  Constraint Logic Programming (CLP) is a language scheme for combining two
declarative paradigms: constraint solving and logic programming. Concurrent
Constraint Programming (CCP) is a declarative model for concurrency where
agents interact by telling and asking constraints in a shared store. In a
previous paper, we developed a framework for dynamic slicing of CCP where the
user first identifies that a (partial) computation is wrong. Then, she marks
(selects) some parts of the final state corresponding to the data (constraints)
and processes that she wants to study more deeply. An automatic process of
slicing begins, and the partial computation is "depurated" by removing
irrelevant information. In this paper we give two major contributions. First,
we extend the framework to CLP, thus generalizing the previous work. Second, we
provide an assertion language suitable for both, CCP and CLP, which allows the
user to specify some properties of the computations in her program. If a state
in a computation does not satisfy an assertion then some "wrong" information is
identified and an automatic slicing process can start. This way we make one
step further towards automatizing the slicing process. We show that our
framework can be integrated with the previous semi-automatic one, giving the
user more choices and flexibility. We show by means of examples and experiments
the usefulness of our approach.
