., how many different test case scenarios before you could state with confidence that the function is proven to be mathematically correct At the risk of going all contrived, if the programmer had accidentally made the function multiply each array element with the previous sub-total instead of adding them, passing in {2, 2} would, of course, return 4 in either case; so the previous test would pass either way. A more complex function could have all kinds of traps and special cases that would be missed by a simple set of input scenarios. To be absolutely sure that each part of the algorithm is working as expected, you d need to delve deeper into the function and ensure that each step matches up with the design i.e., that the initialization of count is done as expected; every value in the array is hit during the loop; the addition is done correctly; and the correct variable is returned. In other words, if the overall unit isn t provably correct, then proving that each step in the unit works is another way to exhaustively test it assuming that you trust the overarching algorithm, of course.
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