hoare-logic-verifier

name: hoare-logic-verifier description: 'Verifies programs using Hoare logic. Use when: (1) Proving program correctness, (2) Designing verified software, (3) Verifying loop invariants.' version: 1.0.0 tags:

• verification
• hoare-logic
• program-proving
• correctness difficulty: intermediate languages:
• python
• coq
• why3 dependencies:
• operational-semantics-definer

Hoare Logic Verifier

Verifies program correctness using Floyd-Hoare logic.

When to Use

• Proving program correctness
• Developing verified software
• Verifying loop invariants
• Static verification

What This Skill Does

1. Specifies contracts - Pre/postconditions and loop invariants
2. Generates verification conditions - Formulas to prove
3. Checks soundness - Proves VCs are valid
4. Handles loops - Invariant inference

Key Concepts

Verification Condition Generation

{P} while b do c {Q}

VCs:
1. P ⇒ I                    (initiation)
2. I ∧ b ⇒ wp(c, I)         (preservation)  
3. I ∧ ¬b ⇒ Q               (usefulness)

Tips

• Start with simple programs, add complexity
• Always verify loop invariants manually first
• Use consequences to strengthen/weaken
• Consider using SMT solvers for complex conditions
• Handle division carefully (non-zero)

Common Patterns

Swap

{ x = a ∧ y = b }
t := x;
x := y;
y := t;
{ x = b ∧ y = a }

Linear Search

{ ∃i. A[i] = k ∧ 0 ≤ i < n }
i := 0;
while i < n do
    if A[i] = k then break;
    i := i + 1
{ (i < n ⇒ A[i] = k) ∧ (i = n ⇒ ∀j. 0≤j<n ⇒ A[j] ≠ k) }

Related Skills

• separation-logician - Heap verification
• invariant-generator - Automatic invariant inference
• loop-termination-prover - Prove termination

Canonical References

Tradeoffs and Limitations

Approach Tradeoffs

When NOT to Use Hoare Logic

• For concurrent programs: Use concurrent separation logic
• For pointer-heavy code: Use separation logic instead
• For automated verification: Consider model checking
• For large codebases: Consider symbolic execution + testing

Complexity Considerations

• VC generation: O(n) in program size
• SMT solving: Expensive for complex formulas; undecidable in general
• Invariant inference: NP-hard in general

Limitations

• Loop invariants: Must be provided manually (undecidable to find)
• Frame problem: Hard to specify what doesn't change; use separation logic
• Partial correctness: Standard Hoare logic proves partial correctness (no termination)
• Scalability: Manual proof effort grows with program size
• Concurrency: Requires extensions (concurrent separation logic)

Research Tools & Artifacts

Verification tools based on Hoare logic:

Interactive Theorem Provers

• Coq - Proof assistant, VST for C
• Isabelle/HOL - General purpose
• Lean - Functional verification
• Agda - Dependent types

Research Frontiers

1. Verification Condition Generation

• Goal: Automate proof effort
• Approach: Generate VCs, discharge with SMT
• Papers: "VCGen for Dummies" (various)
• Tools: Boogie, Why3

2. Loop Invariant Inference

• Goal: Automatically find invariants
• Approach: Abstract interpretation, learning
• Papers: "Invariant Generation" (Sankaranarayanan)
• Tools: Abstract interpretation tools

3. Separation Logic

• Goal: Handle heap and pointers
• Approach: Local reasoning, frame rule
• Papers: "Separation Logic" (O'Hearn, Reynolds)
• Tools: Verifiable C, Smallfoot

4. Concurrent Verification

• Goal: Verify concurrent programs
• Approach: Concurrent separation logic
• Papers: "Concurrent Separation Logic" (O'Hearn)
• Tools: Verifast, Grain

Implementation Pitfalls

The "Loop Invariant" Challenge

Finding invariants is undecidable:

# What invariant proves this?
i = 0
sum = 0
while i < n:
    sum = sum + i
    i = i + 1

# Answer: sum = i*(i-1)/2

# Another valid invariant: 0 <= i <= n AND sum >= 0
# But this is too weak to prove final result!

This is why verification requires human insight!