diff --git a/theodolite-benchmarks/uc1-beam/src/main/java/application/Uc1BeamPipeline.java b/theodolite-benchmarks/uc1-beam/src/main/java/application/Uc1BeamPipeline.java
index eb894d13b38c46eb63136c2f670dfdf7e091356f..352b32a29ff6cfd5d01a4e74798f79c8d08c769a 100644
--- a/theodolite-benchmarks/uc1-beam/src/main/java/application/Uc1BeamPipeline.java
+++ b/theodolite-benchmarks/uc1-beam/src/main/java/application/Uc1BeamPipeline.java
@@ -9,14 +9,8 @@ import theodolite.commons.beam.AbstractPipeline;
 import theodolite.commons.beam.kafka.KafkaActivePowerTimestampReader;
 import titan.ccp.model.records.ActivePowerRecord;
 
-
 /**
- * Implementation of the use case Database Storage using Apache Beam with the Flink Runner. To
- * execute locally in standalone start Kafka, Zookeeper, the schema-registry and the workload
- * generator using the delayed_startup.sh script. Start a Flink cluster and pass its REST adress
- * using--flinkMaster as run parameter. To persist logs add
- * ${workspace_loc:/uc1-application-samza/eclipseConsoleLogs.log} as Output File under Standard
- * Input Output in Common in the Run Configuration Start via Eclipse Run.
+ * Implementation of benchmark UC1: Database Storage with Apache Beam.
  */
 public final class Uc1BeamPipeline extends AbstractPipeline {
 
@@ -27,19 +21,16 @@ public final class Uc1BeamPipeline extends AbstractPipeline {
 
     final SinkType sinkType = SinkType.from(config.getString(SINK_TYPE_KEY));
 
-    // Set Coders for Classes that will be distributed
-    final CoderRegistry cr = this.getCoderRegistry();
+    // Set Coders for classes that will be distributed
+    final CoderRegistry cr = super.getCoderRegistry();
     cr.registerCoderForClass(ActivePowerRecord.class, AvroCoder.of(ActivePowerRecord.SCHEMA$));
 
-    // Create Pipeline transformations
     final KafkaActivePowerTimestampReader kafka = new KafkaActivePowerTimestampReader(
-        this.bootstrapServer,
-        this.inputTopic,
-        this.buildConsumerConfig());
+        super.bootstrapServer,
+        super.inputTopic,
+        super.buildConsumerConfig());
 
-    // Apply pipeline transformations
-    // Read from Kafka
-    this.apply(kafka)
+    super.apply(kafka)
         .apply(Values.create())
         .apply(sinkType.create(config));
   }