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  package org.apache.cassandra.fuzz.harry.examples;
  
  import org.junit.Test;
  
  import org.apache.cassandra.distributed.test.IntegrationTestBase;
  import org.apache.cassandra.harry.SchemaSpec;
  import org.apache.cassandra.harry.checker.ModelChecker;
  import org.apache.cassandra.harry.dsl.HistoryBuilderHelper;
  import org.apache.cassandra.harry.dsl.ReplayingHistoryBuilder;
  import org.apache.cassandra.harry.dsl.SingleOperationBuilder;
  import org.apache.cassandra.harry.execution.InJvmDTestVisitExecutor;
  import org.apache.cassandra.harry.gen.Generator;
  import org.apache.cassandra.harry.gen.Generators;
  import org.apache.cassandra.harry.gen.SchemaGenerators;
  
  import static org.apache.cassandra.harry.checker.TestHelper.withRandom;
  
  public class RangeTombstoneBurnTest extends IntegrationTestBase
  {
      private final int ITERATIONS = 10;
      private final int STEPS_PER_ITERATION = 1000;
  
      @Test
      public void rangeTombstoneBurnTest()
      {
          Generator<SchemaSpec> schemaGen = SchemaGenerators.schemaSpecGen(KEYSPACE, "range_tombstone", 100);
          withRandom(rng -> {
              SchemaSpec schema = schemaGen.generate(rng);
              cluster.get(1).nodetool("disableautocompaction");
              cluster.schemaChange(schema.compile());
  
              int perIteration = Math.min(10, schema.valueGenerators.pkPopulation());;
              int maxPartitions = Math.max(perIteration, schema.valueGenerators.pkPopulation());
  
              for (int iteration = 0; iteration < ITERATIONS; iteration++)
              {
                  Integer[] partitions = new Integer[perIteration];
                  for (int j = 0; j < partitions.length && iteration * 10 < maxPartitions; j++)
                      partitions[j] = iteration * partitions.length + j;
  
                  float deleteRowChance = rng.nextFloat(0.99f, 1.0f);
                  float deletePartitionChance = rng.nextFloat(0.999f, 1.0f);
                  float deleteColumnsChance = rng.nextFloat(0.95f, 1.0f);
                  float deleteRangeChance = rng.nextFloat(0.95f, 1.0f);
                  float flushChance = rng.nextFloat(0.999f, 1.0f);
                  int maxPartitionSize = Math.min(rng.nextInt(1, 1 << rng.nextInt(5, 11)), schema.valueGenerators.ckPopulation());
  
                  Generator<Integer> partitionPicker = Generators.pick(partitions);
                  Generator<Integer> rowPicker = Generators.int32(0, maxPartitionSize);
                  ModelChecker<SingleOperationBuilder, Void> model = new ModelChecker<>();
                  ReplayingHistoryBuilder historyBuilder = new ReplayingHistoryBuilder(schema.valueGenerators,
                                                                                       (hb) -> InJvmDTestVisitExecutor.builder().build(schema, hb, cluster));
  
                  model.init(historyBuilder)
                       .step((history, rng_) -> {
                           int pdIdx = partitionPicker.generate(rng);
                           history.insert(pdIdx, rowPicker.generate(rng));
                           history.selectPartition(pdIdx);
                       })
                       .step((history, rng_) -> rng.nextDouble() >= deleteRowChance,
                             (history, rng_) -> {
                                 int pdIdx = partitionPicker.generate(rng);
                                 history.deleteRow(pdIdx, rowPicker.generate(rng));
                                 history.selectPartition(pdIdx);
                             })
                       .step((history, rng_) -> rng.nextDouble() >= deletePartitionChance,
                             (history, rng_) -> {
                                 int pdIdx = partitionPicker.generate(rng);
                                 history.deletePartition(pdIdx);
                                 history.selectPartition(pdIdx);
                             })
                       .step((history, rng_) -> rng.nextDouble() >= deleteColumnsChance,
                             (history, rng_) -> {
                                 int pdIdx = partitionPicker.generate(rng);
                                 HistoryBuilderHelper.deleteRandomColumns(schema, pdIdx, rowPicker.generate(rng), rng, history);
                                 history.selectPartition(pdIdx);
                             })
                       .step((history, rng_) -> rng.nextDouble() >= deleteRangeChance,
                             (history, rng_) -> {
                                 int pdIdx = partitionPicker.generate(rng);
                                 history.deleteRowRange(pdIdx,
                                                        rowPicker.generate(rng),
                                                        rowPicker.generate(rng),
                                                        rng.nextInt(schema.clusteringKeys.size()),
                                                        rng.nextBoolean(),
                                                        rng.nextBoolean()
                                 );
                                 history.selectPartition(pdIdx);
                             })
                       .step((history, rng_) -> {
                           int pdIdx = partitionPicker.generate(rng);
                           history.selectRow(pdIdx, rowPicker.generate(rng));
                       })
                       .step((history, rng_) -> {
                           int pdIdx = partitionPicker.generate(rng);
                           history.selectRowRange(pdIdx,
                                                  rowPicker.generate(rng),
                                                  rowPicker.generate(rng),
                                                  rng.nextInt(schema.clusteringKeys.size()),
                                                  rng.nextBoolean(),
                                                  rng.nextBoolean());
                       })
                       .step((history, rng_) -> rng.nextDouble() >= flushChance,
                             (history, rng_) -> {
                                 history.custom(() -> cluster.get(1).nodetool("flush", schema.keyspace, schema.table), "FLUSH");
                             })
                       .exitCondition((history) -> {
                           if (historyBuilder.size() < STEPS_PER_ITERATION)
                               return false;
                           return true;
                       })
                       .run(0, Long.MAX_VALUE, rng);
              }
          });
      }
  }