CLRS implementation (opportunity to sort subarray) of merge sort in golang
I'm reading "Introduction to Algorithms" by CLRS and I can't find an
  implementation of the pseudo code from the book in golang.




Here is my Go implementation of the pseudocode from the book.

package main

import (
    "fmt"
    "math"
)

// Introduction to Algorithms
// Third Edition
// Cormen, Leiserson, Rivest, Stein

func merge(a []float64, p, q, r int) {
    nLeft := q - p + 1
    nRight := r - q
    t := make([]float64, (nLeft+1)+(nRight+1))
    left := t[:nLeft+1]
    right := t[nLeft+1:]
    copy(left[:nLeft], a[p:])
    copy(right[:nRight], a[q+1:])
    left[nLeft] = math.Inf(0)
    right[nRight] = math.Inf(0)

    i, j := 0, 0
    for k := p; k &lt;= r; k++ {
        if left[i] &lt;= right[j] {
            a[k] = left[i]
            i++
        } else {
            a[k] = right[j]
            j++
        }
    }
}

// MergeSort sorts the slice a[p:r+1] in nondecreasing order.
func MergeSort(a []float64, p, r int) {
    if p &lt; r {
        q := (p + r) / 2
        MergeSort(a, p, q)
        MergeSort(a, q+1, r)
        merge(a, p, q, r)
    }
}

func main() {
    a := []float64{9: 2, 4, 5, 7, 1, 2, 3, 6}
    fmt.Println(a)
    MergeSort(a, 9, 16)
    fmt.Println(a)
}






This is a real-world code review: Code should be correct, maintainable, robust, reasonably efficient, and, most importantly, readable.

Your code is not readable. Your code does not closely follow the pseudocode. For example, you deleted the n1 and n2 pseudocode variables:

n1 = q - p + 1
n2 = r - q


As a result, your code is very inefficient. Your code is off-by-one.


  The Go Programming Language
  Specification
  
  Appending to and copying
  slices
  
  The variadic function append appends zero or more values x to s of
  type S, which must be a slice type, and returns the resulting slice,
  also of type S. ... If the capacity of s is not large enough to fit
  the additional values, append allocates a new, sufficiently large
  underlying array that fits both the existing slice elements and the
  additional values. Otherwise, append re-uses the underlying array.


For left and right subarrays, you allocate slice with a capacity equal to the number of elements, then you immediately append a sentinel value. This allocates a new slice and copies the old values from the old slice to the new slice.

In my code, I renamed n1 and n2 to a more readable nLeft and nRight. In my code, I minimized the number and size of allocations.

A benchmark (1000 random elements) for my code

$ go test msort.go msort_test.go -bench=. -benchmem
BenchmarkMSort-4  18720   64849 ns/op   98048 B/op   999 allocs/op


versus a benchmark (1000 random elements) for your code

$ go test msort.go msort_test.go -bench=. -benchmem
BenchmarkMSort-4   6996  150493 ns/op  242880 B/op  3996 allocs/op