Mock Data Generator — Kotlin source

// mock-data-generator — Kotlin port of the CosmoDev tool.
// The seeded mulberry32 PRNG (bit-identical to src/lib/mockData.ts and the Go
// twin) drives a representative field set; Int arithmetic wraps mod 2^32 (the
// Math.imul semantics) and ushr supplies the unsigned shift.
val FIRST = listOf("Ava", "Liam", "Noah", "Emma", "Olivia", "Aiden", "Sophia", "Mason")
val LAST = listOf("Smith", "Johnson", "Williams", "Brown", "Jones", "Garcia", "Miller", "Davis")

/** Closure carries the state, mirroring the TS lib's consumption order. */
fun mulberry32(seed: Int): () -> Double {
    var a = seed
    return {
        a += 0x6D2B79F5                                     // wraps: Int is mod 2^32
        var t = (a xor (a ushr 15)) * (1 or a)              // == Math.imul here
        t = (t + (t xor (t ushr 7)) * (61 or t)) xor t
        ((t xor (t ushr 14)).toLong() and 0xFFFFFFFFL) / 4294967296.0 // unsigned
    }
}

/** Representative fields from the schema dispatch in mockData.ts. */
fun field(
    type: String,
    index: Int,
    rand: () -> Double,
    min: Int = 0,
    max: Int = 100,
): Any? = when (type) {
    "index" -> index                                        // no draw
    "email" -> {                                            // two draws, like TS
        val f = FIRST[(rand() * FIRST.size).toInt()].lowercase()
        val l = LAST[(rand() * LAST.size).toInt()].lowercase()
        "$f.$l@example.com"
    }
    "integer" -> min + (rand() * (max - min + 1)).toInt()
    "boolean" -> rand() < 0.5
    else -> null                                            // unknown type -> null
}

fun main() {
    val rand = mulberry32(1234)                             // seed
    data class Spec(val name: String, val type: String, val min: Int = 0, val max: Int = 0)
    val schema = listOf(
        Spec("id", "index"),
        Spec("email", "email"),
        Spec("age", "integer", 18, 65),
        Spec("active", "boolean"),
    )

    repeat(3) { i ->                                        // count
        val row = schema.associate { it.name to field(it.type, i, rand, it.min, it.max) }
        println(row)
    }
}