diff --git a/.jules/bolt.md b/.jules/bolt.md
index 7d3c603..e0b99dd 100644
--- a/.jules/bolt.md
+++ b/.jules/bolt.md
@@ -16,3 +16,6 @@
 ## 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.
+## 2026-07-20 - R 언어에서 데이터프레임 서브셋팅 시 직접 벡터 참조(Direct Vector Subsetting) 최적화
+**Learning:** R에서 `df[condition, "column"] <- value` 같은 2차원 서브셋팅(two-dimensional subsetting)은 S3 메서드 디스패치와 데이터프레임 차원 검사를 수행합니다. 직접 열 할당은 이 고정 오버헤드를 줄이지만, 논리 인덱스 계산과 copy-on-modify 비용은 데이터 크기에 비례하므로 시간 복잡도는 O(N)으로 유지됩니다.
+**Action:** `mirt::mod2values()` 결과를 data.frame과 필수 열 스키마로 명시적 검증한 뒤 `df$column[condition] <- value` 형태의 직접 열 할당을 사용합니다. 기존 2차원 할당과 결과·속성이 동일한지는 대표 파라미터 테이블과 Rasch 분기 회귀 테스트로 보존합니다.
diff --git a/R/aFIPC.R b/R/aFIPC.R
index 6254651..180885b 100644
--- a/R/aFIPC.R
+++ b/R/aFIPC.R
@@ -1,3 +1,45 @@
+.validate_scale_parameter_table <- function(parameters, label) {
+  if (!is.data.frame(parameters)) {
+    stop(
+      sprintf("Security Error: %s parameter table must be a data.frame", label),
+      call. = FALSE
+    )
+  }
+
+  required_columns <- c("item", "name", "value", "est")
+  missing_columns <- setdiff(required_columns, names(parameters))
+  if (length(missing_columns) > 0) {
+    stop(
+      sprintf(
+        "Security Error: %s parameter table is missing required column(s): %s",
+        label,
+        paste(missing_columns, collapse = ", ")
+      ),
+      call. = FALSE
+    )
+  }
+
+  invisible(parameters)
+}
+
+.prepare_scale_parameters <- function(new_parameters, old_parameters, itemtype) {
+  .validate_scale_parameter_table(new_parameters, "new-form")
+  .validate_scale_parameter_table(old_parameters, "old-form")
+
+  new_parameters$est[new_parameters$item == 'GROUP'] <- FALSE
+  old_parameters$est[old_parameters$item == 'GROUP'] <- FALSE
+
+  new_parameters$est[new_parameters$name == "COV_11"] <- TRUE
+  old_parameters$est[old_parameters$name == "COV_11"] <- TRUE
+
+  if (itemtype == 'Rasch') {
+    new_parameters$est[new_parameters$name == "a1"] <- FALSE
+    old_parameters$est[old_parameters$name == "a1"] <- FALSE
+  }
+
+  list(new = new_parameters, old = old_parameters)
+}
+
 #' automated fixed item parameter linking
 #'
 #' @import mirt
@@ -64,7 +106,7 @@ autoFIPC <-
       if (!isS4(x) || !methods::is(x, "SingleGroupClass")) return(FALSE)
       ok <- tryCatch({
         vals <- mirt::mod2values(x)
-        is.data.frame(vals) || is.matrix(vals)
+        is.data.frame(vals)
       }, error = function(e) FALSE, warning = function(w) FALSE)
       if (!isTRUE(ok)) return(FALSE)
       required_slots <- c("OptimInfo", "ParObjects")
@@ -597,17 +639,14 @@ 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
-
-    NewScaleParms[NewScaleParms$name == "COV_11", "est"] <- TRUE
-    OldScaleParms[OldScaleParms$name == "COV_11", "est"] <- TRUE
-
-    if (itemtype == 'Rasch') {
-      NewScaleParms[NewScaleParms$name == "a1", "est"] <- FALSE
-      OldScaleParms[OldScaleParms$name == "a1", "est"] <- FALSE
-    }
+    prepared_parameters <- .prepare_scale_parameters(
+      NewScaleParms,
+      OldScaleParms,
+      itemtype
+    )
+    NewScaleParms <- prepared_parameters$new
+    OldScaleParms <- prepared_parameters$old
+    rm(prepared_parameters)
 
     #IPD
     if (checkIPD == T) {
@@ -785,15 +824,15 @@ autoFIPC <-
         newIdx <- newScaleParmsItemIdxCache[[newFormItemStr]]
         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 = ' '))
+        # ⚡ Bolt: Use cached rows with direct column access to avoid 2D dispatch
+        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')
+        NewScaleParms$value[newIdx] <-
+          OldScaleParms$value[oldIdx]
+        message('   Linkedform Parms: ', paste(NewScaleParms$value[newIdx], collapse = ' '), '\n')
 
-        NewScaleParms[newIdx, "est"] <-
+        NewScaleParms$est[newIdx] <-
           FALSE
       } else {
         message(
@@ -813,9 +852,9 @@ autoFIPC <-
       newBetaIdx <- NewScaleParms$item == 'BETA'
       oldBetaIdx <- OldScaleParms$item == 'BETA'
 
