In this paper, the author provides a framework for Multilevel Expert System to advice scholars for their future career. The proposed framework aims at providing information to decide the career paths for the academics. The emerging fields of Expert System, Education, and Data Mining are speedily providing new possibilities for collecting, analyzing and guiding the scholars in their careers. Many scholars suffer from taking a right career decision, only a few scholars took the right decision about their careers. A poor career decision of scholars may push his whole life in the dark. Nowadays selecting a right career becomes very difficult for the scholars. Among the works reported in this field, we concentrate only Experts Systems that deal with scholar's career selection problem through Data Mining technique.

Software testing is an integral part of the software development cycle. Software testing involves designing a set of test cases. In white box testing, test cases are usually designed based using path testing. The basis path testing approach involves generation of test cases from a set of independent paths. Each test case is forced to execute a certain test path of the control flow graph. Some cases might arise paths of the control flow graph have no test data to force execution. These paths are infeasible paths. Identification and removal of infeasible paths earlier will reduce testing efforts and cost. In the present work, we used Unified Modeling Language (UML) for detecting of these infeasible paths. For detection of these infeasible paths, the author builds the control flow graph from sequence diagram and then generated independent paths from it. Each path is converted into a set of a linear equation and solved. If there is an inconsistent solution, then the corresponding path is infeasible. The presented approach is evaluated on a case study of an automatic gold vending machine.