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Program Derivation by Fixed Point Computation
, 1988
"... This paper develops a transformational paradigm by which nonnumerical algorithms are treated as fixed point computations derived from very high level problem specifications. We begin by presenting an abstract functional + problem specification language SQ , which is shown to express any partial re ..."
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Cited by 58 (10 self)
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This paper develops a transformational paradigm by which nonnumerical algorithms are treated as fixed point computations derived from very high level problem specifications. We begin by presenting an abstract functional + problem specification language SQ , which is shown to express any partial recursive function in a fixed point normal form. Next, we give a nondeterministic iterative schema that in the case of finite iteration generalizes the 'chaotic iteration' of Cousot and Cousot for computing fixed points of monotone functions efficiently. New techniques are discussed for recomputing fixed points of distributive functions efficiently. Numerous examples illustrate how these techniques for computing and recomputing fixed points can be incorporated within a transformational programming methodology to facilitate the design and verification of nonnumerical algorithms. 1. Introduction In a recent survey article [25] Martin Feather has said that the current state of the art of program...
On the Computational Complexity of Dynamic Graph Problems
 THEORETICAL COMPUTER SCIENCE
, 1996
"... ..."
Transformational Design and Implementation Of A New Efficient Solution To The Ready Simulation Problem
 Science of Computer Programming
, 1995
"... A transformational methodology is described for simultaneously designing algorithms and developing programs. The methodology makes use of three transformational tools  dominated convergence, finite differencing, and realtime simulation of a set machine on a RAM. We illustrate the methodology t ..."
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Cited by 42 (2 self)
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A transformational methodology is described for simultaneously designing algorithms and developing programs. The methodology makes use of three transformational tools  dominated convergence, finite differencing, and realtime simulation of a set machine on a RAM. We illustrate the methodology to design a new O(mn + n 2 )time algorithm for deciding when nstate, mtransition processes are ready similar, which is a substantial improvement on the \Theta(mn 6 ) algorithm presented in [6]. The methodology is also used to derive a program whose performance, we believe, is competitive with the most efficient handcrafted implementation of our algorithm. Ready simulation is the finest fully abstract notion of process equivalence in the CCS setting. 1 Introduction Currently there is a wide gap between the goals and practices of research in the theory of algorithm design and the science of programming, which we believe is A preliminary version of this paper appeared in the Conf...
Viewing A Program Transformation System At Work
 Joint 6th International Conference on Programming Language Implementation and Logic Programming (PLILP) and 4th International conference on Algebraic and Logic Programming (ALP), volume 844 of Lecture Notes in Computer Science
, 1994
"... How to decrease labor and improve reliability in the development of efficient implementations of nonnumerical algorithms and labor intensive software is an increasingly important problem as the demand for computer technology shifts from easier applications to more complex algorithmic ones; e.g., opt ..."
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Cited by 26 (2 self)
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How to decrease labor and improve reliability in the development of efficient implementations of nonnumerical algorithms and labor intensive software is an increasingly important problem as the demand for computer technology shifts from easier applications to more complex algorithmic ones; e.g., optimizing compilers for supercomputers, intricate data structures to implement efficient solutions to operations research problems, search and analysis algorithms in genetic engineering, complex software tools for workstations, design automation, etc. It is also a difficult problem that is not solved by current CASE tools and software management disciplines, which are oriented towards data processing and other applications, where the implementation and a prediction of its resource utilization follow more directly from the specification. Recently, Cai and Paige reported experiments suggesting a way to implement nonnumerical algorithms in C at a programming rate (i.e., source lines per second) t...
A simple inductive synthesis methodology and its applications
, 2010
"... Given a highlevel specification and a lowlevel programming language, our goal is to automatically synthesize an efficient program that meets the specification. In this paper, we present a new algorithmic methodology for inductive synthesis that allows us to do this. We use Second Order logic as ou ..."
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Cited by 12 (9 self)
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Given a highlevel specification and a lowlevel programming language, our goal is to automatically synthesize an efficient program that meets the specification. In this paper, we present a new algorithmic methodology for inductive synthesis that allows us to do this. We use Second Order logic as our generic high level specification logic. For our lowlevel languages we choose small applicationspecific logics that can be immediately translated into code that runs in expected linear time in the worst case. We explain our methodology and provide examples of the synthesis of several graph classifiers, e.g, lineartime tests of whether the input graph is connected, acyclic, etc. In another set of applications we automatically derive many finite differencing expressions equivalent to ones that Paige built by hand in his thesis [Pai81]. Finally we describe directions for automatically combining such automatically generated building blocks to synthesize efficient code implementing more complicated specifications. The methods in this paper have been implemented in Python using the SMT solver Z3 [dMB].
A proposal for a
"... Abstract. The objectives of this research are to improve software productivity, reliability, and performance of complex systems. The approach combines program transformations, sometimes in reflective ways, to turn very high level perspicuous specifications into efficient implementations. These trans ..."
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Cited by 1 (0 self)
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Abstract. The objectives of this research are to improve software productivity, reliability, and performance of complex systems. The approach combines program transformations, sometimes in reflective ways, to turn very high level perspicuous specifications into efficient implementations. These transformations will be implemented in a metatransformational system, which itself will be transformed from an executable specification into efficient code. Experiments will be conducted to assess the research objectives in scaled up applications targetted to systems that perform complex program analysis and translation. The transformations to be used include dominated convergence (for implementing fixed points efficiently), finite differencing (for replacing costly repeated calculations by less expensive incremental counterparts), data structure selection (for simulating associative access on a RAM in real time), and partial evaluation (for eliminating interpretive overhead and simplification). Correctness of these transformations, of userdefined transformations, and of the transformational system itself will be addressed in part. Both the partial evaluator and components of the
Research Retrospective
"... The group was exciting in the 1970’s, when we were groping for direction and divided by different orientations. I guess it was in this atmosphere that combined purpose with uncertainty where I found my own voice. The common goal was a transformational program development methodology that would impro ..."
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Cited by 1 (0 self)
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The group was exciting in the 1970’s, when we were groping for direction and divided by different orientations. I guess it was in this atmosphere that combined purpose with uncertainty where I found my own voice. The common goal was a transformational program development methodology that would improve productivity of designing and maintaining correct software. The emphasis was on algorithmic software. We differed as to how to achieve this goal, and my approach was out on a limb. Based on a few transformations, the most exciting of which was Jay Earley’s iterator inversion combined with high level strength reduction, and also on an overly optimistic faith in the power of science to shed light on this subject, I believed that algorithms and algorithmic software could be designed scientifically from abstract problem specifications by application of a small number of rules, whose selection could be simplified (even automated in some cases) if it could be guided by complexity. Most all others (including the SETL crowd at Courant) disagreed, and accepted the notion that algorithm design was ‘inspired’, and that the most significant steps in a derivation were unexplainable ‘Eureka ’ steps. I knew that my goals were ambitious and with little supporting evidence. In fact the
Automatic Generation of Solvers for Multisource Data Flow Analysis Problems
, 2004
"... Much of the success of data flow analysis has come from a welldeveloped unified ..."
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Much of the success of data flow analysis has come from a welldeveloped unified