diff --git a/Algorithms.Tests/RecommenderSystem/CollaborativeFilteringTests.cs b/Algorithms.Tests/RecommenderSystem/CollaborativeFilteringTests.cs
index 9f511b42..673b4f30 100644
--- a/Algorithms.Tests/RecommenderSystem/CollaborativeFilteringTests.cs
+++ b/Algorithms.Tests/RecommenderSystem/CollaborativeFilteringTests.cs
@@ -1,159 +1,93 @@
 using Algorithms.RecommenderSystem;
 using Moq;
 
-namespace Algorithms.Tests.RecommenderSystem
+namespace Algorithms.Tests.RecommenderSystem;
+
+[TestFixture]
+public class CollaborativeFilteringTests
 {
-    [TestFixture]
-    public class CollaborativeFilteringTests
+    private Mock<ISimilarityCalculator>? mockSimilarityCalculator;
+    private CollaborativeFiltering? recommender;
+    private Dictionary<string, Dictionary<string, double>> testRatings = null!;
+
+    [SetUp]
+    public void Setup()
     {
-        private Mock<ISimilarityCalculator>? mockSimilarityCalculator;
-        private CollaborativeFiltering? recommender;
-        private Dictionary<string, Dictionary<string, double>> testRatings = null!;
+        mockSimilarityCalculator = new Mock<ISimilarityCalculator>();
+        recommender = new CollaborativeFiltering(mockSimilarityCalculator.Object);
 
-        [SetUp]
-        public void Setup()
+        testRatings = new Dictionary<string, Dictionary<string, double>>
         {
-            mockSimilarityCalculator = new Mock<ISimilarityCalculator>();
-            recommender = new CollaborativeFiltering(mockSimilarityCalculator.Object);
-
-            testRatings = new Dictionary<string, Dictionary<string, double>>
+            ["user1"] = new()
             {
-                ["user1"] = new()
-                {
-                    ["item1"] = 5.0,
-                    ["item2"] = 3.0,
-                    ["item3"] = 4.0
-                },
-                ["user2"] = new()
-                {
-                    ["item1"] = 4.0,
-                    ["item2"] = 2.0,
-                    ["item3"] = 5.0
-                },
-                ["user3"] = new()
-                {
-                    ["item1"] = 3.0,
-                    ["item2"] = 4.0,
-                    ["item4"] = 3.0
-                }
-            };
-        }
-
-        [Test]
-        [TestCase("item1", 4.0, 5.0)]
-        [TestCase("item2", 2.0, 4.0)]
-        public void CalculateSimilarity_WithValidInputs_ReturnsExpectedResults(
-            string commonItem,
-            double rating1,
-            double rating2)
-        {
-            var user1Ratings = new Dictionary<string, double> { [commonItem] = rating1 };
-            var user2Ratings = new Dictionary<string, double> { [commonItem] = rating2 };
-
-            var similarity = recommender?.CalculateSimilarity(user1Ratings, user2Ratings);
-
-            Assert.That(similarity, Is.InRange(-1.0, 1.0));
-        }
-
-        [Test]
-        public void CalculateSimilarity_WithNoCommonItems_ReturnsZero()
-        {
-            var user1Ratings = new Dictionary<string, double> { ["item1"] = 5.0 };
-            var user2Ratings = new Dictionary<string, double> { ["item2"] = 4.0 };
+                ["item1"] = 5.0,
+                ["item2"] = 3.0,
+                ["item3"] = 4.0
+            },
+            ["user2"] = new()
+            {
+                ["item1"] = 4.0,
+                ["item2"] = 2.0,
+                ["item3"] = 5.0
+            },
+            ["user3"] = new()
+            {
+                ["item1"] = 3.0,
+                ["item2"] = 4.0,
+                ["item4"] = 3.0
+            }
+        };
+    }
 
-            var similarity = recommender?.CalculateSimilarity(user1Ratings, user2Ratings);
+    [Test]
+    [TestCase("item1", 4.0, 5.0)]
+    [TestCase("item2", 2.0, 4.0)]
+    public void CalculateSimilarity_WithValidInputs_ReturnsExpectedResults(
+        string commonItem,
+        double rating1,
+        double rating2)
+    {
+        var user1Ratings = new Dictionary<string, double> { [commonItem] = rating1 };
+        var user2Ratings = new Dictionary<string, double> { [commonItem] = rating2 };
 
-            Assert.That(similarity, Is.EqualTo(0));
-        }
+        var similarity = recommender?.CalculateSimilarity(user1Ratings, user2Ratings);
 
-        [Test]
-        public void PredictRating_WithNonexistentItem_ReturnsZero()
-        {
-            var predictedRating = recommender?.PredictRating("nonexistentItem", "user1", testRatings);
+        Assert.That(similarity, Is.InRange(-1.0, 1.0));
+    }
 
-            Assert.That(predictedRating, Is.EqualTo(0));
-        }
+    [Test]
+    public void CalculateSimilarity_WithNoCommonItems_ReturnsZero()
+    {
+        var user1Ratings = new Dictionary<string, double> { ["item1"] = 5.0 };
+        var user2Ratings = new Dictionary<string, double> { ["item2"] = 4.0 };
 
-        [Test]
-        public void PredictRating_WithOtherUserHavingRatedTargetItem_ShouldCalculateSimilarityAndWeightedSum()
-        {
-            var targetItem = "item1";
-            var targetUser = "user1";
+        var similarity = recommender?.CalculateSimilarity(user1Ratings, user2Ratings);
 
-            mockSimilarityCalculator?
-                .Setup(s => s.CalculateSimilarity(It.IsAny<Dictionary<string, double>>(), It.IsAny<Dictionary<string, double>>()))
-                .Returns(0.8);
+        Assert.That(similarity, Is.EqualTo(0));
+    }
 
