Using Software Metrics for Predicting Vulnerable CodeComponents -code shoppy

 Using Software Metrics for Predicting Vulnerable CodeComponents -code shoppy

 Software vulnerabilities often remain hidden until an attacker exploits the weak/insecure code. Therefore, testing the software from a vulnerability discovery perspective becomes challenging for developers if they do not inspect their code thoroughly (which is time-consuming). We propose that vulnerability prediction using certain software metrics can support the testing process by identifying vulnerable code-components (e.g., functions, classes, etc.). Once a code-component is predicted as vulnerable, the developers can focus their testing efforts on it, thereby avoiding the time/effort required for testing the entire application. The current paper presents a study that compares how software metrics perform as vulnerability predictors for software projects developed in two different languages (Java vs Python). The goal of this research is to analyze the vulnerability prediction performance of software metrics for different programming languages. We designed and conducted experiments on security vulnerabilities reported for three Java projects (Apache Tomcat 6, Tomcat 7, Apache CXF) and two Python projects (Django and Keystone). In this paper, we focus on a specific type of code component: Functions. We apply Machine Learning models for predicting vulnerable functions. Overall results show that software metrics-based vulnerability prediction is more useful for Java projects than Python projects (i.e., software metrics when used as features were able to predict Java vulnerable functions with a higher recall and precision compared to Python vulnerable functions prediction).

 

Online Registration System is a framework to link various hospitals across the country for email id  and mobile number based online registration and appointment system, where counter based OPD registration and appointment system through Hospital Management Information System (HMIS) has been digitalized. Portal facilitates online appointments with various departments of different Hospitals using email id. Patient Mobile number is verified using email to make sure the vaccination and test results reach for correct patients.evoting using django project

Total number of Hospitals for which appointment can be taken through web along with their departments for which online appointment can be taken can be seen in reports. Detail reports showing information about New and Old patients taking appointment through this portal can be seen. Hospitals can come on board this platform and provide their appointment slots for online booking by patients.agri shop

 

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