We use *Specification* and *Discovery* documents stored in Google Drive, but they present some downsides:

* They are rarely updated after creation and initial review, and then become hard to follow, especially after important decisions are made
* They are not synced with the code to reflect the eventual solution that is committed
* Google Docs is not a "code-oriented" tool, like Markdown can be

   * gigantic heap, in which case we scale by heap size.
   */
  private static long timeoutSeconds() {
    // This class can make no hard guarantees.  The methods in this class are inherently flaky, but
    // we try hard to make them robust in practice.  We could additionally try to add in a system
    // load timeout multiplier.  Or we could try to use a CPU time bound instead of wall clock time

   * gigantic heap, in which case we scale by heap size.
   */
  private static long timeoutSeconds() {
    // This class can make no hard guarantees.  The methods in this class are inherently flaky, but
    // we try hard to make them robust in practice.  We could additionally try to add in a system
    // load timeout multiplier.  Or we could try to use a CPU time bound instead of wall clock time

   */
  /*
   * The new array contains nulls, even if the old array did not. If we wanted to be accurate, we
   * would declare a return type of `@Nullable T[]`. However, we've decided not to think too hard
   * about arrays for now, as they're a mess. (We previously discussed this in the review of
   * ObjectArrays, which is the main caller of this method.)
   */

    avatarUrl: https://avatars.githubusercontent.com/u/9536869?u=652dd0d49717803c0cbcbf44f7740e53cf2d4892&v=4
    url: https://github.com/DMantis
  - login: hard-coders
    avatarUrl: https://avatars.githubusercontent.com/u/9651103?u=95db33927bbff1ed1c07efddeb97ac2ff33068ed&v=4
    url: https://github.com/hard-coders
  - login: mntolia
    avatarUrl: https://avatars.githubusercontent.com/u/10390224?v=4
    url: https://github.com/mntolia
  - login: Zuzah

   */
  /*
   * The new array contains nulls, even if the old array did not. If we wanted to be accurate, we
   * would declare a return type of `@Nullable T[]`. However, we've decided not to think too hard
   * about arrays for now, as they're a mess. (We previously discussed this in the review of
   * ObjectArrays, which is the main caller of this method.)
   */

* full-stack: full-stack (do not translate to "de pila completa")
* stack: stack (do not translate to "pila")
* loop (as in async loop): loop (do not translate to "bucle" or "ciclo")
* hard dependencies: dependencias obligatorias (do not translate to "dependencias duras")
* locking: locking (do not translate to "bloqueo")
* testing (as in software testing): escribir pruebas (do not translate to "probar")

Bit Rot, also known as data rot or silent data corruption is a data loss issue faced by disk drives today. Data on the drive may silently get corrupted without signaling an error has occurred, making bit rot more dangerous than a permanent hard drive failure.

MinIO's erasure coded backend uses high speed [HighwayHash](https://github.com/minio/highwayhash) checksums to protect against Bit Rot.

## How are drives used for Erasure Code?

	return tillOffset
}

// erasureSelfTest performs a self-test to ensure that erasure
// algorithms compute expected erasure codes. If any algorithm
// produces an incorrect value it fails with a hard error.
//
// erasureSelfTest tries to catch any issue in the erasure implementation
// early instead of silently corrupting data.
func erasureSelfTest() {
	// Approx runtime ~1ms
	var testConfigs [][2]uint8

		}
	}
	return nil
}

// bitrotSelfTest performs a self-test to ensure that bitrot
// algorithms compute correct checksums. If any algorithm
// produces an incorrect checksum it fails with a hard error.
//
// bitrotSelfTest tries to catch any issue in the bitrot implementation
// early instead of silently corrupting data.
func bitrotSelfTest() {
	checksums := map[BitrotAlgorithm]string{