Coverage Summary for Class: StabilityUpdate (core.pipeline)

 // FILE: core/src/main/kotlin/core/pipeline/StabilityModel.kt
 package core.pipeline
 
 import core.BalanceSettings
 
 /**
  * Stability decision model.
  *
  * ## Semantic Ownership
  * Answers: **Why stability changed by X?**
  *
  * ## Stability Gradient
  * STABLE: Pure calculation logic with explicit rules.
  *
  * ## Determinism
  * - No RNG usage. All inputs are explicit.
  *
  * ## Boundary Rules
  * - Must NOT emit events.
  * - Must NOT mutate state.
  */
 object StabilityModel {
 
     /**
      * Computes stability delta from contract results.
      *
      * @param successfulReturns Number of successful auto-closes this day.
      * @param failedReturns Number of failed auto-closes this day.
      * @param oldStability Current stability value.
      * @return [StabilityUpdate] with computed changes.
      */
     fun computeFromResults(
         successfulReturns: Int,
         failedReturns: Int,
         oldStability: Int
     ): StabilityUpdate {
         val delta = successfulReturns - failedReturns
         val newStability = (oldStability + delta).coerceIn(
             BalanceSettings.STABILITY_MIN, BalanceSettings.STABILITY_MAX
         )
         val changed = newStability != oldStability
 
         return StabilityUpdate(
             oldStability = oldStability,
             newStability = newStability,
             delta = delta,
             changed = changed
         )
     }
 
     /**
      * Computes stability penalty from bad auto-resolve.
      *
      * @param badResolveCount Number of BAD bucket outcomes.
      * @param oldStability Current stability value.
      * @return [StabilityUpdate] with computed penalty.
      */
     fun computeAutoResolvePenalty(
         badResolveCount: Int,
         oldStability: Int
     ): StabilityUpdate {
         val penalty = badResolveCount * BalanceSettings.STABILITY_PENALTY_BAD_AUTO_RESOLVE
         val newStability = (oldStability - penalty).coerceIn(
             BalanceSettings.STABILITY_MIN, BalanceSettings.STABILITY_MAX
         )
         val changed = newStability != oldStability
 
         return StabilityUpdate(
             oldStability = oldStability,
             newStability = newStability,
             delta = -penalty,
             changed = changed
         )
     }
 }
 
 /**
  * Result of stability computation.
  */
 data class StabilityUpdate(
     val oldStability: Int,
     val newStability: Int,
     val delta: Int,
     val changed: Boolean
 )