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why3/examples/sumrange.mlw
2018-06-15 16:45:58 +02:00

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(** {1 Range Sum Queries}
We are interested in specifying and proving correct
data structures that support efficient computation of the sum of the
values over an arbitrary range of an array.
Concretely, given an array of integers `a`, and given a range
delimited by indices `i` (inclusive) and `j` (exclusive), we wish
to compute the value: `\sum_{k=i}^{j-1} a[k]`.
In the first part, we consider a simple loop
for computing the sum in linear time.
In the second part, we introduce a cumulative sum array
that allows answering arbitrary range queries in constant time.
In the third part, we explore a tree data structure that
supports modification of values from the underlying array `a`,
with logarithmic time operations.
*)
(** {2 Specification of Range Sum} *)
module ArraySum
use int.Int
use array.Array
(** `sum a i j` denotes the sum `\sum_{i <= k < j} a[k]`.
It is axiomatizated by the two following axioms expressing
the recursive definition
if `i <= j` then `sum a i j = 0`
if `i < j` then `sum a i j = a[i] + sum a (i+1) j`
*)
let rec function sum (a:array int) (i j:int) : int
requires { 0 <= i <= j <= a.length }
variant { j - i }
= if j <= i then 0 else a[i] + sum a (i+1) j
(** lemma for summation from the right:
if `i < j` then `sum a i j = sum a i (j-1) + a[j-1]`
*)
lemma sum_right : forall a : array int, i j : int.
0 <= i < j <= a.length ->
sum a i j = sum a i (j-1) + a[j-1]
end
(** {2 First algorithm, a linear one} *)
module Simple
use int.Int
use array.Array
use ArraySum
use ref.Ref
(** `query a i j` returns the sum of elements in `a` between
index `i` inclusive and index `j` exclusive *)
let query (a:array int) (i j:int) : int
requires { 0 <= i <= j <= a.length }
ensures { result = sum a i j }
= let s = ref 0 in
for k=i to j-1 do
invariant { !s = sum a i k }
s := !s + a[k]
done;
!s
end
(** {2 Additional lemmas on `sum`}
needed in the remaining code *)
module ExtraLemmas
use int.Int
use array.Array
use ArraySum
(** summation in adjacent intervals *)
lemma sum_concat : forall a:array int, i j k:int.
0 <= i <= j <= k <= a.length ->
sum a i k = sum a i j + sum a j k
(** Frame lemma for `sum`, that is `sum a i j` depends only
of values of `a[i..j-1]` *)
lemma sum_frame : forall a1 a2 : array int, i j : int.
0 <= i <= j ->
j <= a1.length ->
j <= a2.length ->
(forall k : int. i <= k < j -> a1[k] = a2[k]) ->
sum a1 i j = sum a2 i j
(** Updated lemma for `sum`: how does `sum a i j` changes when
`a[k]` is changed for some `k` in `[i..j-1]` *)
lemma sum_update : forall a:array int, i v l h:int.
0 <= l <= i < h <= a.length ->
sum (a[i<-v]) l h = sum a l h + v - a[i]
end
(** {2 Algorithm 2: using a cumulative array}
creation of cumulative array is linear
query is in constant time
array update is linear
*)
module CumulativeArray
use int.Int
use array.Array
use ArraySum
use ExtraLemmas
predicate is_cumulative_array_for (c:array int) (a:array int) =
c.length = a.length + 1 /\
forall i. 0 <= i < c.length -> c[i] = sum a 0 i
(** `create a` builds the cumulative array associated with `a`. *)
let create (a:array int) : array int
ensures { is_cumulative_array_for result a }
= let l = a.length in
let s = Array.make (l+1) 0 in
for i=1 to l do
