Evaluating and Comparing Size, Complexity and Coupling Metrics as Web Applications Vulnerabilities Predictors
Author(s) -
Mohammed Zagane,
Mustapha Kamel Abdi
Publication year - 2019
Publication title -
international journal of information technology and computer science
Language(s) - English
Resource type - Journals
eISSN - 2074-9015
pISSN - 2074-9007
DOI - 10.5815/ijitcs.2019.07.05
Subject(s) - computer science , web application , web application security , software , code (set theory) , vulnerability (computing) , cyclomatic complexity , software metric , data mining , source code , web service , world wide web , web development , software development , software quality , computer security , operating system , set (abstract data type) , programming language
Most security and privacy issues in software are related to exploiting code vulnerabilities. Many studies have tried to find the correlation between the software characteristics (complexity, coupling, etc.) quantified by corresponding code metrics and its vulnerabilities and to propose automatic prediction models that help developers locate vulnerable components to minimize maintenance costs. The results obtained by these studies cannot be applied directly to web applications because a web application differs in many ways from a non-web application: development, use, etc. and a lot of evaluation of these conclusions has to be made. The purpose of this study is to evaluate and compare the vulnerabilities prediction power of three types of code metrics in web applications. There are a few similar studies that targeted non-web application and to the best of our knowledge, there are no similar studies that targeted web applications. The results obtained show that unlike non-web applications where complexity metrics have better vulnerability prediction power, in web applications the metrics that give better prediction are the coupling metrics with high recall (> 75%) and fewer costs in terms of inspection (<25%).
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