## Dynamic-Programming

Missing docstring for `knapsack_solver`

. Check Documenter's build log for details.

Missing docstring for `lis_length`

. Check Documenter's build log for details.

Missing docstring for `minumum_operations`

. Check Documenter's build log for details.

`AlgorithmsCollection.number_of_steps`

— Function`number_of_steps(distance::Int64, step_size::Int64)`

Number of step*size is calculating the total number of combinations for walking a distance for a given number of step*size. For example, for a

`distance`

of 3 with a maximum `step_size`

of 3 will provide for possible combinations:```
- 1 step + 1 step + 1 step
- 1 step + 2 step
- 2 step + 1 step
- 3 step
```

**Arguments**

`distance::Int64`

: Distance to go`step_size::Int64`

: Maximum step size of walking a distance

**Examples**

```
julia> import ClassicAlgorithmsCollections
julia> ClassicAlgorithmsCollections.number_of_steps(8,3)
81
```

`AlgorithmsCollection.subset_sum_test`

— Function`subset_sum_test(array::Array{Int64,1}, target::Int64)`

The recursive expression tests if there is a subset in the array, where the sum of the subset is equal to the `target`

.

**Arguments**

`array::Array{Int64,1}`

: Array with a possible sum of a subsequence.`target::Int64`

: Target sum of the subsequence, which should be included in the array.

**Examples**

```
julia> import ClassicAlgorithmsCollections
julia> set = [3, 34, 4, 12, 5, 2]
julia> sum = 9
julia> ClassicAlgorithmsCollections.subset_sum_test(set, sum)
true
```