Program analysis is the heart of modern compilers. Most control flow analyses are reduced to the problem of finding a fixed point in a certain transition system, and such fixed point is commonly computed through an iterative procedure that repeats tracing until convergence. This paper proposes a new method to analyze programs through recursive graph traversals instead of iterative procedures, based on the fact that most programs (without spaghetti GOTO) have wellstructured control flow graphs, graphs with bounded tree width. Our main techniques are; an algebraic construction of a control flow graph, called SP Term, which enables control flow analysis to be defined in a natural recursive form, and the Optimization Theorem, which enables us to compute optimal solution by dynamic programming. We illustrate our method with two examples; dead code detection and register allocation. Different from the traditional standard iterative solution, our dead code detection is described as a simple combination of bottom-up and top-down traversals on SP Term. Register allocation is more interesting, as it further requires optimality of the result. We show how the Optimization Theorem on SP Terms works to find an optimal register allocation as a certain dynamic programming.
In this paper we propose a new method for deriving a practical linear-time algorithm from the specification of a maximum-weightsum problem: From the elements of a data structure x , find a subset which satisfies a certain property p and whose weightsum is maximum. Previously proposed methods for automatically generating linear-time algorithms are theoretically appealing, but the algorithms generated are hardly useful in practice due to a huge constant factor for space and time. The key points of our approach are to express the property p by a recursive boolean function over the structure x rather than a usual logical predicate and to apply program transformation techniques to reduce the constant factor. We present an optimization theorem , give a calculational strategy for applying the theorem, and demonstrate the effectiveness of our approach through several nontrivial examples which would be difficult to deal with when using the methods previously available.
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