This paper surveys recent work on applying analysis and transformation techniques that
originate in the field of constraint logic programming (CLP) to the problem of verifying …

Emerging high-performance architectures are anticipated to contain unreliable components
that may exhibit soft errors, which silently corrupt the results of computations. Full detection …

The" size-change termination" principle for a first-order functional language with well-
founded data is: a program terminates on all inputs if every infinite call sequence (following …

Probabilistic inference is a key mechanism for reasoning about probabilistic programs.
Since exact inference is theoretically expensive, most probabilistic inference systems today …

With the range and sensitivity of algorithmic decisions expanding at a break-neck speed, it is
imperative that we aggressively investigate fairness and bias in decision-making programs …

The continued development of efficient automated decision procedures has spurred the
resurgence of research on symbolic execution over the past decade. Researchers have …

In order to contribute to the solution of the software reliability problem, tools have been
designed to analyze statically the run-time behavior of programs. Because the correctness …

As machine learning systems are increasingly used to make real world legal and financial
decisions, it is of paramount importance that we develop algorithms to verify that these …

We introduce a general uniform language-independent framework for designing online and
offline source-to-source program transformations by abstract interpretation of program …

Probabilistic programming systems (PP systems) allow developers to model stochastic
phenomena and perform efficient inference on the models. The number and adoption of …