diff --git a/.jules/bolt.md b/.jules/bolt.md
index 7d3c603..31b25c1 100644
--- a/.jules/bolt.md
+++ b/.jules/bolt.md
@@ -16,3 +16,7 @@
 ## 2025-02-12 - R 언어에서 반복적인 mirt 모델 생성 시 불필요한 데이터프레임 부분집합 추출 최적화
 **Learning:** R에서 데이터프레임의 특정 열을 추출하는 작업(`df[cols]`)은 O(N)의 메모리 복사를 수반합니다. `autoFIPC`에서 `mirt` 모델의 파라미터를 설정하거나 호출하는 과정 중에 `newformXDataK[colnames(newFormModel@Data$data)]` 코드가 반복해서 사용되었고, 심지어 `ncol()`을 위해 단순히 개수를 구할 때도 사용되어 불필요한 메모리 할당과 오버헤드를 초래했습니다.
 **Action:** 조건문이나 반복문 내부에서 불필요하게 데이터프레임 부분집합 연산이 반복되지 않도록 외부에서 한 번만 `linkedFormData <- newformXDataK[colnames(newFormModel@Data$data)]`로 캐싱(caching)한 뒤, `ncol(linkedFormData)`와 `data = linkedFormData` 형태로 재사용하여 메모리 복사와 O(N) 오버헤드를 방지해야 합니다.
+
+## 2024-05-13 - Subsetting Refactoring
+**Learning:** In R, updating a specific column based on a conditional match is significantly faster using direct vector subsetting (e.g., `df$col[df$idx == 'val'] <- new_val`) compared to two-dimensional subsetting (e.g., `df[df$idx == 'val', 'col'] <- new_val`) because it avoids row/column matching overhead and intermediate object creation.
+**Action:** Use 1D vector subsetting when conditionally updating columns in R dataframe in a performance-critical loop.
diff --git a/R/aFIPC.R b/R/aFIPC.R
index 6254651..3d80da7 100644
--- a/R/aFIPC.R
+++ b/R/aFIPC.R
@@ -598,15 +598,17 @@ autoFIPC <-
     # Preserve mirt's structural estimability flags. Forcing every row TRUE
     # frees boundary parameters such as 2PL g/u and makes the Hessian unstable.
 
-    NewScaleParms[NewScaleParms$item == 'GROUP', "est"] <- FALSE
-    OldScaleParms[OldScaleParms$item == 'GROUP', "est"] <- FALSE
+    # ⚡ Bolt: Optimizing 2D dataframe subsetting to 1D vector subsetting
+    # This avoids intermediate object creations and row/column matching overhead
+    NewScaleParms$est[NewScaleParms$item == 'GROUP'] <- FALSE
+    OldScaleParms$est[OldScaleParms$item == 'GROUP'] <- FALSE
 
-    NewScaleParms[NewScaleParms$name == "COV_11", "est"] <- TRUE
-    OldScaleParms[OldScaleParms$name == "COV_11", "est"] <- TRUE
+    NewScaleParms$est[NewScaleParms$name == "COV_11"] <- TRUE
+    OldScaleParms$est[OldScaleParms$name == "COV_11"] <- TRUE
 
     if (itemtype == 'Rasch') {
-      NewScaleParms[NewScaleParms$name == "a1", "est"] <- FALSE
-      OldScaleParms[OldScaleParms$name == "a1", "est"] <- FALSE
+      NewScaleParms$est[NewScaleParms$name == "a1"] <- FALSE
+      OldScaleParms$est[OldScaleParms$name == "a1"] <- FALSE
     }
 
     #IPD
@@ -786,14 +788,15 @@ autoFIPC <-
         oldIdx <- oldScaleParmsItemIdxCache[[oldFormItemStr]]
 
