diff --git a/solr/contrib/ltr/src/test/org/apache/solr/ltr/feature/TestLTRScoringAlgorithm.java b/solr/contrib/ltr/src/test/org/apache/solr/ltr/feature/TestLTRScoringAlgorithm.java
index 72ba5cd7859e..eb3828fac866 100644
--- a/solr/contrib/ltr/src/test/org/apache/solr/ltr/feature/TestLTRScoringAlgorithm.java
+++ b/solr/contrib/ltr/src/test/org/apache/solr/ltr/feature/TestLTRScoringAlgorithm.java
@@ -28,7 +28,6 @@
 import org.apache.solr.ltr.ranking.Feature;
 import org.apache.solr.ltr.ranking.RankSVMModel;
 import org.apache.solr.ltr.rest.ManagedModelStore;
-import org.apache.solr.ltr.util.FeatureException;
 import org.apache.solr.ltr.util.ModelException;
 import org.junit.BeforeClass;
 import org.junit.Test;
@@ -48,7 +47,7 @@ public static void setup() throws Exception {
   }
 
   @Test
-  public void getInstanceTest() throws FeatureException, ModelException {
+  public void getInstanceTest() {
     final Map<String,Object> weights = new HashMap<>();
     weights.put("constant1", 1d);
     weights.put("constant5", 1d);
@@ -69,149 +68,127 @@ public void getInstanceTest() throws FeatureException, ModelException {
     assertEquals(meta, m);
   }
 
-  @Test(expected = ModelException.class)
-  public void getInvalidTypeTest() throws ModelException, FeatureException {
-    final List<Feature> features = getFeatures(new String[] {
-        "constant1", "constant5"});
-    final List<Normalizer> norms = 
-        new ArrayList<Normalizer>(
-            Collections.nCopies(features.size(),IdentityNormalizer.INSTANCE));
-    final LTRScoringAlgorithm meta = new RankSVMModel("test2",
-        features, norms, "test", fstore.getFeatures(), null);
-    store.addMetadataModel(meta);
-    final LTRScoringAlgorithm m = store.getModel("test38290156821076");
-  }
-
-  @Test(expected = ModelException.class)
-  public void getInvalidNameTest() throws ModelException, FeatureException {
-    final List<Feature> features = getFeatures(new String[] {
-        "constant1", "constant5"});
-    final List<Normalizer> norms = 
-        new ArrayList<Normalizer>(
-            Collections.nCopies(features.size(),IdentityNormalizer.INSTANCE));
-    final LTRScoringAlgorithm meta = new RankSVMModel("!!!??????????",
-        features, norms, "test", fstore.getFeatures(), null);
-    store.addMetadataModel(meta);
-    store.getModel("!!!??????????");
-  }
-
-  @Test(expected = ModelException.class)
-  public void existingNameTest() throws ModelException, FeatureException {
-    final Map<String,Object> weights = new HashMap<>();
-    weights.put("constant1", 1d);
-    weights.put("constant5", 1d);
-
-    Map<String,Object> params = new HashMap<String,Object>();
-    params.put("weights", weights);
-    final List<Feature> features = getFeatures(new String[] {
-        "constant1", "constant5"});
-    final List<Normalizer> norms = 
-        new ArrayList<Normalizer>(
-            Collections.nCopies(features.size(),IdentityNormalizer.INSTANCE));
-    final LTRScoringAlgorithm meta = new RankSVMModel("test3",
-        features, norms, "test", fstore.getFeatures(),
-        params);
-    store.addMetadataModel(meta);
-    final LTRScoringAlgorithm m = store.getModel("test3");
-    assertEquals(meta, m);
-    store.addMetadataModel(meta);
-  }
-
-  @Test(expected = ModelException.class)
-  public void duplicateFeatureTest() throws ModelException, FeatureException {
-    final Map<String,Object> weights = new HashMap<>();
-    weights.put("constant1", 1d);
-    weights.put("constant5", 1d);
-
-    Map<String,Object> params = new HashMap<String,Object>();
-    params.put("weights", weights);
-    final List<Feature> features = getFeatures(new String[] {
-        "constant1", "constant1"});
-    final List<Normalizer> norms = 
+  @Test
+  public void nullFeatureWeightsTest() {
+    final ModelException expectedException = 
+        new ModelException("Model test2 doesn't contain any weights");
+    try {
+      final List<Feature> features = getFeatures(new String[] 
+          {"constant1", "constant5"});
+      final List<Normalizer> norms = 
         new ArrayList<Normalizer>(
             Collections.nCopies(features.size(),IdentityNormalizer.INSTANCE));
-    final LTRScoringAlgorithm meta = new RankSVMModel("test4",
-        features, norms, "test", fstore.getFeatures(),
-        params);
-    store.addMetadataModel(meta);
-
+      final LTRScoringAlgorithm meta = new RankSVMModel("test2",
+          features, norms, "test", fstore.getFeatures(), null);
+      fail("unexpectedly got here instead of catching "+expectedException);
+    } catch (ModelException actualException) {
+      assertEquals(expectedException.toString(), actualException.toString());
+    }
   }
 
