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23. Debugging
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Formatting, Fred Freeform Fruit-Loop, Frita Goto, Gary Many-Loop, Mavis Modula, Mildred Statement, Sue Switch Whileloop, Wendy
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$5,877 $5,771 $1,666 $8,889 $10,788 $4,000 $7,860
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This successful run supports the hypothesis. To confirm it, you want to try adding a few new employees, one at a time, to see whether they show up in the wrong order and whether the order changes on the second run.
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Locate the Source of the Error
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The goal of simplifying the test case is to make it so simple that changing any aspect of it changes the behavior of the error. Then, by changing the test case carefully and watching the program s behavior under controlled conditions, you can diagnose the problem. Locating the source of the error also calls for using the scientific method. You might suspect that the defect is a result of a specific problem, say an off-by-one error. You could then vary the parameter you suspect is causing the problem one below the boundary, on the boundary, and one above the boundary and determine whether your hypothesis is correct. In the running example, the source of the problem could be an off-by-one defect that occurs when you add one new employee but not when you add two or more. Examining the code, you don t find an obvious off-by-one defect. Resorting to Plan B, you run a test case with a single new employee to see whether that s the problem. You add Hardcase, Henry as a single employee and hypothesize that his record will be out of order. Here s what you find:
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Formatting, Fred Freeform Fruit-Loop, Frita Goto, Gary Hardcase, Henry Many-Loop, Mavis Modula, Mildred Statement, Sue Switch Whileloop, Wendy $5,877 $5,771 $1,666 $493 $8,889 $10,788 $4,000 $7,860
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The line for Hardcase, Henry is exactly where it should be, which means that your first hypothesis is false. The problem isn t caused simply by adding one employee at a time. It s either a more complicated problem or something completely different. Examining the test-run output again, you notice that Fruit-Loop, Frita and Many-Loop, Mavis are the only names containing hyphens. Fruit-Loop was out of order when she was first entered, but Many-Loop wasn t, was she Although
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23. Debugging
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you don t have a printout from the original entry, in the original error Modula, Mildred appeared to be out of order, but she was next to Many-Loop. Maybe Many-Loop was out of order and Modula was all right. You hypothesize: The problem arises from names with hyphens, not names that are entered singly. But how does that account for the fact that the problem shows up only the first time an employee is entered You look at the code and find that two different sorting routines are used. One is used when an employee is entered, and another is used when the data is saved. A closer look at the routine used when an employee is first entered shows that it isn t supposed to sort the data completely. It only puts the data in approximate order to speed up the save routine s sorting. Thus, the problem is that the data is printed before it s sorted. The problem with hyphenated names arises because the rough-sort routine doesn t handle niceties such as punctuation characters. Now, you can refine the hypothesis even further. You hypothesize: Names with punctuation characters aren t sorted correctly until they re saved. You later confirm this hypothesis with additional test cases.
Tips for Finding Defects
Once you ve stabilized an error and refined the test case that produces it, finding its source can be either trivial or challenging, depending on how well you ve written your code. If you re having a hard time finding a defect, it could be because the code isn t well written. You might not want to hear that, but it s true. If you re having trouble, consider these tips:
Use all the data available to make your hypothesis When creating a hypothesis about the source of a defect, account for as much of the data as you can in your hypothesis. In the example, you might have noticed that Fruit-Loop, Frita was out of order and created a hypothesis that names beginning with an F are sorted incorrectly. That s a poor hypothesis because it doesn t account for the fact that Modula, Mildred was out of order or that names are sorted correctly the second time around. If the data doesn t fit the hypothesis, don t discard the data ask why it doesn t fit, and create a new hypothesis.
The second hypothesis in the example, that the problem arises from names with hyphens, not names that are entered singly, didn t seem initially to account for the fact that names were sorted correctly the second time around either. In this case, however, the second hypothesis led to a more refined hypothesis that proved to be correct. It s all right that the hypothesis doesn t account for all of
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