Skills-4-SE abstract-invariant-generator
Uses abstract interpretation to automatically infer loop invariants, function preconditions, and postconditions for formal verification. Generates invariants that capture program behavior and support correctness proofs in Dafny, Isabelle, Coq, and other verification systems. Use when adding formal specifications to code, generating verification conditions, inferring contracts for functions, or discovering loop invariants for proofs.
git clone https://github.com/ArabelaTso/Skills-4-SE
T=$(mktemp -d) && git clone --depth=1 https://github.com/ArabelaTso/Skills-4-SE "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/abstract-invariant-generator" ~/.claude/skills/arabelatso-skills-4-se-abstract-invariant-generator && rm -rf "$T"
skills/abstract-invariant-generator/SKILL.mdAbstract Invariant Generator
Overview
This skill uses abstract interpretation to automatically infer loop invariants, function preconditions, and postconditions. It generates formal specifications that support verification and reasoning about program correctness.
Invariant Generation Workflow
Step 1: Identify Specification Points
Analyze the code to identify where invariants are needed:
Loop Invariants: For each loop
while condition: # Need: invariant that holds before/after each iteration body
Function Contracts: For each function
def function(params): # Need: precondition (what must be true on entry) body # Need: postcondition (what is guaranteed on exit)
Assertions: For verification points
# Need: invariant that holds at this point assert property
Step 2: Perform Abstract Interpretation
Use abstract domains to infer properties:
Interval Analysis: Infer numeric ranges
i = 0 while i < n: # Inferred: 0 ≤ i < n i += 1 # Inferred: i = n
Relational Analysis: Infer relationships between variables
i = 0 j = 0 while i < n: # Inferred: i = j i += 1 j += 1
Shape Analysis: Infer data structure properties
while node is not None: # Inferred: node is in the linked list node = node.next
Step 3: Generate Loop Invariants
For each loop, generate an invariant that:
- Holds before the loop (initialization)
- Is preserved by the loop body (maintenance)
- Combined with loop exit, implies desired property (termination)
Template-Based Generation:
Counter Loop:
i = 0 while i < n: arr[i] = 0 i += 1
Generated Invariant:
invariant 0 ≤ i ≤ n invariant ∀k. 0 ≤ k < i ⟹ arr[k] = 0
Accumulator Loop:
sum = 0 i = 0 while i < len(arr): sum += arr[i] i += 1
Generated Invariant:
invariant 0 ≤ i ≤ len(arr) invariant sum = Σ(arr[0..i-1])
Search Loop:
i = 0 found = False while i < len(arr) and not found: if arr[i] == target: found = True else: i += 1
Generated Invariant:
invariant 0 ≤ i ≤ len(arr) invariant ∀k. 0 ≤ k < i ⟹ arr[k] ≠ target invariant found ⟹ arr[i] = target
Step 4: Generate Function Preconditions
Infer what must be true for the function to work correctly:
Array Access Function:
def get_element(arr, index): return arr[index]
Generated Precondition:
requires 0 ≤ index < len(arr) requires arr is not None
Division Function:
def divide(x, y): return x / y
Generated Precondition:
requires y ≠ 0
Linked List Function:
def get_next(node): return node.next
Generated Precondition:
requires node is not None
Step 5: Generate Function Postconditions
Infer what the function guarantees on exit:
Maximum Function:
def find_max(arr): max_val = arr[0] for i in range(1, len(arr)): if arr[i] > max_val: max_val = arr[i] return max_val
Generated Postcondition:
ensures result ∈ arr ensures ∀x ∈ arr. x ≤ result
Sorting Function:
def sort(arr): # ... sorting logic ... return sorted_arr
Generated Postcondition:
ensures len(result) = len(arr) ensures ∀i. 0 ≤ i < len(result)-1 ⟹ result[i] ≤ result[i+1] ensures multiset(result) = multiset(arr)
Search Function:
def binary_search(arr, target): # ... search logic ... return index
Generated Postcondition:
ensures result = -1 ∨ (0 ≤ result < len(arr) ∧ arr[result] = target) ensures result ≠ -1 ⟹ arr[result] = target ensures result = -1 ⟹ target ∉ arr
Step 6: Express in Target Language
Format invariants for the target verification system:
Dafny:
method FindMax(arr: array<int>) returns (max: int) requires arr.Length > 0 ensures max in arr[..] ensures forall i :: 0 <= i < arr.Length ==> arr[i] <= max { max := arr[0]; var i := 1; while i < arr.Length invariant 1 <= i <= arr.Length invariant max in arr[..i] invariant forall k :: 0 <= k < i ==> arr[k] <= max { if arr[i] > max { max := arr[i]; } i := i + 1; } }
Isabelle/HOL:
lemma find_max_correct: assumes "length arr > 0" shows "find_max arr ∈ set arr ∧ (∀x ∈ set arr. x ≤ find_max arr)"
Coq:
Lemma find_max_correct : forall (arr : list nat), length arr > 0 -> In (find_max arr) arr /\ (forall x, In x arr -> x <= find_max arr).
