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 …

Combining fuzzing techniques and reinforcement learning could be an important direction in
software testing. However, there is a gap in support for experimentation in this field, as there …

This paper presents an integrated testing framework for Internet of Things (IoT) systems
based on the open-source platform RIVER. Our objective is to leverage the existing methods …

The increasingly popular no-or low-code paradigm is based on functional blocks connected
on a graphical interface that is accessible to many stakeholders in an application. Areas …

Testing cloud applications has recently gained in importance since many companies
migrated their operations in the cloud. To optimise resources, cloud applications may serve …

The current encryption infrastructure is no match for an Artificial Superintelligence (ASI), the
likely result of a possible intelligence explosion by a self-improving AI. That kind of ASI …

This paper presents the latest updates to the RIVER open-source testing platform for x86
programs, focusing on how artificial intelligence (AI) techniques can be used to improve the …

This paper presents a new open-source testing tool capable of performing concolic
execution on x86 binaries. Using this tool, one can find out ahead of time of potential bugs …