What is the Computational Complexity of the `append` Function in Go?

How Complex is the append Computation in Go Programming Language?

The append operation in Go programming language is responsible for adding one or more elements to the end of a slice. Understanding its computational complexity is crucial for optimizing code performance.

Computational Complexity

The Go Programming Language Specification defines that append operates in amortized constant time. This means that, on average, the time taken to append an element remains constant, regardless of the slice's size.

Implementation Details

The precise implementation of append is compiler-dependent. For example, the gc compiler uses a dynamic array with an amortized constant time algorithm, while the gccgo compiler may differ in its implementation details.

Dynamic Array

The Go runtime uses a dynamic array to implement slices internally. This array may require reallocation and copying of data when new elements are appended. To minimize this cost, the runtime implements a doubling algorithm that efficiently allocates new memory when necessary.

Reallocation

The append function checks if there is enough capacity in the existing slice to accommodate the new elements before appending them. If the capacity is insufficient, the slice is reallocated, and the existing data is copied to the new location.

Parsimonious Reallocation

While the gc compiler uses a generous approach to memory allocation, it's possible to create a parsimonious append implementation that minimizes reallocation overhead. This trade-off between performance and memory usage depends on the specific application requirements.

Benchmarking Different Implementations

The provided code example demonstrates the different reallocation behaviors of the gc, gccgo, constant (generous), and variable (parsimonious) append implementations. The output shows that the gc and gccgo compilers employ amortized constant time algorithms, while the constant and variable implementations can be either generous or parsimonious in their reallocation strategy.

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