Abstract program slicing on dependence condition graphs

Mastroeni and Zanardini introduced the notion of semanticsbased data dependences, both at concrete and abstract domains, that helps in converting the traditional syntactic Program Dependence Graphs (PDGs) into more refined semantics-based (abstract) PDGs by disregarding some false dependences from them. As a result, the slicing techniques based on these semantics-based (abstract) PDGs result into more precise slices. Aim: The aim of this paper is to further refine the slicing algorithms when focussing on a given property. Method: The improvement is obtained by (i) applying the notions of semantic relevancy of statements and semantic data dependences, and (ii) combining them with conditional dependences. Result: We provide an abstract slicing algorithm based on semantics-based abstract Dependence Condition Graphs (DCGs) that enable to identify the conditions for dependences between program points