Virtually all real-valued computations are carried out using floating-point data types and
operations. The precision of these data types must be set with the goals of reducing the …

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 …

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

Software engineering and development is well-known to suffer from unplanned overtime,
which causes stress and illness in engineers and can lead to poor quality software with …

Floating point computation is by nature inexact, and numerical libraries that intensively
involve floating-point computations may encounter high floating-point errors. Due to the wide …

This paper tackles the important, difficult problem of detecting program inputs that trigger
large floating-point errors in numerical code. It introduces a novel, principled dynamic …

Floating point is widely used in software to emulate arithmetic over reals. Unfortunately,
floating point leads to rounding errors that propagate and accumulate during execution …

The floating-point representation provides widely-used data types (such as “float” and
“double”) for modern numerical software. Numerical errors are inherent due to floating …

Numerical libraries constitute the building blocks for software applications that perform
numerical calculations. Thus, it is paramount that such libraries provide accurate and …