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To test a compiler, compile and run the test files The test progralns should in turn generate output, and their results should be compared to known ones To test a numerical program, generate test cases that explore the edges of the algorithm, trivial cases as well as hard ones Where possible, write code that verifies that output properties are sane For example, the output of a numerical integrator can be tested for continuity, and for agreement with closed-form solutions To test a graphics program, it's not enough to see if it can draw a box; instead read the box back from the screen and check that its edges are exactly where they should be If the program has an inverse, check that its application recovers the input Encryption and decryption are inverses so if you encrypt something and can't decrypt it, something is wrong Similarly, lossless compression and expansion algorithms should be inverses Programs that bundle files together should extract them unchanged Sometimes there are multiple methods for inversion: check all combinations
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Verify conservation properties Many programs preserve some property of their inputs Tools like wc (count lines, words, and characters) and sum (compute a checksum) can verify that outputs are of the same size, have the same number of words, contain the same bytes in some order, and the like Other programs compare files for identity (cmp) or report differences ( d i f f ) These programs or similar ones are readily available for most environments, and are well worth acquiring A byte-frequency program can be used to check for conservation of data and also to spot anomalies like non-text characters in supposedly text-only files; here's a version that we call f req:
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# i n c l u d e < s t d i o h> # i n c l u d e <ctype h> # i n c l u d e <li m i t s h>
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unsigned 1ong count [UCHARKMAX+l] ;
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/+ f r e q main: d i s p l a y b y t e frequency counts */
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in t mai n (voi d)
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i n t c; w h i l e ((c = getchar()) count LC]++;
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!= EOF)
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f o r (c = 0 ; c <= UCHAR-MAX; c++) i f (count [c] != 0) p r i n t f ("%2x %c % l u \ n n , c , i s p r i n t ( c ) c : ' - ' countCc1); return 0;
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Conservation properties can be verified within a program too A function that counts the elements in a data structure provides a trivial consistency check A hash
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TESTING
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table should have the property that every element inserted into it can be retrieved This condition is easy to check with a function that dumps the contents of the table into a file or an array At any time, the number of insertions into a data structure minus the number of deletions must equal the number of elements contained, a condition that is easy to verify
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Compare independent implementations Independent implementations of a library or program should produce the same answers For example, two compilers should produce programs that behave the same way on the same machine, at least in most situations Sometimes an answer can be computed in two different ways, or you might be able to write a trivial version of a program to use as a slow but independent comparison If two unrelated programs get the same answers, there is a good chance that they are correct; if they get different answers, at least one is wrong One of the authors once worked with another person on a compiler for a new machine The work of debugging the code generated by the compiler was split: one person wrote the software that encoded instructions for the target machine, and the other wrote the disassembler for the debugger This meant that any error of interpretation or implementation of the instruction set was unlikely to be duplicated between the two components When the compiler miscoded an instruction, the disassembler was sure to notice All the early output of the compiler was run through the disassembler and verified against the compiler's own debugging printouts This strategy worked very well in practice, instantly catching mistakes in both pieces The only difficult, protracted debugging occurred when both people interpreted an ambiguous phrase in the architecture description in the same incorrect way Measure test coverage One goal of testing is to make sure that every statement of a program has been executed sometime during the sequence of tests; testing cannot be considered complete unless every line of the program has been exercised by at least one test Complete coverage is often quite difficult to achieve Even leaving aside "can't happen" statements, it is hard to use normal inputs to force a program to go through particular statements There are commercial tools for measuring coverage Profilers, often included as pan of compiler suites, provide a way to compute a statement frequency count for each program statement that indicates the coverage achieved by specific tests
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We tested the Markov program of 3 with a combination of these techniques The last section of this chapter describes those tests in detail
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Exercise 6-3 Describe how you would test f req Exercise 6-4 Design and implement a version of f r e q that measures the frequencies of other types of data values, such as 32-bit integers or floating-point numbers Can you make one version of the program handle a variety of types elegantly
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