-      NewScaleParms[newBetaIdx, "value"] <-
-        OldScaleParms[oldBetaIdx, "value"]
-      NewScaleParms[newBetaIdx, "est"] <-
+      NewScaleParms$value[newBetaIdx] <-
+        OldScaleParms$value[oldBetaIdx]
+      NewScaleParms$est[newBetaIdx] <-
         FALSE
 
       message('applying BETA parameter as linking')
@@ -823,7 +862,7 @@ autoFIPC <-
       message(
         '   Linkedform Parms: ',
         paste0(
-          NewScaleParms[newBetaIdx, "value"],
+          NewScaleParms$value[newBetaIdx],
           ' '
         ),
         '\n'
@@ -858,13 +897,13 @@ autoFIPC <-
       new_mean11_idx <- NewScaleParms$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
+      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 +914,8 @@ autoFIPC <-
           'MEAN = F1'
         ))
 
-      NewScaleParms[NewScaleParms$name == "MEAN_1", "est"] <- TRUE
-      OldScaleParms[OldScaleParms$name == "MEAN_1", "est"] <- TRUE
+      NewScaleParms$est[NewScaleParms$name == "MEAN_1"] <- TRUE
+      OldScaleParms$est[OldScaleParms$name == "MEAN_1"] <- TRUE
     } else {
       LinkedModelSyntax <-
         mirt::mirt.model(paste0(
diff --git a/tests/testthat/test-optimization-equivalence.R b/tests/testthat/test-optimization-equivalence.R
index 02ce2f7..d7a5fa6 100644
--- a/tests/testthat/test-optimization-equivalence.R
+++ b/tests/testthat/test-optimization-equivalence.R
@@ -78,3 +78,149 @@ test_that("IPD anchor extraction keeps old/new rows and screened columns (#99)",
   expect_identical(actual_old, legacy_old)
   expect_identical(actual_new, legacy_new)
 })
+
+test_that("Direct column assignment matches 2D assignment behavior", {
+  # Mock Data setup equivalent to scale parms
+  NewScaleParms_2D <- data.frame(
+    item = c("GROUP", "Item1", "BETA", "Item2"),
+    name = c("MEAN_1", "a1", "COV_11", "d"),
+    value = c(0, 1.5, 1, -0.5),
+    est = c(TRUE, TRUE, FALSE, TRUE),
+    stringsAsFactors = FALSE
+  )
+  OldScaleParms_2D <- NewScaleParms_2D
+  OldScaleParms_2D$value <- c(1, 2.0, 0, -1.0)
+
+  NewScaleParms_1D <- NewScaleParms_2D
+  OldScaleParms_1D <- OldScaleParms_2D
+
+  # 2D Assignment (Legacy)
+  NewScaleParms_2D[NewScaleParms_2D$item == 'GROUP', "est"] <- FALSE
+  OldScaleParms_2D[OldScaleParms_2D$item == 'GROUP', "est"] <- FALSE
+  NewScaleParms_2D[NewScaleParms_2D$name == "COV_11", "est"] <- TRUE
+  OldScaleParms_2D[OldScaleParms_2D$name == "COV_11", "est"] <- TRUE
+  NewScaleParms_2D[NewScaleParms_2D$name == "a1", "est"] <- FALSE
+  OldScaleParms_2D[OldScaleParms_2D$name == "a1", "est"] <- FALSE
+
+  newBetaIdx <- NewScaleParms_2D$item == 'BETA'
+  oldBetaIdx <- OldScaleParms_2D$item == 'BETA'
+  NewScaleParms_2D[newBetaIdx, "value"] <- OldScaleParms_2D[oldBetaIdx, "value"]
+  NewScaleParms_2D[newBetaIdx, "est"] <- FALSE
+
+  # 1D Assignment (Optimized)
+  NewScaleParms_1D$est[NewScaleParms_1D$item == 'GROUP'] <- FALSE
+  OldScaleParms_1D$est[OldScaleParms_1D$item == 'GROUP'] <- FALSE
+  NewScaleParms_1D$est[NewScaleParms_1D$name == "COV_11"] <- TRUE
+  OldScaleParms_1D$est[OldScaleParms_1D$name == "COV_11"] <- TRUE
+  NewScaleParms_1D$est[NewScaleParms_1D$name == "a1"] <- FALSE
+  OldScaleParms_1D$est[OldScaleParms_1D$name == "a1"] <- FALSE
+
+  newBetaIdx_1D <- NewScaleParms_1D$item == 'BETA'
+  oldBetaIdx_1D <- OldScaleParms_1D$item == 'BETA'
+  NewScaleParms_1D$value[newBetaIdx_1D] <- OldScaleParms_1D$value[oldBetaIdx_1D]
+  NewScaleParms_1D$est[newBetaIdx_1D] <- FALSE
+
+  expect_identical(NewScaleParms_2D, NewScaleParms_1D)
+  expect_identical(OldScaleParms_2D, OldScaleParms_1D)
+
+  # Check type preservation
+  expect_type(NewScaleParms_1D$value, "double")
+  expect_type(NewScaleParms_1D$est, "logical")
