No issue: Fix resource leaks in tests

dkpro-core-eval-asl/src/main/java/org/dkpro/core/eval/EvalUtil.java

@@ -17,11 +17,11 @@
  */
 package org.dkpro.core.eval;
 
+import static java.nio.charset.StandardCharsets.UTF_8;
 import static org.apache.uima.fit.pipeline.SimplePipeline.iteratePipeline;
 import static org.apache.uima.fit.util.JCasUtil.select;
 
 import java.io.File;
-import java.io.FileNotFoundException;
 import java.io.FileOutputStream;
 import java.io.IOException;
 import java.io.OutputStreamWriter;
@@ -47,21 +47,21 @@ public class EvalUtil
 {
     public static <T extends Annotation> List<Span<String>> loadSamples(
             CollectionReaderDescription aReader, Class<T> aType)
-                throws UIMAException, IOException
+        throws UIMAException, IOException
     {
         return loadSamples(aReader, aType, null);
     }
-    
+
     public static <T extends Annotation> List<Span<String>> loadSamples(
             CollectionReaderDescription aReader, Class<T> aType, Function<T, String> aLabelFunction)
-                throws UIMAException, IOException
+        throws UIMAException, IOException
     {
         return loadSamples(iteratePipeline(aReader), aType, aLabelFunction);
     }
-    
-    public static <T extends Annotation> List<Span<String>> loadSamples(
-            JCasIterable aIterable, Class<T> aType, Function<T, String> aLabelFunction)
-                throws UIMAException, IOException
+
+    public static <T extends Annotation> List<Span<String>> loadSamples(JCasIterable aIterable,
+            Class<T> aType, Function<T, String> aLabelFunction)
+        throws UIMAException, IOException
     {
         List<Span<String>> samples = new ArrayList<>();
         for (JCas jcas : aIterable) {
@@ -74,28 +74,30 @@ public static <T extends Annotation> List<Span<String>> loadSamples(
 
         return samples;
     }
-    
+
     public static Result dumpResults(File targetFolder, Collection<? extends Object> aExpected,
             Collection<? extends Object> aActual)
-                throws UnsupportedEncodingException, FileNotFoundException
+        throws UnsupportedEncodingException, IOException
     {
         System.out.println("Calculating F-measure");
         FMeasure fmeasure = new FMeasure();
         fmeasure.process(aExpected, aActual);
-        
+
         System.out.printf("F-score     %f%n", fmeasure.getFMeasure());
         System.out.printf("Precision   %f%n", fmeasure.getPrecision());
         System.out.printf("Recall      %f%n", fmeasure.getRecall());
-        
+
         Result results = new Result();
         results.setFscore(fmeasure.getFMeasure());
         results.setPrecision(fmeasure.getPrecision());
         results.setRecall(fmeasure.getRecall());
 
-        Yaml yaml = new Yaml();
-        yaml.dump(results, new OutputStreamWriter(
-                new FileOutputStream(new File(targetFolder, "results.yaml")), "UTF-8"));
-
+        try (var os = new OutputStreamWriter(
+                new FileOutputStream(new File(targetFolder, "results.yaml")), UTF_8)) {
+            Yaml yaml = new Yaml();
+            yaml.dump(results, os);
+        }
+
         return results;
     }
 }

dkpro-core-opennlp-asl/src/test/java/org/dkpro/core/opennlp/OpenNlpChunkerTrainerTest.java

@@ -56,33 +56,33 @@ public void test(@TempDir File targetFolder)
 
         // Train model
         System.out.println("Training model from training data");
-        CollectionReaderDescription trainReader = createReaderDescription(
-                Conll2000Reader.class,
-                Conll2000Reader.PARAM_PATTERNS, split.getTrainingFiles(),
+        CollectionReaderDescription trainReader = createReaderDescription( //
+                Conll2000Reader.class, //
+                Conll2000Reader.PARAM_PATTERNS, split.getTrainingFiles(), //
                 Conll2000Reader.PARAM_LANGUAGE, ds.getLanguage());
 
-        AnalysisEngineDescription trainer = createEngineDescription(
-                OpenNlpChunkerTrainer.class,
-                OpenNlpChunkerTrainer.PARAM_TARGET_LOCATION, new File(targetFolder, "model.bin"),
+        AnalysisEngineDescription trainer = createEngineDescription( //
+                OpenNlpChunkerTrainer.class, //
+                OpenNlpChunkerTrainer.PARAM_TARGET_LOCATION, new File(targetFolder, "model.bin"), //
 //                OpenNlpChunkerTrainer.PARAM_ALGORITHM, "PERCEPTRON",
 //                OpenNlpChunkerTrainer.PARAM_CUTOFF, 0,
-                OpenNlpChunkerTrainer.PARAM_NUM_THREADS, 2,
-                OpenNlpChunkerTrainer.PARAM_LANGUAGE, ds.getLanguage(),
+                OpenNlpChunkerTrainer.PARAM_NUM_THREADS, 2, //
+                OpenNlpChunkerTrainer.PARAM_LANGUAGE, ds.getLanguage(), //
                 OpenNlpChunkerTrainer.PARAM_ITERATIONS, 10);
 
         SimplePipeline.runPipeline(trainReader, trainer);
 
         // Apply model and collect labels
         System.out.println("Applying model to test data");
-        CollectionReaderDescription testReader = createReaderDescription(
-                Conll2000Reader.class,
-                Conll2000Reader.PARAM_PATTERNS, split.getTestFiles(),
-                Conll2000Reader.PARAM_READ_CHUNK, false,
+        CollectionReaderDescription testReader = createReaderDescription( //
+                Conll2000Reader.class, //
+                Conll2000Reader.PARAM_PATTERNS, split.getTestFiles(), //
+                Conll2000Reader.PARAM_READ_CHUNK, false, //
                 Conll2000Reader.PARAM_LANGUAGE, ds.getLanguage());
 
-        AnalysisEngineDescription ner = createEngineDescription(
-                OpenNlpChunker.class,
-                OpenNlpChunker.PARAM_PRINT_TAGSET, true,
+        AnalysisEngineDescription ner = createEngineDescription( //
+                OpenNlpChunker.class, //
+                OpenNlpChunker.PARAM_PRINT_TAGSET, true, //
                 OpenNlpChunker.PARAM_MODEL_LOCATION, new File(targetFolder, "model.bin"));
 
         List<Span<String>> actual = EvalUtil.loadSamples(iteratePipeline(testReader, ner),