Background: Recently, machine and deep learning (ML/DL) algorithms have been
increasingly adopted in many software systems. Due to their inductive nature, ensuring the …

Context Confirmation bias is a person's tendency to look for evidence that strengthens
his/her prior beliefs rather than refutes them. Manifestation of confirmation bias in software …

Background: The existing literature in software engineering reports adverse effects of
confirmation bias on software testing. Confirmation bias among software testers leads to …

Positive tests (aka, happy path tests) cover the expected behavior of the program, while
negative tests (aka, unhappy path tests) check the unexpected behavior. Ideally, test suites …

Background: Software testers manifest confirmation bias (the cognitive tendency) when they
design relatively more specification consistent test cases than specification inconsistent test …

Background: We are witnessing an increasing adoption of machine learning (ML), especially
deep learning (DL) algorithms in many software systems, including safety-critical systems …

When creating test cases, ideally, developers should test both the expected and unexpected
behaviors of the program to catch more bugs and avoid regressions. However, the literature …

Testing is a key activity in industry to verify and validate products before they reach end
customers. In hardware-in-the-loop system-level verification of automotive systems, testing is …

Testing is an important phase of every software system, as it can reveal defects early and
contribute to achieving high software quality. In this process of quality assurance …

The size and complexity of software in automotive systems have increased steadily over the
last decades. Modern vehicles typically contain numerous electrical control units (ECUs) …