One of the basic scheduling problems, the open-shop scheduling problem has a broad
range of applications across different sectors. The problem concerns scheduling a set of …

Before a combinatorial problem can be solved by current SAT methods, it must usually be
encoded in conjunctive normal form, which facilitates algorithm implementation and allows a …

Understanding properties of deep neural networks is an important challenge in deep
learning. In this paper, we take a step in this direction by proposing a rigorous way of …

In this system description, we present the tool AProVE for automatic termination and
complexity proofs of Java, C, Haskell, Prolog, and rewrite systems. In addition to classical …

Algorithm selection (AS) techniques-which involve choosing from a set of algorithms the one
expected to solve a given problem instance most efficiently-have substantially improved the …

Understanding database reconstruction attacks on public data Page 1 46 COMMUNICATIONS
OF THE ACM | MARCH 2019 | VOL. 62 | NO. 3 practice IN 2020, THE US Census Bureau will …

Answer Set Programming (ASP) is a well-known paradigm of declarative programming with
roots in logic programming and non-monotonic reasoning. Similar to other closely related …

When solving a combinatorial problem using Constraint Programming (CP) or Satisfiability
(SAT), modelling and formulation are vital and difficult tasks. Even an expert human may …

We present the third generation of the constraint answer set system clingcon, combining
Answer Set Programming (ASP) with finite domain constraint processing (CP). While its …

Path testing is the strongest coverage criterion in white box testing. Finding target paths is a
key challenge in path testing. Genetic algorithms have been successfully used in many …