+})
+
+test_that("direct parameter-column assignment preserves table semantics (#156)", {
+  new_parameters <- data.frame(
+    item = c("GROUP", "item_1", "item_1", "item_2", "BETA", "GROUP"),
+    name = c("MEAN_1", "a1", "d", "COV_11", "beta", "MEAN_11"),
+    value = c(0, 0.8, -0.4, 0.9, 0.2, 0.1),
+    est = c(TRUE, TRUE, TRUE, FALSE, TRUE, TRUE),
+    stringsAsFactors = FALSE
+  )
+  old_parameters <- data.frame(
+    item = c("GROUP", "old_1", "old_1", "old_2", "BETA", "GROUP"),
+    name = c("MEAN_1", "a1", "d", "COV_11", "beta", "MEAN_11"),
+    value = c(0, 1.1, -0.7, 1.2, 0.5, -0.1),
+    est = c(TRUE, TRUE, TRUE, FALSE, TRUE, TRUE),
+    stringsAsFactors = FALSE
+  )
+
+  legacy_new <- new_parameters
+  legacy_old <- old_parameters
+  direct_new <- new_parameters
+  direct_old <- old_parameters
+
+  legacy_new[legacy_new$item == "GROUP", "est"] <- FALSE
+  legacy_old[legacy_old$item == "GROUP", "est"] <- FALSE
+  direct_new$est[direct_new$item == "GROUP"] <- FALSE
+  direct_old$est[direct_old$item == "GROUP"] <- FALSE
+
+  legacy_new[legacy_new$name == "COV_11", "est"] <- TRUE
+  legacy_old[legacy_old$name == "COV_11", "est"] <- TRUE
+  direct_new$est[direct_new$name == "COV_11"] <- TRUE
+  direct_old$est[direct_old$name == "COV_11"] <- TRUE
+
+  new_anchor <- legacy_new$item == "item_1"
+  old_anchor <- legacy_old$item == "old_1"
+  direct_new_anchor <- direct_new$item == "item_1"
+  direct_old_anchor <- direct_old$item == "old_1"
+  legacy_new[new_anchor, "value"] <- legacy_old[old_anchor, "value"]
+  legacy_new[new_anchor, "est"] <- FALSE
+  direct_new$value[direct_new_anchor] <- direct_old$value[direct_old_anchor]
+  direct_new$est[direct_new_anchor] <- FALSE
+
+  new_beta <- legacy_new$item == "BETA"
+  old_beta <- legacy_old$item == "BETA"
+  direct_new_beta <- direct_new$item == "BETA"
+  direct_old_beta <- direct_old$item == "BETA"
+  legacy_new[new_beta, "value"] <- legacy_old[old_beta, "value"]
+  legacy_new[new_beta, "est"] <- FALSE
+  direct_new$value[direct_new_beta] <- direct_old$value[direct_old_beta]
+  direct_new$est[direct_new_beta] <- FALSE
+
+  expect_identical(direct_new, legacy_new)
+  expect_identical(direct_old, legacy_old)
+})
+
+test_that("scale-parameter preparation validates schema and preserves Rasch semantics (#156)", {
+  parameters <- data.frame(
+    item = c("GROUP", "item_1", "item_2"),
+    name = c("MEAN_1", "a1", "COV_11"),
+    value = c(0, 1, 1),
+    est = c(TRUE, TRUE, FALSE),
+    stringsAsFactors = FALSE
+  )
+
+  legacy_new <- parameters
+  legacy_old <- parameters
+  legacy_new[legacy_new$item == "GROUP", "est"] <- FALSE
+  legacy_old[legacy_old$item == "GROUP", "est"] <- FALSE
+  legacy_new[legacy_new$name == "COV_11", "est"] <- TRUE
+  legacy_old[legacy_old$name == "COV_11", "est"] <- TRUE
+  legacy_new[legacy_new$name == "a1", "est"] <- FALSE
+  legacy_old[legacy_old$name == "a1", "est"] <- FALSE
+
+  actual <- aFIPC:::.prepare_scale_parameters(parameters, parameters, "Rasch")
+
+  expect_identical(actual$new, legacy_new)
+  expect_identical(actual$old, legacy_old)
+  expect_false(actual$new$est[actual$new$name == "a1"])
+
+  expect_error(
+    aFIPC:::.prepare_scale_parameters(
+      as.matrix(parameters),
+      parameters,
+      "Rasch"
+    ),
+    "new-form parameter table must be a data.frame",
+    fixed = TRUE
+  )
+
+  for (missing_column in c("item", "name", "value", "est")) {
+    incomplete <- parameters[setdiff(names(parameters), missing_column)]
+    expect_error(
+      aFIPC:::.prepare_scale_parameters(incomplete, parameters, "Rasch"),
+      paste0("missing required column\\(s\\): ", missing_column),
+      fixed = FALSE
+    )
+  }
+})