Open AccessBinary Class Classification of Software Faults in Software Modules using Popular Machine Learning Techniques
Author(s) -
S Devika,
P L Lekshmy
Publication year - 2020
Publication title -
international journal of innovative science and modern engineering
Language(s) - English
Resource type - Journals
ISSN - 2319-6386
DOI - 10.35940/ijisme.f1221.046620
Subject(s) - computer science , software sizing , naive bayes classifier , software development , machine learning , software engineering , software construction , class (philosophy) , software metric , artificial intelligence , software , software bug , software reliability testing , software regression , verification and validation , decision tree , data mining , support vector machine , engineering , operating system , operations management
Software engineering is an important area that deals with development and maintenance of software. After developing a software, it is always important to track its performance. One has to always see whether the software functions according to customer requirements. To ensure this, faulty and non- faulty modules must be identified. For this purpose, one can make use of a model for binary class classification of faults. Different technique's outputs differ in one or the other way with respect to the following: fault dataset used, complexity, classification algorithm implemented, etc. Various machine learning techniques can be used for this purpose. But this paper deals with the best classification algorithms available till date and they are decision tree, random forest, naive bayes and logistic regression (tree-based techniques and bayesian based techniques). The motive behind developing such a project is to identify the faulty modules within a software before the actual software testing takes place. As a result, the time consumed by testers or the workload of the testers can be reduced to an extent. This work is very well useful to those working in software industry and also to those people carrying out research in software engineering where the lifecycle of development of a software is discussed.