Artificial intelligence (AI) and machine learning (ML) are increasingly broadly adopted in
industry. However, based on well over a dozen case studies, we have learned that …

Context: A large part of the software produced by many companies and organizations today
are web applications. Testing web applications is vital to ensure and maintain the quality of …

Software developers in big and medium-size companies are working with millions of lines of
code in their codebases. Assuring the quality of this code has shifted from simple defect …

Based on interviews with 20 interviewees from four case study companies, this paper
presents a list of key factors that enable efficient and effective exploratory testing of large …

Context: Exploratory testing plays an important role in the continuous integration and
delivery pipelines of large-scale software systems, but a holistic and structured approach is …

With the rapid growth of the contemporary Internet of Things (IoT) market, the established
systems raise a number of concerns regarding the reliability and the potential presence of …

Various software engineering paradigms and real-time projects have proved that software
testing is the most critical and highly important phase in the SDLC. In general, software …

The generation of syntactically and semantically valid input data, able to exercise
functionalities imposing constraints on the validity of the inputs, is a key challenge in …

Testing has been widely recognised as difficult for AI applications. This paper proposes a set
of testing strategies for testing machine learning applications in the framework of the …

Continuous experimentation (CE) refers to a group of practices used by software companies
to rapidly assess the usage, value and performance of deployed software using data …