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| dc.contributor.author | Hira Zarif, 01-244151-032 | |
| dc.date.accessioned | 2018-08-29T08:12:28Z | |
| dc.date.available | 2018-08-29T08:12:28Z | |
| dc.date.issued | 2018 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/7384 | |
| dc.description | Supervised by Dr. Tamim Ahmed Khan | en_US |
| dc.description.abstract | Regression testing is most crucial and very expensive to be performed, mostly in time and resource constraint environment ..Thus this research makes use of technique like Test Case Prioritization, to prioritize a subset from the whole test suite, satisfying some predefined criteria. Ant Colony Optimization (ACO) is a technique based on the actual living manner of the ants. This research presents an implementation of the previously introduced Ant Colony Optimization Algorithm for Test Case Prioritization. Experimental representation and example runs explained in this research show how the random nature of ACO helps to find out the promising paths and pick the best from them .Results demonstrate that ACO leads to solutions that are in close familiarity with best solution. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Software Engineering, Bahria University Engineering School Islamabad | en_US |
| dc.relation.ispartofseries | MS SE;T-0747 | |
| dc.subject | Software Engineering | en_US |
| dc.title | Test Case Priortization By Using Ant Colony Optimization (T-0747) (MFN 6892) | en_US |
| dc.type | MS Thesis | en_US |