How Time-Fault Ratio helps in Test Case Prioritization for Regression Testing

Regression testing analyzes whether the maintenance of the software has adversely affected its normal functioning. Regression testing is generally performed under the strict time constraints. Due to limited time budget, it is not possible to test the software with all available test cases. Thus, the reordering of the test cases, on the basis of their effectiveness, is always needed. A test prioritization technique, which prioritizes the test cases on the basis of their Time -Fault Ratio (TFR), has been proposed in this paper. The technique tends to maximize the fault detection as the faults are exposed in the ascending order of their detection times. The proposed technique may be used at any stage of software development

Mining of Emerging Pattern: Discovering Frequent itemsets in a Stock Data 1 2

Data mining is the process of finding valid, useful and understandable pattern in data. Due to the large size of databases, importance of information stored, and valuable information obtained, finding hidden patterns in data has become increasingly significant. Stock data mining plays an important role to visualize the behavior of financial market. Association rule mining algorithms can be used to discover all item associations (or rules) in a dataset that satisfy user-specified constraints, i.e. minimum support and minimum confidence. Since only one minimum support is used for the whole database, it is implicitly assumed that all items are of the same nature and / or have similar frequencies in the data. Patterns are evaluated by means of generating itemsets using a predefined support and association rules with a higher confidence level. The pattern generated by the frequent itemset of size three is found to be same as being reflected by means of obtained association rules. The pattern so generated helps investors to build their portfolio and use these patterns to learn more about investment planning and financial marke