         # ⚡ Bolt: Remove unnecessary paste0() array string generation overhead
-        message('   Newform Parms: ', paste(NewScaleParms[newIdx, "value"], collapse = ' '))
-        message('   Oldform Parms: ', paste(OldScaleParms[oldIdx, "value"], collapse = ' '))
+        message('   Newform Parms: ', paste(NewScaleParms$value[newIdx], collapse = ' '))
+        message('   Oldform Parms: ', paste(OldScaleParms$value[oldIdx], collapse = ' '))
 
-        NewScaleParms[newIdx, "value"] <-
-          OldScaleParms[oldIdx, "value"]
-        message('   Linkedform Parms: ', paste(NewScaleParms[newIdx, "value"], collapse = ' '), '\n')
+        # ⚡ Bolt: Optimizing 2D dataframe subsetting to 1D vector subsetting
+        NewScaleParms$value[newIdx] <-
+          OldScaleParms$value[oldIdx]
+        message('   Linkedform Parms: ', paste(NewScaleParms$value[newIdx], collapse = ' '), '\n')
 
-        NewScaleParms[newIdx, "est"] <-
+        NewScaleParms$est[newIdx] <-
           FALSE
       } else {
         message(
@@ -813,9 +816,10 @@ autoFIPC <-
       newBetaIdx <- NewScaleParms$item == 'BETA'
       oldBetaIdx <- OldScaleParms$item == 'BETA'
 
-      NewScaleParms[newBetaIdx, "value"] <-
-        OldScaleParms[oldBetaIdx, "value"]
-      NewScaleParms[newBetaIdx, "est"] <-
+      # ⚡ Bolt: Optimizing 2D dataframe subsetting to 1D vector subsetting
+      NewScaleParms$value[newBetaIdx] <-
+        OldScaleParms$value[oldBetaIdx]
+      NewScaleParms$est[newBetaIdx] <-
         FALSE
 
       message('applying BETA parameter as linking')
@@ -823,7 +827,7 @@ autoFIPC <-
       message(
         '   Linkedform Parms: ',
         paste0(
-          NewScaleParms[newBetaIdx, "value"],
+          NewScaleParms$value[newBetaIdx],
           ' '
         ),
         '\n'
@@ -858,13 +862,14 @@ autoFIPC <-
       new_mean11_idx <- NewScaleParms$name == "MEAN_11"
       old_mean11_idx <- OldScaleParms$name == "MEAN_11"
 
-      NewScaleParms[new_cov11_idx, "est"] <- FALSE
-      OldScaleParms[old_cov11_idx, "est"] <- FALSE
-      NewScaleParms[new_mean11_idx, "est"] <- FALSE
-      OldScaleParms[old_mean11_idx, "est"] <- FALSE
+      # ⚡ Bolt: Optimizing 2D dataframe subsetting to 1D vector subsetting
+      NewScaleParms$est[new_cov11_idx] <- FALSE
+      OldScaleParms$est[old_cov11_idx] <- FALSE
+      NewScaleParms$est[new_mean11_idx] <- FALSE
+      OldScaleParms$est[old_mean11_idx] <- FALSE
 
-      NewScaleParms[new_cov11_idx, "value"] <- 1
-      OldScaleParms[old_mean11_idx, "value"] <- 0
+      NewScaleParms$value[new_cov11_idx] <- 1
+      OldScaleParms$value[old_mean11_idx] <- 0
     }
     if (freeMEAN == T) {
       LinkedModelSyntax <-
@@ -875,8 +880,9 @@ autoFIPC <-
           'MEAN = F1'
         ))
 
-      NewScaleParms[NewScaleParms$name == "MEAN_1", "est"] <- TRUE
-      OldScaleParms[OldScaleParms$name == "MEAN_1", "est"] <- TRUE
+      # ⚡ Bolt: Optimizing 2D dataframe subsetting to 1D vector subsetting
+      NewScaleParms$est[NewScaleParms$name == "MEAN_1"] <- TRUE
+      OldScaleParms$est[OldScaleParms$name == "MEAN_1"] <- TRUE
     } else {
       LinkedModelSyntax <-
         mirt::mirt.model(paste0(