invariant { forall k. 0 <= k < i -> s[k] = sum a 0 k }
s[i] <- s[i-1] + a[i-1]
done;
s
(** `query c i j a` returns the sum of elements in `a` between
index `i` inclusive and index `j` exclusive, in constant time *)
let query (c:array int) (i j:int) (ghost a:array int): int
requires { is_cumulative_array_for c a }
requires { 0 <= i <= j < c.length }
ensures { result = sum a i j }
= c[j] - c[i]
(** `update c i v a` updates cell `a[i]` to value `v` and updates
the cumulative array `c` accordingly *)
let update (c:array int) (i:int) (v:int) (ghost a:array int) : unit
requires { is_cumulative_array_for c a }
requires { 0 <= i < a.length }
writes { c, a }
ensures { is_cumulative_array_for c a }
ensures { a[i] = v }
ensures { forall k. 0 <= k < a.length /\ k <> i ->
a[k] = (old a)[k] }
= let incr = v - c[i+1] + c[i] in
a[i] <- v;
for j=i+1 to c.length-1 do
invariant { forall k. j <= k < c.length -> c[k] = sum a 0 k - incr }
invariant { forall k. 0 <= k < j -> c[k] = sum a 0 k }
c[j] <- c[j] + incr
done
end
(** {2 Algorithm 3: using a cumulative tree}
creation is linear
query is logarithmic
update is logarithmic
*)
module CumulativeTree
use int.Int
use array.Array
use ArraySum
use ExtraLemmas
use int.ComputerDivision
type indexes =
{ low : int;
high : int;
isum : int;
}
type tree = Leaf indexes | Node indexes tree tree
let function indexes (t:tree) : indexes =
match t with
| Leaf ind -> ind
| Node ind _ _ -> ind
end
predicate is_indexes_for (ind:indexes) (a:array int) (i j:int) =
ind.low = i /\ ind.high = j /\
0 <= i < j <= a.length /\
ind.isum = sum a i j
predicate is_tree_for (t:tree) (a:array int) (i j:int) =
match t with
| Leaf ind ->
is_indexes_for ind a i j /\ j = i+1
| Node ind l r ->
is_indexes_for ind a i j /\
i = l.indexes.low /\ j = r.indexes.high /\
let m = l.indexes.high in
m = r.indexes.low /\
i < m < j /\ m = div (i+j) 2 /\
is_tree_for l a i m /\
is_tree_for r a m j
end
(** {3 creation of cumulative tree} *)
let rec tree_of_array (a:array int) (i j:int) : tree
requires { 0 <= i < j <= a.length }
variant { j - i }
ensures { is_tree_for result a i j }
= if i+1=j then begin
Leaf { low = i; high = j; isum = a[i] }
end
else
begin
let m = div (i+j) 2 in
assert { i < m < j };
let l = tree_of_array a i m in
let r = tree_of_array a m j in
let s = l.indexes.isum + r.indexes.isum in
assert { s = sum a i j };
Node { low = i; high = j; isum = s} l r
end
let create (a:array int) : tree
requires { a.length >= 1 }
ensures { is_tree_for result a 0 a.length }
= tree_of_array a 0 a.length
(** {3 query using cumulative tree} *)
let rec query_aux (t:tree) (ghost a: array int)
(i j:int) : int
requires { is_tree_for t a t.indexes.low t.indexes.high }
requires { 0 <= t.indexes.low <= i < j <= t.indexes.high <= a.length }
variant { t }
ensures { result = sum a i j }
= match t with
| Leaf ind ->
ind.isum
| Node ind l r ->
let k1 = ind.low in
let k3 = ind.high in
if i=k1 && j=k3 then ind.isum else
let m = l.indexes.high in
if j <= m then query_aux l a i j else
if i >= m then query_aux r a i j else
query_aux l a i m + query_aux r a m j
end
let query (t:tree) (ghost a: array int) (i j:int) : int
requires { 0 <= i <= j <= a.length }
requires { is_tree_for t a 0 a.length }
ensures { result = sum a i j }
= if i=j then 0 else query_aux t a i j
(** frame lemma for predicate `is_tree_for` *)
lemma is_tree_for_frame : forall t:tree, a:array int, k v i j:int.
