Talk:All-pairs testing

message: In one of the courses I have attended, someone argued that instead of running the all-pair combinations, one can run same number of combinations, with random values out of the vectors, and gain ~90% coverage in relation to all-pair coverage.
Should one really define pairs for testing if that is true ?
It might be easier to execute O(nm) random cases, or if we would like to improve coverage, then O(nm) x 2.
Should this be indicated in the all-pair term ?
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The suggestion that there is little benefit from pairwise test cases compared with randomly generated cases seems to come from one example in Bach and Schroeder's, “Pairwise Testing: A Best Practice that Isn’t.” 
http://www.testingeducation.org/wtst5/PairwisePNSQC2004.pdf
See also the notes for slides #35-36 from Sherwood's review "Pairwise Testing Comes of Age."
http://testcover.com/pub/background/stareast2008.ppt
"In this example the pairwise test cases cover 100% of the required pairs. The authors observe that an equal number of random tests cover 88% of the pairs; therefore the pairwise tests aren’t much better. But in the same example it takes more than twice as many random test cases to cover all the pairs. If we’re trying to generate a small set of covering test cases, there is no real choice here."
"In all the comparisons I’ve seen between pairwise and random generators, the pairwise tools are more efficient. That is, they produce smaller sets of covering test cases."
"In some of the comparisons, there also seems to be an implicit assumption that the pairwise tests are representative of the technique generally. We just saw a list of 25 tools. The same web page presents a table showing differences in the numbers of test cases they generate. There is variation here, and perhaps more importantly, there are possible improvements, ..."
The tools list referenced above is at Czerwonka's Pairwise.org site:
http://www.pairwise.org/tools.asp
Improvements in reducing the number of pairwise test cases are discussed later in Sherwood's review. See also Colbourn's list of best known pairwise templates (covering arrays for t=2).
http://www.public.asu.edu/~ccolbou/src/tabby/catable.html
Whether it is easier to generate pairwise or random test cases is dependent on the generator tool of course. In both techniques, an analysis of the system and its operational states is required. Pairwise testing can provide better coverage of pairs with far fewer test cases. Random test cases make sense for stability testing or load testing, when more test cases may be desirable.
Bookworm271 (talk) 17:47, 22 August 2008 (UTC)
thread_title:  Replacing All-Pairs with Random Values ? 

message: The text is difficult to understand.
Can we avoid words which are not in common use? 
E.g. predicate. The entry for predicate is itself confusing, so pointing to it does not help.
W102102 (talk) 08:01, 13 May 2022 (UTC)
thread_title:  Simplify text 

message: The second paragraph of the introduction contains a link to a paid online course on Udemy, a website which IMO employs highly scammy marketing strategies. I'm not sure if Wikipedia should link to such sites in the article itself, but I'm not too familiar with the rules for this, maybe someone who is can take a look. 195.176.112.243 (talk) 11:46, 14 August 2023 (UTC)
thread_title:  Remove link to Udemy course