Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Software Engineering

PDF

Research Collection School Of Computing and Information Systems

Series

Empirical study

Publication Year

Articles 1 - 2 of 2

Full-Text Articles in Engineering

Practitioners' Expectations On Automated Fault Localization, Pavneet Singh Kochhar, Xin Xia, David Lo, Shanping Li Jul 2016

Practitioners' Expectations On Automated Fault Localization, Pavneet Singh Kochhar, Xin Xia, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Software engineering practitioners often spend significant amount of time and effort to debug. To help practitioners perform this crucial task, hundreds of papers have proposed various fault localization techniques. Fault localization helps practitioners to find the location of a defect given its symptoms (e.g., program failures). These localization techniques have pinpointed the locations of bugs of various systems of diverse sizes, with varying degrees of success, and for various usage scenarios. Unfortunately, it is unclear whether practitioners appreciate this line of research. To fill this gap, we performed an empirical study by surveying 386 practitioners from more than 30 countries …


Predicting Sql Injection And Cross Site Scripting Vulnerabilities Through Mining Input Sanitization Patterns, Lwin Khin Shar, Hee Beng Kuan Tan Apr 2013

Predicting Sql Injection And Cross Site Scripting Vulnerabilities Through Mining Input Sanitization Patterns, Lwin Khin Shar, Hee Beng Kuan Tan

Research Collection School Of Computing and Information Systems

ContextSQL injection (SQLI) and cross site scripting (XSS) are the two most common and serious web application vulnerabilities for the past decade. To mitigate these two security threats, many vulnerability detection approaches based on static and dynamic taint analysis techniques have been proposed. Alternatively, there are also vulnerability prediction approaches based on machine learning techniques, which showed that static code attributes such as code complexity measures are cheap and useful predictors. However, current prediction approaches target general vulnerabilities. And most of these approaches locate vulnerable code only at software component or file levels. Some approaches also involve process attributes that …