Security vulnerabilities play a vital role in network security system. Fuzzing technology is
widely used as a vulnerability discovery technology to reduce damage in advance …

Context: Software testing is applied to validate the behaviour of the software system and
identify flaws and bugs. Different machine learning technique types such as supervised and …

Mutation-based fuzzing is one of the most popular vulnerability discovery solutions. Its
performance of generating interesting test cases highly depends on the mutation scheduling …

Fuzzing has become the de facto standard technique for finding software vulnerabilities.
However, even state-of-the-art fuzzers are not very efficient at finding hard-to-trigger …

Data flow analysis (eg, dynamic taint analysis) has proven to be useful for guiding fuzzers to
explore hard-to-reach code and find vulnerabilities. However, traditional taint analysis is …

Game testing has been long recognized as a notoriously challenging task, which mainly
relies on manual playing and scripting based testing in game industry. Even until recently …

Web testing has long been recognized as a notoriously difficult task. Even nowadays, web
testing still mainly relies on manual efforts in many cases while automated web testing is still …

Fuzzing embeds a large number of decisions requiring finetuned and hard-coded
parameters to maximize its efficiency. This is especially true for kernel fuzzing due to (1) OS …

Hybrid fuzzing, which combines the merits of both fuzzing and concolic execution, has
become one of the most important trends in coverage-guided fuzzing techniques. Despite …

Greybox fuzzing has made impressive progress in recent years, evolving from heuristics-
based random mutation to approaches for solving individual branch constraints. However …