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SyntaxGuided Synthesis
"... Abstract—The classical formulation of the programsynthesis problem is to find a program that meets a correctness specification given as a logical formula. Recent work on program synthesis and program optimization illustrates many potential benefits of allowing the user to supplement the logical spe ..."
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Abstract—The classical formulation of the programsynthesis problem is to find a program that meets a correctness specification given as a logical formula. Recent work on program synthesis and program optimization illustrates many potential benefits of allowing the user to supplement the logical specification with a syntactic template that constrains the space of allowed implementations. Our goal is to identify the core computational problem common to these proposals in a logical framework. The input to the syntaxguided synthesis problem (SyGuS) consists of a background theory, a semantic correctness specification for the desired program given by a logical formula, and a syntactic set of candidate implementations given by a grammar. The computational problem then is to find an implementation from the set of candidate expressions so that it satisfies the specification in the given theory. We describe three different instantiations of the counterexampleguidedinductivesynthesis (CEGIS) strategy for solving the synthesis problem, report on prototype implementations, and present experimental results on an initial set of benchmarks. I.
Reductions for Synthesis Procedures ⋆
"... Abstract. A synthesis procedure acts as a compiler for declarative specifications. It accepts a formula describing a relation between inputs and outputs, and generates a function implementing this relation. This paper presents the first synthesis procedures for 1) algebraic data types and 2) arrays. ..."
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Abstract. A synthesis procedure acts as a compiler for declarative specifications. It accepts a formula describing a relation between inputs and outputs, and generates a function implementing this relation. This paper presents the first synthesis procedures for 1) algebraic data types and 2) arrays. Our procedures are reductions that lift a synthesis procedure for the elements into synthesis procedures for containers storing these elements. We introduce a framework to describe synthesis procedures as systematic applications of inference rules. We show that, by interpreting both synthesis problems and programs as relations, we can derive and modularly prove widely applicable transformation rules, simplifying both the presentation and the correctness argument. 1
On Integrating Deductive Synthesis and Verification Systems
, 2013
"... We describe techniques for synthesis and verification of recursive functional programs over unbounded domains. Our techniques build on top of an algorithm for satisfiability modulo recursive functions, a framework for deductive synthesis, and complete synthesis procedures for algebraic data types. W ..."
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We describe techniques for synthesis and verification of recursive functional programs over unbounded domains. Our techniques build on top of an algorithm for satisfiability modulo recursive functions, a framework for deductive synthesis, and complete synthesis procedures for algebraic data types. We present new counterexampleguided algorithms for constructing verified programs. We have implemented these algorithms in an integrated environment for interactive verification and synthesis from relational specifications. Our system was able to synthesize a number of useful recursive functions that manipulate unbounded numbers and data structures.
TRANSIT: Specifying Protocols with Concolic Snippets ∗
"... With the maturing of technology for model checking and constraint solving, there is an emerging opportunity to develop programming tools that can transform the way systems are specified. In this paper, we propose a new way to program distributed protocols using concolic snippets. Concolic snippets a ..."
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With the maturing of technology for model checking and constraint solving, there is an emerging opportunity to develop programming tools that can transform the way systems are specified. In this paper, we propose a new way to program distributed protocols using concolic snippets. Concolic snippets are sample execution fragments that contain both concrete and symbolic values. The proposed approach allows the programmer to describe the desired system partially using the traditional model of communicating extended finitestatemachines (EFSM), along with highlevel invariants and concrete execution fragments. Our synthesis engine completes an EFSM skeleton by inferring guards and updates from the given fragments which is then automatically analyzed using a model checker with respect to the desired invariants. The counterexamples produced by the model checker can then be used by
Executing Specifications using Synthesis and Constraint Solving
"... Abstract. Specifications are key to improving software reliability as well as documenting precisely the intended behavior of software. Writing specifications is still perceived as expensive. Of course, writing implementations is at least as expensive, but is hardly questioned because there is curren ..."
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Abstract. Specifications are key to improving software reliability as well as documenting precisely the intended behavior of software. Writing specifications is still perceived as expensive. Of course, writing implementations is at least as expensive, but is hardly questioned because there is currently no real alternative. Our goal is to give specifications a more balanced role compared to implementations, enabling the developers to compile, execute, optimize, and verify against each other mixed code fragments containing both specifications and implementations. To make specification constructs executable we combine deductive synthesis with runtime constraint solving, in both cases leveraging modern SMT solvers. Our tool decomposes specifications into simpler fragments using a costdriven deductive synthesis framework. It compiles as many fragments as possible into conventional functional code; it executes the remaining fragments by invoking our constraint solver that extends an SMT solver to handle recursive functions. Using this approach we were able to execute constraints that describe the desired properties of integers, sets, maps and algebraic data types. 1
On Reductions for Synthesis Procedures EPFLREPORT181031
"... Abstract. A synthesis procedure acts as a compiler for declarative specifications. It accepts a formula describing a relation between inputs and outputs, and generates a function implementing this relation. This paper presents synthesis procedures for data structures. Our procedures are reductions t ..."
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Abstract. A synthesis procedure acts as a compiler for declarative specifications. It accepts a formula describing a relation between inputs and outputs, and generates a function implementing this relation. This paper presents synthesis procedures for data structures. Our procedures are reductions that lift a synthesis procedure for the elements into synthesis procedures for containers storing these elements. We introduce a framework to describe synthesis procedures as systematic applications of inference rules. We show that, by interpreting both synthesis problems and programs as relations, we can derive and modularly prove transformation rules that are widely applicable, thus simplifying both the presentation and the correctness argument. 1
Interpolation for Synthesis on Unbounded Domains
"... Abstract—Synthesis procedures compile relational specifications into functions. In addition to bounded domains, synthesis procedures are applicable to domains such as mathematical integers, where the domain and range of relations and synthesized code is unbounded. Previous work presented synthesis p ..."
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Abstract—Synthesis procedures compile relational specifications into functions. In addition to bounded domains, synthesis procedures are applicable to domains such as mathematical integers, where the domain and range of relations and synthesized code is unbounded. Previous work presented synthesis procedures that generate selfcontained code and do not require components as inputs. The advantage of this approach is that it requires only specifications as user input. On the other hand, in some cases it can be desirable to require that the synthesized system reuses existing components. This paper describes a fairly general technique to automatically synthesize systems from components. Our technique is sound, and it is complete for constraints for which an interpolation procedure exists, which includes e.g. propositional logic, bitvectors, linear integer arithmetic, recursive structures, finite sets, and extensions of the theory of arrays. I.