A feasibility Study: The Succinct Solver v2.0, XSB Prolog v2.6, and Flow-Logic Based Program Analysis for Carmel

Number: SECSAFE-IMM-008-1.0 Classification: Internal Abstract. We perform a direct comparison of the Succinct Solver v2.0 and XSB Prolog v2.6 based on experiments with Control Flow Analyses of scalable Discretionary Ambient programs and Carmel programs. To facilitate this comparison we expand ALFP clauses accepted by the Succinct Solver into more general Normal clauses accepted by both solvers and run the experiments for all three possible combinations of input and solver. This allows the solvers to be tested on even ground and enables the reuse of existing analyses and their corresponding ALFP constraint generators. The performance of the Succinct Solver is at worst a small constant factor worse than XSB Prolog. In optimum cases the Succinct Solver outperforms XSB Prolog by having

Control-flow analysis in cubic time

. It is well-known that context-independent control flow analysis can be performed in cubic time for functional and object-oriented languages. Yet recent applications of control flow analysis to calculi of computation (like the #-calculus and the ambient calculus) have reported considerably higher complexities. In this paper we introduce two general techniques, the use of Horn clauses with sharing and the use of tiling of Horn clauses, for reducing the worst-case complexity of analyses. Applying these techniques to the #-calculus and the ambient calculus we reduce the complexity from O(n 5 ) to O(n 3 ) in both cases. Keywords: Program analysis, Horn clauses with sharing, tiling of Horn clauses, #-calculus, ambient calculus, 0-CFA. 1 Introduction Program analyses often can be separated into two phases. In the first phase, the program to be analyzed is translated into a suitable constraint system describing safe information about the program, and where the unknowns represent the..

Control-Flow Analysis in Cubic Time

It is well-known that context-independent control flow analysis can be performed in cubic time for functional and object-oriented languages. Yet recent applications of control flow analysis to calculi of computation (like the #-calculus and the ambient calculus) have reported considerably higher complexities. In this paper we introduce two general techniques, the use of Horn clauses with sharing and the use of tiling of Horn clauses, for reducing the worst-case complexity of analyses. Applying these techniques to the #-calculus and the ambient calculus we reduce the complexity from O(n 5 ) to O(n 3 ) in both cases