# GORM

The fantastic ORM library for Golang, aims to be developer friendly.

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                withFirEntry("fir", firFunctionSymbol.firSymbol.fir)
            }
        else firFunctionSymbol.valueParameters[valueParameterReference.parameterIndex]
    )

    // Util function to avoid hard coding names of the classes. Type inference will do a better job figuring out the best type to cast to.
    // This visitor isn't type-safe anyway
    private inline fun <reified T> ConeContractDescriptionElement.accept() =

                        }
                    }
                }
            }
        }
    }
}

// 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

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

        variableReference: VariableReference,
        constructor: (KtParameterSymbol) -> T
    ): T = constructor(variableReference.descriptor.toKtSymbol(analysisContext) as KtParameterSymbol)

    // Util function to avoid hard coding names of the classes. Type inference will do a better job figuring out the best type to cast to.
    // This visitor isn't type-safe anyway

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

   There used to be two different mechanisms - one for regular S3 objects and one for IAM data.
- Reduced server startup time. For IAM encryption with the root credentials, MinIO had
   to use a memory-hard function (Argon2) that (on purpose) consumes a lot of memory and CPU.
   The new KMS-based approach can use a key derivation function that is orders of magnitudes
   cheaper w.r.t. memory and CPU.

docs/debugging/hash-set/hash-set
docs/debugging/healing-bin/healing-bin
docs/debugging/inspect/inspect
docs/debugging/pprofgoparser/pprofgoparser
docs/debugging/reorder-disks/reorder-disks
docs/debugging/populate-hard-links/populate-hardlinks

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