Synthesis of loop-free programs

Abstract

We consider the problem of synthesizing loop-free programs that implement a desired functionality using components from a given library. Specifications of the desired functionality and the library components are provided as logical relations between their respective input and output variables. The library components can be used at most once, and hence the library is required to contain a reasonable overapproximation of the multiset of the components required. We solve the above component-based synthesis problem using a constraint-based approach that involves first generating a synthesis constraint, and then solving the constraint. The synthesis constraint is a first-order ∃∀ logic formula whose size is quadratic in the number of components. We present a novel algorithm for solving such constraints. Our algorithm is based on counterexample guided iterative synthesis paradigm and uses off-the-shelf SMT solvers. We present experimental results that show that our tool Brahma can efficiently synthesize highly nontrivial 10-20 line loop-free bitvector programs. These programs represent a state space of approximately 20 10 programs, and are beyond the reach of the other tools based on sketching and superoptimization.

Software Workarounds for Hardware Errors: Instruction Patch Synthesis

“…Prior program optimization techniques can potentially be adopted for patch optimization. On the other hand, there are recent attentions on program synthesis [11], [14], [20]. In program synthesis, missing code fragments conforming to some specification are to be derived.…”

“…In program synthesis, missing code fragments conforming to some specification are to be derived. In [11] and [20], the problem reduces to solving quantified formulas (possibly beyond a purely propositional domain), which have quantification structures similar to (5).…”

Constraints as control

“…The counter-example guided approach for this problem was successfully applied to software synthesis in the algorithm for combinatorial sketching using SAT solvers [58]. This technique was later applied with an SMT solver as the satisfiability engine to synthesize loop-free bit-vector code fragments [26].…”

“…These paradigms hold great promise to raise the abstraction level of software. They are related to program synthesis research [26,35,39,53,58], which can be viewed as a compilation mechanism for declarative specifications.…”

A decomposition approach for SMT-based schedule synthesis for time-triggered networks

“…RELATED WORK SMT solvers have been applied to various applications: model checking [11], verification [12], automated test generation [13], synthesis of programs [14] and more. The first use of SMT solvers to synthesize schedules [9] has been done to schedule medium size time-triggered multihop networks.…”