ACSL (for C):
/*@ requires n > 0; @ requires \valid(arr + (0..n-1)); @ ensures \result >= 0 && \result < n; @ ensures \forall integer k; 0 <= k < n ==> arr[k] <= arr[\result]; @*/ int find_max(int arr[], int n) { int max_idx = 0; /*@ loop invariant 1 <= i <= n; @ loop invariant 0 <= max_idx < i; @ loop invariant \forall integer k; 0 <= k < i ==> arr[k] <= arr[max_idx]; @ loop variant n - i; @*/ for (int i = 1; i < n; i++) { if (arr[i] > arr[max_idx]) { max_idx = i; } } return max_idx; }
Complete Example
Input Code (Python):
def insertion_sort(arr): for i in range(1, len(arr)): key = arr[i] j = i - 1 while j >= 0 and arr[j] > key: arr[j + 1] = arr[j] j -= 1 arr[j + 1] = key
Analysis:
Outer Loop (for i in range(1, len(arr))):
- i ranges from 1 to len(arr)
- After each iteration, arr[0..i] is sorted
- Elements are permutation of original
Inner Loop (while j >= 0 and arr[j] > key):
- j decreases from i-1 to -1
- Shifts elements greater than key to the right
- Maintains: arr[j+2..i+1] contains elements > key
Generated Invariants (Dafny):
method InsertionSort(arr: array<int>) requires arr.Length >= 0 ensures sorted(arr[..]) ensures multiset(arr[..]) == multiset(old(arr[..])) modifies arr { var i := 1; while i < arr.Length invariant 1 <= i <= arr.Length invariant sorted(arr[..i]) invariant multiset(arr[..]) == multiset(old(arr[..])) { var key := arr[i]; var j := i - 1; while j >= 0 && arr[j] > key invariant -1 <= j < i invariant sorted(arr[..j+1]) invariant sorted(arr[j+2..i+1]) invariant forall k :: j+2 <= k <= i ==> arr[k] > key invariant multiset(arr[..]) == multiset(old(arr[..])) { arr[j + 1] := arr[j]; j := j - 1; } arr[j + 1] := key; i := i + 1; } } predicate sorted(s: seq<int>) { forall i, j :: 0 <= i < j < |s| ==> s[i] <= s[j] }
Explanation:
Outer Loop Invariants:
: Loop counter bounds1 <= i <= arr.Length
: First i elements are sortedsorted(arr[..i])
: Permutation preservationmultiset(arr[..]) == multiset(old(arr[..]))
Inner Loop Invariants:
: Loop counter bounds-1 <= j < i
: Elements before j+1 remain sortedsorted(arr[..j+1])
: Shifted elements remain sortedsorted(arr[j+2..i+1])
: Shifted elements are greater than keyforall k :: j+2 <= k <= i ==> arr[k] > key
: Permutation preservationmultiset(arr[..]) == multiset(old(arr[..]))
Invariant Patterns
Numeric Bounds
invariant 0 ≤ i ≤ n invariant low ≤ mid ≤ high
Array Properties
invariant ∀k. 0 ≤ k < i ⟹ P(arr[k]) invariant sorted(arr[0..i]) invariant arr[i] = max(arr[0..i])
Relationships
invariant i + j = n invariant i = 2 * j invariant sum = Σ(arr[0..i-1])
Data Structure Properties
invariant acyclic(list) invariant node ∈ reachable(head) invariant size(tree) = n
Permutation
invariant multiset(arr) = multiset(old(arr)) invariant set(arr) = set(old(arr))
Strengthening Weak Invariants
Sometimes initial invariants are too weak. Strengthen them:
Weak:
invariant 0 ≤ i ≤ n
Strengthened:
invariant 0 ≤ i ≤ n invariant ∀k. 0 ≤ k < i ⟹ processed(arr[k])
Technique: Add properties about what has been accomplished so far.
Handling Complex Loops
Nested Loops
Generate invariants for each level:
for i in range(n): for j in range(m): matrix[i][j] = 0
Invariants:
Outer loop: invariant 0 ≤ i ≤ n invariant ∀r. 0 ≤ r < i ⟹ (∀c. 0 ≤ c < m ⟹ matrix[r][c] = 0) Inner loop: invariant 0 ≤ j ≤ m invariant ∀c. 0 ≤ c < j ⟹ matrix[i][c] = 0
Multiple Exit Conditions
Handle all exit paths:
while i < n and not found: if arr[i] == target: found = True i += 1
Invariants:
invariant 0 ≤ i ≤ n invariant found ⟹ arr[i-1] = target invariant ¬found ⟹ (∀k. 0 ≤ k < i ⟹ arr[k] ≠ target)
References
For detailed invariant generation techniques and patterns:
- references/loop_invariants.md: Loop invariant patterns and generation strategies
- references/function_contracts.md: Precondition and postcondition inference
- references/invariant_templates.md: Common invariant templates by algorithm type
- references/verification_languages.md: Syntax for different verification systems