In some recent papers, the weight based statistical bounds have
arguably explained time complexity better than the count based
mathematical bounds. This is definitely true for average case
where for an arbitrary code it is difficult to identify the pivotal
operation or pivotal region in the code for taking the expectation
and/or when the probability distribution, over which expectation
is taken, becomes unrealistic over the problem domain. In worst
case, it can certify whether a mathematical bound is conservative
or not. Here we revisit the results on Bubble sort in sequential
mode and make an independent study of the same algorithm in
parallel mode using statistical bound
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/214089 |
| Date | 15 February 2012 |
| Creators | Panigrahi, Sunil Kumar, Chakraborty, Soubhik, Mishra, Jibitesh |
| Contributors | Dept of Computer Science and Engineering, APEX Institute of Technology & Management, Pahal, Bhubaneswar-752101, Orissa, India |
| Publisher | IJCSN Journal |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Article, Technical Report |
| Relation | IJCSN-2012-1-1-1, http://ijcsn.org/publications.html |
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