diff --git a/kmath-core/api/kmath-core.api b/kmath-core/api/kmath-core.api
index 687de9cc8..261aa1e24 100644
--- a/kmath-core/api/kmath-core.api
+++ b/kmath-core/api/kmath-core.api
@@ -792,7 +792,6 @@ public final class space/kscience/kmath/nd/DefaultStrides : space/kscience/kmath
 	public fun getStrides ()[I
 	public fun hashCode ()I
 	public fun index (I)[I
-	public fun offset ([I)I
 }
 
 public final class space/kscience/kmath/nd/DefaultStrides$Companion {
@@ -934,7 +933,7 @@ public abstract interface class space/kscience/kmath/nd/Strides {
 	public abstract fun getStrides ()[I
 	public abstract fun index (I)[I
 	public fun indices ()Lkotlin/sequences/Sequence;
-	public abstract fun offset ([I)I
+	public fun offset ([I)I
 }
 
 public abstract interface class space/kscience/kmath/nd/Structure1D : space/kscience/kmath/nd/StructureND, space/kscience/kmath/structures/Buffer {
diff --git a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt
index 65c233012..a3331d71a 100644
--- a/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt
+++ b/kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt
@@ -189,7 +189,10 @@ public interface Strides {
     /**
      * Get linear index from multidimensional index
      */
-    public fun offset(index: IntArray): Int
+    public fun offset(index: IntArray): Int = index.mapIndexed { i, value ->
+        if (value < 0 || value >= shape[i]) throw IndexOutOfBoundsException("Index $value out of shape bounds: (0,${this.shape[i]})")
+        value * strides[i]
+    }.sum()
 
     /**
      * Get multidimensional from linear
@@ -233,11 +236,6 @@ public class DefaultStrides private constructor(override val shape: IntArray) :
         }.toList().toIntArray()
     }
 
-    override fun offset(index: IntArray): Int = index.mapIndexed { i, value ->
-        if (value < 0 || value >= shape[i]) throw IndexOutOfBoundsException("Index $value out of shape bounds: (0,${this.shape[i]})")
-        value * strides[i]
-    }.sum()
-
     override fun index(offset: Int): IntArray {
         val res = IntArray(shape.size)
         var current = offset
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/TensorLinearStructure.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/TensorLinearStructure.kt
index 8e83dafd6..08aab5175 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/TensorLinearStructure.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/TensorLinearStructure.kt
@@ -68,8 +68,6 @@ public class TensorLinearStructure(override val shape: IntArray) : Strides
     override val strides: IntArray
         get() = stridesFromShape(shape)
 
-    override fun offset(index: IntArray): Int = offsetFromIndex(index, shape, strides)
-
     override fun index(offset: Int): IntArray =
         indexFromOffset(offset, strides, shape.size)
 
@@ -82,7 +80,4 @@ public class TensorLinearStructure(override val shape: IntArray) : Strides
     public val dim: Int
         get() = shape.size
 
-    override fun indices(): Sequence<IntArray> = (0 until linearSize).asSequence().map {
-        index(it)
-    }
 }
\ No newline at end of file
diff --git a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/broadcastUtils.kt b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/broadcastUtils.kt
index 58d8654af..e883b7861 100644
--- a/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/broadcastUtils.kt
+++ b/kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/broadcastUtils.kt
@@ -75,14 +75,13 @@ internal fun broadcastTensors(vararg tensors: DoubleTensor): List<DoubleTensor>
     val totalShape = broadcastShapes(*(tensors.map { it.shape }).toTypedArray())
     val n = totalShape.reduce { acc, i -> acc * i }
 
-    val res = ArrayList<DoubleTensor>(0)
-    for (tensor in tensors) {
-        val resTensor = DoubleTensor(totalShape, DoubleArray(n))
-        multiIndexBroadCasting(tensor, resTensor, n)
-        res.add(resTensor)
+    return  buildList {
+        for (tensor in tensors) {
+            val resTensor = DoubleTensor(totalShape, DoubleArray(n))
+            multiIndexBroadCasting(tensor, resTensor, n)
+            add(resTensor)
+        }
     }
-
-    return res
 }
 
 internal fun broadcastOuterTensors(vararg tensors: DoubleTensor): List<DoubleTensor> {
diff --git a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt
index 34fe5d5f1..a0efa4573 100644
--- a/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt
+++ b/kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt
@@ -170,7 +170,6 @@ internal class TestDoubleTensorAlgebra {
         val tensor1 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
         val tensor2 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
         val tensor3 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 5.0))
-        val tensor4 = fromArray(intArrayOf(6, 1), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
 
         assertTrue(tensor1 eq tensor1)
         assertTrue(tensor1 eq tensor2)