A methodology for test suit reduction in user-session-based testing
Y Huang, L Lu - 2010 IEEE Fifth International Conference on …, 2010 - ieeexplore.ieee.org
Y Huang, L Lu
2010 IEEE Fifth International Conference on Bio-Inspired Computing …, 2010•ieeexplore.ieee.orgUser-session-based testing that leverages user session data to generate a test suite seems
to be a promising technique for testing Web applications. Before this technique can be put
into practice, we must develop methods to manage the collected user session data. In this
paper, we propose a methodology based on a user session and service profile matrix to
generate a reduced user session set. We first collect user sessions from log files and
construct a service profile of the application. Then, we build the relational matrix between …
to be a promising technique for testing Web applications. Before this technique can be put
into practice, we must develop methods to manage the collected user session data. In this
paper, we propose a methodology based on a user session and service profile matrix to
generate a reduced user session set. We first collect user sessions from log files and
construct a service profile of the application. Then, we build the relational matrix between …
User-session-based testing that leverages user session data to generate a test suite seems to be a promising technique for testing Web applications. Before this technique can be put into practice, we must develop methods to manage the collected user session data. In this paper, we propose a methodology based on a user session and service profile matrix to generate a reduced user session set. We first collect user sessions from log files and construct a service profile of the application. Then, we build the relational matrix between these two fields. Finally, through concept analysis, a reduced user session set is produced. Experimental results show that our technique can significantly reduce the quantity of collected user session data while retaining service coverage of the application and enhancing the fault detection rate. This technique can also apply to continuously-evolving applications.
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