This is a vision paper on incorporating of embodied virtual agents into everyday operations of software testing team. An important property of intelligent virtual agents is their capability to acquire information from their environment as well as from available data bases and information services. Research challenges and issues tied up with development of intelligent virtual assistant for software testing team are discussed.
An overview of recent research on passive testing methods and tools which covers 104 manually selected papers most relevant to this topic - research presented at MACSPro in Vienna by Iosif Itkin.
The research aims to decrease maintenance costs and improve software quality via ML-enabled analysis of bug report descriptions. Feature selection helps better predict resolution times for various purposes.
This paper presents Petri net models assembling crucial processes executed within order-driven systems: order submission, application of precedence rules, and the order matching mechanism.
The paper presents an overview of a test automation framework aimed at end-to-end functional and non-functional testing of DLT-based hybrid financial software for post-trade. The proposed solution comprises the components designed for testing user-facing parts of the SUT as well as business logic specific for different DLT-based architectures. This combined approach is seen as a viable solution of the problem of the SUT complexity as well the variety of possible DLT architectural decisions.
Testing of distributed systems is a complex task, which is hampered by the impossibility of guaranteed reproduction of errors associated with race conditions. Even minor instrumentation of the system significantly changes its characteristics, which becomes critical, especially for load testing. All of that increases the importance of quality control methods based on the system log analysis. In this paper, we present our experience of semi-automated analysis of the behavior of clearing and settlement system by utilizing its logs for the purpose of identifying and classifying errors.
