--------------------------------------------------------------------------------- -- | -- Module : Data.SBV -- Copyright : (c) Levent Erkok -- License : BSD3 -- Maintainer : erkokl@gmail.com -- Stability : experimental -- Portability : portable -- -- (The sbv library is hosted at . -- Comments, bug reports, and patches are always welcome.) -- -- SBV: Symbolic Bit Vectors in Haskell -- -- Express properties about bit-precise Haskell programs and automatically prove -- them using SMT solvers. -- -- >>> prove $ \x -> x `shiftL` 2 .== 4 * (x :: SWord8) -- Q.E.D. -- -- >>> prove $ forAll ["x"] $ \x -> x `shiftL` 2 .== (x :: SWord8) -- Falsifiable. Counter-example: -- x = 128 :: SWord8 -- -- The function 'prove' has the following type: -- -- @ -- 'prove' :: 'Provable' a => a -> 'IO' 'ThmResult' -- @ -- -- The class 'Provable' comes with instances for n-ary predicates, for arbitrary n. -- The predicates are just regular Haskell functions over symbolic signed and unsigned -- bit-vectors. Functions for checking satisfiability ('sat' and 'allSat') are also -- provided. -- -- In particular, the sbv library introduces the types: -- -- * 'SBool': Symbolic Booleans (bits) -- -- * 'SWord8', 'SWord16', 'SWord32', 'SWord64': Symbolic Words (unsigned) -- -- * 'SInt8', 'SInt16', 'SInt32', 'SInt64': Symbolic Ints (signed) -- -- * 'SArray', 'SFunArray': Flat arrays of symbolic values -- -- * Symbolic polynomials over GF(2^n), and polynomial arithmetic -- -- * Uninterpreted constants and functions over symbolic values, with user -- defined SMT-Lib axioms -- -- The user can construct ordinary Haskell programs using these types, which behave -- very similar to their concrete counterparts. In particular these types belong to the -- standard classes 'Num', 'Bits', custom versions of 'Eq' ('EqSymbolic') -- and 'Ord' ('OrdSymbolic'), along with several other custom classes for simplifying -- bit-precise programming with symbolic values. The framework takes full advantage -- of Haskell's type inference to avoid many common mistakes. -- -- Furthermore, predicates (i.e., functions that return 'SBool') built out of -- these types can also be: -- -- * proven correct via an external SMT solver (the 'prove' function) -- -- * checked for satisfiability (the 'sat' and 'allSat' functions) -- -- * quick-checked -- -- If a predicate is not valid, 'prove' will return a counterexample: An -- assignment to inputs such that the predicate fails. The 'sat' function will -- return a satisfying assignment, if there is one. The 'allSat' function returns -- all satisfying assignments, lazily. -- -- The sbv library uses third-party SMT solvers via the standard SMT-Lib interface: -- . -- -- While the library is designed to work with any SMT-Lib compliant SMT-solver, -- solver specific support is required for parsing counter-example/model data since -- there is currently no agreed upon format for getting models from arbitrary SMT -- solvers. (The SMT-Lib2 initiative will potentially address this issue in the -- future, at which point the sbv library can be generalized as well.) Currently, we -- only support the Yices SMT solver from SRI as far as the counter-example -- and model generation support is concerned: . -- However, other solvers can be hooked up with relative ease. -- -- You /should/ download and install Yices on your machine, and make sure the -- @yices@ executable is in your path before using the sbv library, as it is the -- current default solver. Alternatively, you can specify the location of yices -- executable in the environment variable @SBV_YICES@ and the options to yices -- in @SBV_YICES_OPTIONS@. (The default for the latter is '\"-m -f\"'.) --------------------------------------------------------------------------------- module Data.SBV ( -- * Programming with symbolic values -- $progIntro -- ** Symbolic types -- *** Symbolic bit SBool -- *** Unsigned symbolic bit-vectors , SWord8, SWord16, SWord32, SWord64 -- *** Signed symbolic bit-vectors , SInt8, SInt16, SInt32, SInt64 -- *** Arrays of symbolic values , SymArray(..), SArray, SFunArray, mkSFunArray -- *** Full binary trees , STree, readSTree, writeSTree, mkSTree -- ** Operations on symbolic words -- *** Word level , bitValue, setBitTo, oneIf, lsb, msb -- *** List level , allEqual, allDifferent -- *** Blasting/Unblasting , blastBE, blastLE, FromBits(..) -- *** Splitting, joining, and extending , Splittable(..) -- *** Sign-casting , SignCast(..) -- ** Polynomial arithmetic , Polynomial(..) -- ** Conditionals: Mergeable values , Mergeable(..) -- ** Symbolic equality , EqSymbolic(..) -- ** Symbolic ordering , OrdSymbolic(..) -- ** Division , BVDivisible(..) -- ** The Boolean class , Boolean(..) -- *** Generalizations of boolean operations , bAnd, bOr, bAny, bAll -- ** Pretty-printing and reading numbers in Hex & Binary , PrettyNum(..), readBin -- * Uninterpreted constants and functions , Uninterpreted(..) -- ** Accessing the handle , SBVUF, sbvUFName -- ** Adding axioms , addAxiom -- * Proving properties -- $proveIntro -- ** Predicates , Predicate, Provable(..), Equality(..) -- ** Proving properties , prove, proveWith, isTheorem, isTheoremWithin -- ** Checking satisfiability , sat, satWith, isSatisfiable, isSatisfiableWithin -- ** Finding all satisfying assignments , allSat, allSatWith, numberOfModels -- * Model extraction -- $modelExtraction -- ** Inspecting proof results -- $resultTypes , ThmResult(..), SatResult(..), AllSatResult(..), SMTResult(..) -- ** Programmable model extraction -- $programmableExtraction , SatModel(..), getModel, displayModels -- * SMT Interface: Configurations and solvers , SMTConfig(..), SMTSolver(..), defaultSMTCfg, verboseSMTCfg, timingSMTCfg, verboseTimingSMTCfg, timeout , yices -- * Symbolic computations , Symbolic, output, SymWord(..) -- * Getting SMT-Lib output (for offline analysis) , compileToSMTLib -- * Code generation from symbolic programs -- $cCodeGeneration , SBVCodeGen -- ** Setting code-generation options , cgPerformRTCs, cgSetDriverValues -- ** Designating inputs , cgInput, cgInputArr -- ** Designating outputs , cgOutput, cgOutputArr -- ** Designating return values , cgReturn, cgReturnArr -- ** Compilation to C , compileToC, compileToCLib -- * Module exports -- $moduleExportIntro , module Data.Bits , module Data.Word , module Data.Int ) where import Data.SBV.BitVectors.Data import Data.SBV.BitVectors.Model import Data.SBV.BitVectors.PrettyNum import Data.SBV.BitVectors.Polynomial import Data.SBV.BitVectors.SignCast import Data.SBV.BitVectors.Splittable import Data.SBV.BitVectors.STree import Data.SBV.Compilers.C import Data.SBV.Compilers.CodeGen import Data.SBV.Provers.Prover import Data.SBV.Utils.Boolean import Data.Bits import Data.Word import Data.Int -- Haddock section documentation {- $progIntro The SBV library is really two things: * A framework for writing bit-precise programs in Haskell * A framework for proving properties of such programs using SMT solvers In this first section we will look at the constructs that will let us construct such programs in Haskell. The goal is to have a "seamless" experience, i.e., program in the usual Haskell style without distractions of symbolic coding. While Haskell helps in some aspects (the 'Num' and 'Bits' classes simplify coding), it makes life harder in others. For instance, @if-then-else@ only takes 'Bool' as a test in Haskell, and comparisons ('>' etc.) only return 'Bool's. Clearly we would like these values to be symbolic (i.e., 'SBool'), thus stopping us from using some native Haskell constructs. When symbolic versions of operators are needed, they are typically obtained by prepending a dot, for instance '==' becomes '.=='. Care has been taken to make the transition painless. In particular, any Haskell program you build out of symbolic components is fully concretely executable within Haskell, without the need for any custom interpreters. (They are truly Haskell programs, not AST's built out of pieces of syntax.) This provides for an integrated feel of the system, one of the original design goals for SBV. -} {- $proveIntro The SBV library provides a "push-button" verification system via automated SMT solving. The design goal is to let SMT solvers be used without any knowledge of how SMT solvers work or how different logics operate. The details are hidden behind the SBV framework, providing Haskell programmers with a clean API that is unencumbered by the details of individual solvers. To that end, we use the SMT-Lib standard () to communicate with arbitrary SMT solvers. Unfortunately, the SMT-Lib version 1.X does not standardize how models are communicated back from solvers, so there is some work in parsing individual SMT solver output. The 2.X version of the SMT-Lib standard (not yet implemented by SMT solvers widely, unfortunately) will bring new standard features for getting models; at which time the SBV framework can be modified into a truly plug-and-play system where arbitrary SMT solvers can be used. -} {- $modelExtraction The default 'Show' instances for prover calls provide all the counter-example information in a human-readable form and should be sufficient for most casual uses of sbv. However, tools built on top of sbv will inevitably need to look into the constructed models more deeply, programmatically extracting their results and performing actions based on them. The API provided in this section aims at simplifying this task. -} {- $resultTypes 'ThmResult', 'SatResult', and 'AllSatResult' are simple newtype wrappers over 'SMTResult'. Their main purpose is so that we can provide custom 'Show' instances to print results accordingly. -} {- $programmableExtraction While default 'Show' instances are sufficient for most use cases, it is sometimes desirable (especially for library construction) that the SMT-models are reinterpreted in terms of domain types. Programmable extraction allows getting arbitrarily typed models out of SMT models. -} {- $cCodeGeneration The SBV library can generate straight-line executable code in C. (While other target languages are certainly possible, currently only C is supported.) The generated code will perform no run-time memory-allocations, (no calls to @malloc@), so its memory usage can be predicted ahead of time. Also, the functions will execute precisely the same instructions in all calls, so they have predictable timing properties as well. The generated code has no loops or jumps, and is typically quite fast. While the generated code can be large due to complete unrolling, these characteristics make them suitable for use in hard real-time systems, as well as in traditional computing. -} {- $moduleExportIntro The SBV library exports the following modules wholesale, as user programs will have to import these three modules to make any sensible use of the SBV functionality. -}