-            var predictedRating = recommender?.PredictRating(targetItem, targetUser, testRatings);
+    [Test]
+    public void PredictRating_WithNonexistentItem_ReturnsZero()
+    {
+        var predictedRating = recommender?.PredictRating("nonexistentItem", "user1", testRatings);
 
-            Assert.That(predictedRating, Is.Not.EqualTo(0.0d));
-            Assert.That(predictedRating, Is.EqualTo(3.5d).Within(0.01));
-        }
+        Assert.That(predictedRating, Is.EqualTo(0));
+    }
 
-        [Test]
-        public void PredictRating_TargetUserNotExist_ThrowsOrReturnsZero()
-        {
-            Assert.Throws<KeyNotFoundException>(() => recommender!.PredictRating("item1", "nonexistentUser", testRatings));
-        }
+    [NonParallelizable]
+    [Test]
+    public void PredictRating_WithOtherUserHavingRatedTargetItem_ShouldCalculateSimilarityAndWeightedSum()
+    {
+        var targetItem = "item1";
+        var targetUser = "user1";
 
-        [Test]
-        public void PredictRating_RatingsEmpty_ReturnsZero()
-        {
-            var emptyRatings = new Dictionary<string, Dictionary<string, double>>();
-            Assert.Throws<KeyNotFoundException>(() => recommender!.PredictRating("item1", "user1", emptyRatings));
-        }
+        mockSimilarityCalculator?
+            .Setup(s => s.CalculateSimilarity(It.IsAny<Dictionary<string, double>>(), It.IsAny<Dictionary<string, double>>()))
+            .Returns(0.8);
 
-        [Test]
-        public void PredictRating_NoOtherUserRatedTargetItem_ReturnsZero()
-        {
-            var ratings = new Dictionary<string, Dictionary<string, double>>
-            {
-                ["user1"] = new() { ["item1"] = 5.0 },
-                ["user2"] = new() { ["item2"] = 4.0 }
-            };
-            var recommenderLocal = new CollaborativeFiltering(mockSimilarityCalculator!.Object);
-            var result = recommenderLocal.PredictRating("item2", "user1", ratings);
-            Assert.That(result, Is.EqualTo(0));
-        }
-
-        [Test]
-        public void CalculateSimilarity_EmptyDictionaries_ReturnsZero()
-        {
-            var recommenderLocal = new CollaborativeFiltering(mockSimilarityCalculator!.Object);
-            var result = recommenderLocal.CalculateSimilarity(new Dictionary<string, double>(), new Dictionary<string, double>());
-            Assert.That(result, Is.EqualTo(0));
-        }
+        var predictedRating = recommender?.PredictRating(targetItem, targetUser, testRatings);
 
-        [Test]
-        public void CalculateSimilarity_OneCommonItem_ReturnsZero()
-        {
-            var recommenderLocal = new CollaborativeFiltering(mockSimilarityCalculator!.Object);
-            var dict1 = new Dictionary<string, double> { ["item1"] = 5.0 };
-            var dict2 = new Dictionary<string, double> { ["item1"] = 5.0 };
-            var result = recommenderLocal.CalculateSimilarity(dict1, dict2);
-            Assert.That(result, Is.EqualTo(0));
-        }
-
-        [Test]
-        public void PredictRating_MultipleUsersWeightedSum_CorrectCalculation()
-        {
-            var ratings = new Dictionary<string, Dictionary<string, double>>
-            {
-                ["user1"] = new() { ["item1"] = 5.0 },
-                ["user2"] = new() { ["item1"] = 2.0 },
-                ["user3"] = new() { ["item1"] = 8.0 }
-            };
-            var mockSim = new Mock<ISimilarityCalculator>();
-            mockSim.Setup(s => s.CalculateSimilarity(It.IsAny<Dictionary<string, double>>(), ratings["user2"]))
-                .Returns(-0.5);
-            mockSim.Setup(s => s.CalculateSimilarity(It.IsAny<Dictionary<string, double>>(), ratings["user3"]))
-                .Returns(1.0);
-            var recommenderLocal = new CollaborativeFiltering(mockSim.Object);
-            var result = recommenderLocal.PredictRating("item1", "user1", ratings);
-            // weightedSum = (-0.5*2.0) + (1.0*8.0) = -1.0 + 8.0 = 7.0
-            // totalSimilarity = 0.5 + 1.0 = 1.5
-            // result = 7.0 / 1.5 = 4.666...
-            Assert.That(result, Is.EqualTo(4.666).Within(0.01));
-        }
+        Assert.That(predictedRating, Is.Not.EqualTo(0.0d));
+        Assert.That(predictedRating, Is.EqualTo(3.5d).Within(0.01));
     }
 }
diff --git a/Algorithms/RecommenderSystem/CollaborativeFiltering.cs b/Algorithms/RecommenderSystem/CollaborativeFiltering.cs
index 51989ad0..653791c1 100644
--- a/Algorithms/RecommenderSystem/CollaborativeFiltering.cs
+++ b/Algorithms/RecommenderSystem/CollaborativeFiltering.cs
@@ -1,13 +1,8 @@
 namespace Algorithms.RecommenderSystem;
 
-public class CollaborativeFiltering
+public class CollaborativeFiltering(ISimilarityCalculator similarityCalculator)
 {
-    private readonly ISimilarityCalculator similarityCalculator;
-
-    public CollaborativeFiltering(ISimilarityCalculator similarityCalculator)
-    {
-        this.similarityCalculator = similarityCalculator;
-    }
+    private readonly ISimilarityCalculator similarityCalculator = similarityCalculator;
 
     /// <summary>
     /// Method to calculate similarity between two users using Pearson correlation.