Root Cause Detection and Test Case Generation for Student Academics

Abstract

Cause-effect graph concept is used to shows the relation between the effect (outcome) and cause (condition/input). We identified and define the effect and fill the effect box and draw the spine, than constructed binart tree based code events, iterate through the tree to get the result, if the results are on the false side it will backtrack towards to the root to find the actual cause and will print. The work scan the code line by line and will show the line number where actual the problem is.We took one sample test code(Fibonacci series) to demonstrate the concept. Concentrated on the bugs such as library function inclusion, parenthessis matching and package inclusion. Once the root cause is found, these data can be used for test case generation, student academic details are used in the easiest way. We categorized the student's strength levels on the basis of their studying capabilities, regularity in class and participation activities in the Indoor or outdoor level. Depending on this categorization we analyzed the effect, then Graph is constructed, it then converted into a decision table, and lastly we conclude with test case generation. So by considering the effects, the department heads can also take prior mitigations. This study useful for testing people who involved in application related to educational institutions can have the scope to pick up the test cases directly. This paper also helps educational institutions to reason out the actual cause for their effects.