Open AccessFault detection technique for test cases in software engineering
Author(s) -
Jagatjot Singh,
Sumit Sharma
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i1.7870
Subject(s) - computer science , fault detection and isolation , software , software fault tolerance , reliability engineering , process (computing) , fault (geology) , software reliability testing , fault coverage , regression testing , real time computing , software construction , software development , artificial intelligence , engineering , operating system , actuator , geology , electronic circuit , electrical engineering , seismology
The processing of software and performing various operations on it is known as a software engineering process. The application of test cases for detecting the faults within the software is done through the testing process. There are various types of faults that occur within a software or test case which are to be identified and preventive approaches are to be applied to prevent them. In this paper, the Learn-to-rank algorithm is utilized which helps in detecting the faults from the software. The Back-Propagation technique is included with the LRA approach for enhancing its performance and improving the detection of fault rate. 10 test cases of different types are used for running various experiments and the MATLAB tool is utilized for performing various simulations. It is seen through the various simulation results that the fault detection rate is increased as well as the execution time is minimized with the help of this approach.