40 citations · 54 across the 9 of their papers we have counts for
9 papers
Enhanced Bug Prediction in JavaScript Programs with Hybrid Call-Graph Based Invocation Metrics
Gábor Antal, Zoltán Tóth, Péter Hegedűs +1
Bug prediction aims at finding source code elements in a software system that are likely to contain defects. Being aware of the most error-prone parts of the program, one can effic…
Challenging Machine Learning Algorithms in Predicting Vulnerable JavaScript Functions
Rudolf Ferenc, Péter Hegedűs, Péter Gyimesi +3
The rapid rise of cyber-crime activities and the growing number of devices threatened by them place software security issues in the spotlight. As around 90% of all attacks exploit…
Static JavaScript Call Graphs: A Comparative Study
Gábor Antal, Péter Hegedűs, Zoltán Tóth +2
The popularity and wide adoption of JavaScript both at the client and server side makes its code analysis more important than ever before. Most of the algorithms for vulnerability…
Transforming C++11 Code to C++03 to Support Legacy Compilation Environments
Gábor Antal, Dávid Havas, István Siket +3
Newer technologies - programming languages, environments, libraries - change very rapidly. However, various internal and external constraints often prevent projects from quickly ad…
An AST-based Code Change Representation and its Performance in Just-in-time Vulnerability Prediction
Tamás Aladics, Péter Hegedűs, Rudolf Ferenc
The presence of software vulnerabilities is an ever-growing issue in software development. In most cases, it is desirable to detect vulnerabilities as early as possible, preferably…
Bug Prediction Using Source Code Embedding Based on Doc2Vec
Tamás Aladics, Judit Jász, Rudolf Ferenc
Bug prediction is a resource demanding task that is hard to automate using static source code analysis. In many fields of computer science, machine learning has proven to be extrem…
Improving Vulnerability Prediction of JavaScript Functions Using Process Metrics
Tamás Viszkok, Péter Hegedűs, Rudolf Ferenc
Due to the growing number of cyber attacks against computer systems, we need to pay special attention to the security of our software systems. In order to maximize the effectivenes…
Employing Partial Least Squares Regression with Discriminant Analysis for Bug Prediction
Rudolf Ferenc, István Siket, Péter Hegedűs +1
Forecasting defect proneness of source code has long been a major research concern. Having an estimation of those parts of a software system that most likely contain bugs may help…
An Automatically Created Novel Bug Dataset and its Validation in Bug Prediction
Rudolf Ferenc, Péter Gyimesi, Gábor Gyimesi +2
Bugs are inescapable during software development due to frequent code changes, tight deadlines, etc.; therefore, it is important to have tools to find these errors. One way of perf…