-  @Test(expected = ModelException.class)
-  public void missingFeatureTest() throws ModelException, FeatureException {
-    final Map<String,Object> weights = new HashMap<>();
-    weights.put("constant1", 1d);
-    weights.put("constant5missing", 1d);
-
-    Map<String,Object> params = new HashMap<String,Object>();
-    params.put("weights", weights);
-    final List<Feature> features = getFeatures(new String[] {
-        "constant1", "constant1"});
-    final List<Normalizer> norms = 
+  @Test
+  public void existingNameTest() {
+    final ModelException expectedException = 
+        new ModelException("model 'test3' already exists. Please use a different name");
+    try {
+      final List<Feature> features = getFeatures(new String[] 
+          {"constant1", "constant5"});
+      final List<Normalizer> norms = 
         new ArrayList<Normalizer>(
             Collections.nCopies(features.size(),IdentityNormalizer.INSTANCE));
-    final LTRScoringAlgorithm meta = new RankSVMModel("test5",
-        features, norms, "test", fstore.getFeatures(),
-        params);
-    store.addMetadataModel(meta);
-
+      final Map<String,Object> weights = new HashMap<>();
+      weights.put("constant1", 1d);
+      weights.put("constant5", 1d);
+
+      Map<String,Object> params = new HashMap<String,Object>();
+      params.put("weights", weights);
+      final LTRScoringAlgorithm meta = new RankSVMModel("test3",
+          features, norms, "test", fstore.getFeatures(),
+              params);
+      store.addMetadataModel(meta);
+      final LTRScoringAlgorithm m = store.getModel("test3");
+      assertEquals(meta, m);
+      store.addMetadataModel(meta);
+      fail("unexpectedly got here instead of catching "+expectedException);
+    } catch (ModelException actualException) {
+      assertEquals(expectedException.toString(), actualException.toString());
+    }
   }
 
-  @Test(expected = ModelException.class)
-  public void notExistingClassTest() throws ModelException, FeatureException {
-    final Map<String,Object> weights = new HashMap<>();
-    weights.put("constant1", 1d);
-    weights.put("constant5missing", 1d);
-
-    Map<String,Object> params = new HashMap<String,Object>();
-    params.put("weights", weights);
-    final List<Feature> features = getFeatures(new String[] {
-        "constant1", "constant5"});
-    final List<Normalizer> norms = 
+  @Test
+  public void duplicateFeatureTest() {
+    final ModelException expectedException = 
+        new ModelException("duplicated feature constant1 in model test4");
+    try {
+      final List<Feature> features = getFeatures(new String[] 
+          {"constant1", "constant1"});
+      final List<Normalizer> norms = 
         new ArrayList<Normalizer>(
             Collections.nCopies(features.size(),IdentityNormalizer.INSTANCE));
-    final LTRScoringAlgorithm meta = new RankSVMModel("test6",
-        features, norms, "test", fstore.getFeatures(),
-        params);
-    store.addMetadataModel(meta);
+      final Map<String,Object> weights = new HashMap<>();
+      weights.put("constant1", 1d);
+      weights.put("constant5", 1d);
+
+      Map<String,Object> params = new HashMap<String,Object>();
+      params.put("weights", weights);
+      final LTRScoringAlgorithm meta = new RankSVMModel("test4",
+          features, norms, "test", fstore.getFeatures(),
+              params);
+      store.addMetadataModel(meta);
+      fail("unexpectedly got here instead of catching "+expectedException);
+    } catch (ModelException actualException) {
+      assertEquals(expectedException.toString(), actualException.toString());
+    }
 
