//	#define A #define B(x) x
	// and
	//	#define A #define B (x) x
	// The first definition of B has an argument, the second doesn't. Because we let
	// text/scanner strip the blanks for us, this is extremely rare, hard to fix, and not worth it.
	return s.pos
}

func (s *Slice) Close() {

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 asciidoc 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.)
   */

   */
  /*
   * 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.)
   */

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?

                        }
                    }
                }
            }
        }
    }
}

// run the parallel ITs
parallel(runITsTasks)

// JENKINS-34376 seems to make it hard to detect the aborted builds
} catch (org.jenkinsci.plugins.workflow.steps.FlowInterruptedException e) {
    echo "[FAILURE-002] FlowInterruptedException ${e}"
    // this ambiguous condition means a user probably aborted

		}
	}
	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{

  url: https://github.com/alejsdev
- login: hard-coders
  count: 10
  avatarUrl: https://avatars.githubusercontent.com/u/9651103?u=95db33927bbff1ed1c07efddeb97ac2ff33068ed&v=4
  url: https://github.com/hard-coders
- login: KaniKim
  count: 10
  avatarUrl: https://avatars.githubusercontent.com/u/19832624?u=40f8f7f3f36d5f2365ba2ad0b40693e60958ce70&v=4