Regression testing is a crucial part of software development. It checks that software changes
do not break existing functionality. An important assumption of regression testing is that test …

Given the variety of numerical errors that can occur, floating-point programs are difficult to
write, test and debug. One common practice employed by developers without an advanced …

Scientific and engineering applications depend on floating point arithmetic to approximate
real arithmetic. This approximation introduces rounding error, which can accumulate to …

Rigorous estimation of maximum floating-point round-off errors is an important capability
central to many formal verification tools. Unfortunately, available techniques for this task …

Metamorphic testing (MT) is an effective methodology for testing those so-called``non-
testable''programs (eg, scientific programs), where it is sometimes very difficult for testers to …

Automated unit test generation techniques traditionally follow one of two goals: Either they
try to find violations of automated oracles (eg, assertions, contracts, undeclared exceptions) …

Deep learning (DL) techniques attract people from various fields with superior performance
in making progressive breakthroughs. To ensure the quality of DL techniques, researchers …

Numerical software is used in a wide variety of applications including safety-critical systems,
which have stringent correctness requirements, and whose failures have catastrophic …

Tools for floating-point error estimation are fundamental to program understanding and
optimization. In this paper, we focus on tools for determining the input settings to a floating …

While tremendously useful, automated techniques for tuning the precision of floating-point
programs face important scalability challenges. We present Blame Analysis, a novel …