   }
 
-  @Test(expected = ModelException.class)
-  public void badModelClassTest() throws ModelException, FeatureException {
-    final Map<String,Object> weights = new HashMap<>();
-    weights.put("constant1", 1d);
-    weights.put("constant5missing", 1d);
-
-    Map<String,Object> params = new HashMap<String,Object>();
-    params.put("weights", weights);
-    final List<Feature> features = getFeatures(new String[] {
-        "constant1", "constant5"});
-    final List<Normalizer> norms = 
+  @Test
+  public void missingFeatureWeightTest() {
+    final ModelException expectedException = 
+        new ModelException("no weight for feature constant5");
+    try {
+      final List<Feature> features = getFeatures(new String[] 
+          {"constant1", "constant5"});
+      final List<Normalizer> norms = 
         new ArrayList<Normalizer>(
             Collections.nCopies(features.size(),IdentityNormalizer.INSTANCE));
-    final LTRScoringAlgorithm meta = new RankSVMModel("test7",
-        features, norms, "test", fstore.getFeatures(),
-        params);
-    store.addMetadataModel(meta);
-
+      final Map<String,Object> weights = new HashMap<>();
+      weights.put("constant1", 1d);
+      weights.put("constant5missing", 1d);
+
+      Map<String,Object> params = new HashMap<String,Object>();
+      params.put("weights", weights);
+      final LTRScoringAlgorithm meta = new RankSVMModel("test5",
+          features, norms, "test", fstore.getFeatures(),
+              params);
+      fail("unexpectedly got here instead of catching "+expectedException);
+    } catch (ModelException actualException) {
+      assertEquals(expectedException.toString(), actualException.toString());
+    }
   }
 
-  @Test(expected = ModelException.class)
-  public void misingFeaturesTest() throws ModelException, FeatureException {
-    final Map<String,Object> weights = new HashMap<>();
-    weights.put("constant1", 1d);
-    weights.put("constant5missing", 1d);
-
-    Map<String,Object> params = new HashMap<String,Object>();
-    params.put("weights", weights);
-    final List<Feature> features = getFeatures(new String[] {});
-    final List<Normalizer> norms = 
+  @Test
+  public void emptyFeaturesTest() {
+    final ModelException expectedException = 
+        new ModelException("no features declared for model test6");
+    try {
+      final List<Feature> features = getFeatures(new String[] {});
+      final List<Normalizer> norms = 
         new ArrayList<Normalizer>(
             Collections.nCopies(features.size(),IdentityNormalizer.INSTANCE));
-    final LTRScoringAlgorithm meta = new RankSVMModel("test8",
-        features, norms, "test", fstore.getFeatures(),
-        params);
-    store.addMetadataModel(meta);
+      final Map<String,Object> weights = new HashMap<>();
+      weights.put("constant1", 1d);
+      weights.put("constant5missing", 1d);
+
+      Map<String,Object> params = new HashMap<String,Object>();
+      params.put("weights", weights);
+      final LTRScoringAlgorithm meta = new RankSVMModel("test6",
+          features, norms, "test", fstore.getFeatures(),
+          params);
+      store.addMetadataModel(meta);
+      fail("unexpectedly got here instead of catching "+expectedException);
+    } catch (ModelException actualException) {
+      assertEquals(expectedException.toString(), actualException.toString());
+    }
   }
-}
+}
\ No newline at end of file