# Understanding btime

**URL:** <https://discourse.julialang.org/t/understanding-btime/75468>\
**Category:** General Usage\
**Tags:** benchmarktools\
**Created:** [January 30, 2022, 2:42pm UTC](https://discourse.julialang.org/t/understanding-btime/75468 "2022-01-30T14:42:04Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![iskyd](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/iskyd/32/44797_2.png) [@iskyd](https://discourse.julialang.org/u/iskyd)\
**Post date:** [January 30, 2022, 2:42pm UTC](https://discourse.julialang.org/t/understanding-btime/75468/1 "2022-01-30T14:42:04Z")

</div>

I’ve implemented insertion sort and merge sort and I’m trying to run a benchmark between the two using @btime from BenchmarkTools

```julia
input = rand(1:1000, 1000000)
println("Insertion sort on random array of size ", length(input))
@time output = insertion_sort(input)

input = rand(1:1000, 1000000)
println("Merge sort on random array of size ", length(input))
@time output = merge_sort!(input, 1, length(input))

```

I got from @btime that insertion sort runs in 862.916 μs (0 allocations: 0 bytes) while merge sort 129.066 ms. And well, that’s impossibile. Running the two algorithms I can see (by the time i watch the terminal expecting for the output) that insertion sort is by far slower than merge sort (as expected since insertion sort is O(n^2) and merge\_sort is O(nlogn)).

If I ran the same code using @time instead of @btime I got

> Insertion sort on random array of size 1000000  
> 161.143262 seconds (18.99 k allocations: 1.062 MiB, 0.01% compilation time)  
> Merge sort on random array of size 1000000  
> 0.188673 seconds (4.02 M allocations: 670.534 MiB, 12.13% gc time, 4.99% compilation time)

Here’s the whole code: [Insertion Sort vs Merge Sort · GitHub](https://gist.github.com/iskyd/0410ca63e7b066a6d6afdd753e51389c)

Why is this happening?

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<div class="post-metadata">

**Author:** ![lmiq](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lmiq/32/18314_2.png) [@lmiq](https://discourse.julialang.org/u/lmiq)\
**Post date:** [January 30, 2022, 2:50pm UTC](https://discourse.julialang.org/t/understanding-btime/75468/2 "2022-01-30T14:50:19Z")

</div>

`@btime` runs the code multiple times to obtain a good estimate of the time, and if the array is already sorted the second time, the benchmark is probably meaningless. To avoid that (if that is the problem, I didn’t look closely), you can reset the array at each run within `@btime` with:

```julia
input = rand(1:1000,1000000)
@btime merge_sort!(x, 1, length(x)) setup=(x=copy($input)) evals=1

```

(see [Manual · BenchmarkTools.jl](https://juliaci.github.io/BenchmarkTools.jl/dev/manual/#Benchmark-Parameters))