More robust iteration over Vectors

Currently, if a vector is resized in the midst of iteration, then `done` might "miss" the end of iteration. This trivially changes the definition to catch such a case. I am not sure what guarantees we make about mutating iterables during iteration, but this seems simple and easy to support.  Note, though, that it is somewhat tricky: until #13866 we used `i > length(a)`, but that foils vectorization due to the `typemax` case. This definition seems to get the best of both worlds. For a definition like `f` below, this new definition just requires one extra `add i64` operation in the preamble (before the loop). Everything else is identical to master.

```julia
function f(A)
    r = 0
    @inbounds for x in A
        r += x
    end
    r
end
```

base/array.jl

@@ -642,7 +642,7 @@ end
 ## Iteration ##
 start(A::Array) = 1
 next(a::Array,i) = (@_propagate_inbounds_meta; (a[i],i+1))
-done(a::Array,i) = (@_inline_meta; i == length(a)+1)
+done(a::Array,i) = (@_inline_meta; i >= length(a)+1)
 
 ## Indexing: getindex ##
 

test/arrayops.jl

@@ -2424,6 +2424,25 @@ end
     @inferred hash([1,2,3])
 end
 
+function f27079()
+    X = rand(5)
+    for x in X
+        resize!(X, 0)
+    end
+    length(X)
+end
+function g27079(X)
+    r = 0
+    @inbounds for x in X
+        r += x
+    end
+    r
+end
+@testset "iteration over resized vector" begin
+    @test f27079() == 0
+    @test occursin("vector.body", sprint(code_llvm, g27079, Tuple{Vector{Int}}))
+end
+
 @testset "indices-related shape promotion errors" begin
     @test_throws DimensionMismatch Base.promote_shape((2,), (3,))
     @test_throws DimensionMismatch Base.promote_shape((2, 3), (2, 4))