Symbolic execution is capable of automatically generating tests that achieve high coverage. However, its practical use is limited by the scalability problem. To mitigate it, this paper proposes State Concretization based Symbolic Execution (SCSE). SCSE speeds up symbolic execution via state concretization. Specifically, by introducing a concrete store, our approach avoids invoking the constraint solver to check path feasibility at conditional instructions. Intuitively, there is no need to check the feasibility of a path along a concrete execution since it is always feasible. With state concretization, the number of solver queries greatly decreases, thus improving the efficiency of symbolic execution. Through experimental evaluation on real programs, we show that state concretization helps to speed up symbolic execution significantly.

In this paper we describe collaborative constraint functional logic programming and the system called Open CFLP that supports this programming paradigm. The system solves equations by collaboration of various equational constraint solvers. The solvers include higher-order lazy narrowing calculi that serve as the interpreter of higher-order functional logic programming, and specialized solvers for solving equations over specific domains, such as a polynomial solver and a differential equation solver. The constraint solvers are distributed in an open environment such as the Internet. They act as providers of constraint solving services. The collaboration between solvers is programmed in a coordination language embedded in a host language. In Open CFLP the user can solve equations in a higher-order functional logic programming style and yet exploit solving resources in the Internet without giving low-level programs of distributions of resources or specifying details of solvers deployed in the Internet.