Model based test case prioritization using UML behavioural diagrams and association rule mining.

Autor: Mahali, Prateeva, Mohapatra, Durga Prasad
Zdroj: International Journal of Systems Assurance Engineering & Management; Oct2018, Vol. 9 Issue 5, p1063-1079, 17p
Abstrakt: In software development life cycle, maximum effort is spent on the maintenance phase. This is due to the retesting carried out in this phase to ensure that any moderation made to the system under test (SUT) does not hamper the unchanged components of the SUT. This retesting is a part of regression testing which is performed in the maintenance phase. But in the retesting approach, all the old test cases are re-executed which leads to increase in cost and time of testing. So, test case prioritization technique is widely used to overcome this problem i.e. to keep the testing cost and time down. Test case prioritization techniques schedule the test cases for regression testing in an order that improves rate of fault detection, coverage percentage etc. To improve the fault detection rate, we propose an approach for prioritizing the test cases by using multiple modified functions and association rule mining. Since, we are doing model based testing, UML (Unified Modelling Language) behavioural diagrams such as activity diagram and sequence diagram are used to model the system. An activity sequence graph (ASG) is generated taking into account the combined features of activity diagram and sequence diagram. Then, test scenarios are generated by traversing the graph. The affected nodes and corresponding modified nodes are found out using forward slicing algorithm. The details of modified nodes and corresponding affected nodes are stored in a project repository. Then, association rule mining (ARM) is applied to the historical data to generate the frequent pattern. Finally, test cases are prioritized based on business criticality test value (BCTV) and frequent pattern. We have also verified the effectiveness of proposed approach by determining the percentage of fault detection. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index