0 <= k < a.length ->
k < i \/ k >= j ->
is_tree_for t a i j ->
is_tree_for t a[k<-v] i j
(** {3 update cumulative tree} *)
let rec update_aux
(t:tree) (i:int) (ghost a :array int) (v:int) : (t': tree, delta: int)
requires { is_tree_for t a t.indexes.low t.indexes.high }
requires { t.indexes.low <= i < t.indexes.high }
variant { t }
ensures {
delta = v - a[i] /\
t'.indexes.low = t.indexes.low /\
t'.indexes.high = t.indexes.high /\
is_tree_for t' a[i<-v] t'.indexes.low t'.indexes.high }
= match t with
| Leaf ind ->
assert { i = ind.low };
(Leaf { ind with isum = v }, v - ind.isum)
| Node ind l r ->
let m = l.indexes.high in
if i < m then
let l',delta = update_aux l i a v in
assert { is_tree_for l' a[i<-v] t.indexes.low m };
assert { is_tree_for r a[i<-v] m t.indexes.high };
(Node {ind with isum = ind.isum + delta } l' r, delta)
else
let r',delta = update_aux r i a v in
assert { is_tree_for l a[i<-v] t.indexes.low m };
assert { is_tree_for r' a[i<-v] m t.indexes.high };
(Node {ind with isum = ind.isum + delta} l r',delta)
end
let update (t:tree) (ghost a:array int) (i v:int) : tree
requires { 0 <= i < a.length }
requires { is_tree_for t a 0 a.length }
writes { a }
ensures { a[i] = v }
ensures { forall k. 0 <= k < a.length /\ k <> i -> a[k] = (old a)[k] }
ensures { is_tree_for result a 0 a.length }
= let t,_ = update_aux t i a v in
assert { is_tree_for t a[i <- v] 0 a.length };
a[i] <- v;
t
(** {2 complexity analysis}
We would like to prove that `query` is really logarithmic. This is
non-trivial because there are two recursive calls in some cases.
So far, we are only able to prove that `update` is logarithmic
We express the complexity by passing a "credit" as a ghost
parameter. We pose the precondition that the credit is at least
equal to the depth of the tree.
*)
(** preliminaries: definition of the depth of a tree, and showing
that it is indeed logarithmic in function of the number of its
elements *)
use int.MinMax
function depth (t:tree) : int =
match t with
| Leaf _ -> 1
| Node _ l r -> 1 + max (depth l) (depth r)
end
lemma depth_min : forall t. depth t >= 1
use bv.Pow2int
let rec lemma depth_is_log (t:tree) (a :array int) (k:int)
requires { k >= 0 }
requires { is_tree_for t a t.indexes.low t.indexes.high }
requires { t.indexes.high - t.indexes.low <= pow2 k }
variant { t }
ensures { depth t <= k+1 }
= match t with
| Leaf _ -> ()
| Node _ l r ->
depth_is_log l a (k-1);
depth_is_log r a (k-1)
end
(** `update_aux` function instrumented with a credit *)
use ref.Ref
let rec update_aux_complexity
(t:tree) (i:int) (ghost a :array int)
(v:int) (ghost c:ref int) : (t': tree, delta: int)
requires { is_tree_for t a t.indexes.low t.indexes.high }
requires { t.indexes.low <= i < t.indexes.high }
variant { t }
ensures { !c - old !c <= depth t }
ensures {
delta = v - a[i] /\
t'.indexes.low = t.indexes.low /\
t'.indexes.high = t.indexes.high /\
is_tree_for t' a[i<-v] t'.indexes.low t'.indexes.high }
= c := !c + 1;
match t with
| Leaf ind ->
assert { i = ind.low };
(Leaf { ind with isum = v }, v - ind.isum)
| Node ind l r ->
let m = l.indexes.high in
if i < m then
let l',delta = update_aux_complexity l i a v c in
assert { is_tree_for l' a[i<-v] t.indexes.low m };
assert { is_tree_for r a[i<-v] m t.indexes.high };
(Node {ind with isum = ind.isum + delta } l' r, delta)
else
let r',delta = update_aux_complexity r i a v c in
assert { is_tree_for l a[i<-v] t.indexes.low m };
assert { is_tree_for r' a[i<-v] m t.indexes.high };
(Node {ind with isum = ind.isum + delta} l r',delta) (*>*)
end
(** `query_aux` function instrumented with a credit *)
let rec query_aux_complexity (t:tree) (ghost a: array int)
(i j:int) (ghost c:ref int) : int
requires { is_tree_for t a t.indexes.low t.indexes.high }
requires { 0 <= t.indexes.low <= i < j <= t.indexes.high <= a.length }
variant { t }
ensures { !c - old !c <=
if i = t.indexes.low /\ j = t.indexes.high then 1 else
if i = t.indexes.low \/ j = t.indexes.high then 2 * depth t else
4 * depth t }
ensures { result = sum a i j }
= c := !c + 1;
match t with
| Leaf ind ->
ind.isum
| Node ind l r ->
let k1 = ind.low in
let k3 = ind.high in
if i=k1 && j=k3 then ind.isum else
let m = l.indexes.high in
if j <= m then query_aux_complexity l a i j c else
if i >= m then query_aux_complexity r a i j c else
query_aux_complexity l a i m c + query_aux_complexity r a m j c
end
end