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Bit Vector

Bit Vector. Daniel Kroening and Ofer Strichman Decision Procedure. Decision procedures. Decision procedures which we learnt.. SAT Solver BDDs Decision procedure for equality logic … However, what kind of logic do we need to express bit-wise operations and bit-wise arithmetic?

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Bit Vector

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  1. Bit Vector Daniel Kroening and OferStrichman Decision Procedure

  2. Decision procedures • Decision procedures which we learnt.. • SAT Solver • BDDs • Decision procedure for equality logic • … • However, what kind of logic do we need to express bit-wise operations and bit-wise arithmetic? • Logics which we covered can not express those kind of operations. • We need bit-vector logic.

  3. We need bit-vector logic • We need bit-vector logic • Bit-wise operators : bit-wise AND, shift … • Bit-wise arithmetic : bit addition, bit multiplication … • Since bit-vector has finite domain, so we need to consider overflow problem which can not be happened in unbounded type operations, such as integer domain. • We want to verify large formulas • Program analysis tools that generate bit-vector formulas: • CBMC • SATABS • F-Soft • …

  4. Contents • Introduction to bit-vector logic • Syntax • Semantics • Decision procedures for bit-vector logic • Flattening bit-vector logic • Incremental flattening • Conclusion

  5. Bit-vector logic syntax • Bit-vector logic syntax

  6. Semantics • Following formula obviously holds over the integer domain: • However, this equivalence no longer holds over the bit-vectors. • Subtraction operation may generate an overflow. • Example

  7. Width and Encoding • The meaning of a bit-vector formula obviously depends on • the width of the expression in bits • the encoding - whether it is signed or unsigned • Typical encodings: • Binary encoding - unsigned • Two’s complement - signed

  8. Examples • The width of the expression in bits • unsatisfiable for one bit wide bit vectors, but satisfiable for larger widths. • The encoding • means different with respect to each encoding schemes. • Notation to clarify width and encoding U: unsigned binary encoding S : signed two’s complement width in bits

  9. Definition of bit-vector • Definition. A bit vector b is a vector of bits with a given length l (or dimension) : • The i-th bit of the bit vector is denoted by … bits

  10. λ- Notation for bit-vectors • A lambda expression for a bit vector with bits has the form • is an expression that denotes the value of the i-th bit. • Example • The expression above denotes the bit vector 10101010.

  11. Examples (cond.) • The vector of length l that consists of zeros: • A function that inverts a bit vector: • A bit-wise OR:

  12. Semantics for arithmetic operators (1/3) • What is the answer for the below C program ? • On 8 bits architectures, this is 44 which is not 300. • Therefore, Bit vector arithmetic uses modular arithmetic.

  13. Semantics for arithmetic operators (2/3) • Semantics for addition and subtraction: • Semantics for relational operators:

  14. Semantics for arithmetic operators (3/3) • Semantics for shift : • logical left shift • logical right shift • arithmetic right shift - the sign bit of a is replicated

  15. Decision procedure for bit-vector • Bit-vector flattening • Most commonly used decision procedure • Transform bit-vector logic to propositional logic, which is then passed to SAT solver. • Algorithm Input : A formula in bit-vector arithmetic Output : An equisatisfiable Boolean formula Convert each term into new Boolean variable Set each bit of each term to a new Boolean variable Add constraint for each atom Add constraint for each term

  16. Example • Bit-vector formula • Convert each term into new Boolean variable • Set each bit of each term to a new Boolean variable • Add constraint for each atom • Add constraint for each term

  17. Example (l-bit Adder) • 1-bit adder can be defined as follows: • Carry bit can be defined as follows:

  18. Example (l-bit Adder) • l-bit Adder can be defined as follows: • The constraints generated by algorithm for the formula is following:

  19. Incremental bit flattening (1/4) • Some arithmetic operation result in very hard formulas • Multiplication • Multiplier is defined recursively for , where denotes the width of the second operand: • Therefore, we want to check satisfiability of a given formula without checking satisfiability of sub-formulas which have complicated arithmetic operations such as multiplication.

  20. Incremental bit flattening (2/4) • Example • This formula is obviously unsatisfiable • Since first two conjuncts are inconsistent and last two conjuncts are also inconsistent. • SAT solver wants to make a decision of first two conjuncts because a and b are used frequently than x and y. • However, this decision isn’t good because last two conjuncts are rather easy to check satisfiability since relation bit-vector operation is less complicate than multiplication bit-vector operation.

  21. Incremental bit flattening (3/4) Pick ‘easy’ part convert to CNF YES : Boolean part of : set of terms that encoded to CNF formula : set of terms that are inconsistent with the current satisfying assignment SAT UNSAT

  22. Incremental bit flattening (4/4) • Idea : add ‘easy’ parts of the formula first • Only add hard parts when needed • only gets stronger - that’s why it is incremental

  23. Conclusion • We can compute bit-wise operations and arithmetics using bit-vector logic. • There are decision procedures which check satisfiability of given bit-vector logic formula.

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