backend/core/trace_back_test.py

# Copyright 2023 DeepMind Technologies Limited
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================


"""
Unit and integration testing for the expanded trace_back module, including analytics, visualization, streaming, plugins, error handling, and benchmarking.
"""



import unittest
import random
import time
import threading
import tempfile
import os
from absl.testing import absltest
import ddar
import graph as gh
import problem as pr
import trace_back as tb
# --- Additional imports for advanced testing ---
from hypothesis import given, strategies as st
import logging
class TracebackPropertyBasedTest(unittest.TestCase):
  @given(st.lists(st.text(min_size=1, max_size=5), min_size=1, max_size=10))
  def test_randomized_dummy_traceback(self, names):
    # Small randomized test: ensure parallel traceback returns one log per query
    class DummyDepSmall:
      def __init__(self, name):
        self._name = name
      def hashed(self):
        return self._name
      @property
      def rule_name(self):
        return ''
      @property
      def why(self):
        return []
      def remove_loop(self):
        return self
    queries = [DummyDepSmall(n) for n in names]
    logs = tb.parallel_recursive_traceback(queries, max_workers=4)
    self.assertEqual(len(logs), len(names))

  @given(st.lists(st.text(min_size=1, max_size=10), min_size=10, max_size=100))
  def test_large_randomized_traceback(self, names):
    # Larger randomized test to exercise parallel traceback on many items
    class DummyDep:
      def __init__(self, name):
        self._name = name
      def hashed(self):
        return self._name
      @property
      def rule_name(self):
        return ''
      @property
      def why(self):
        return []
      def remove_loop(self):
        return self
    queries = [DummyDep(n) for n in names]
    logs = tb.parallel_recursive_traceback(queries, max_workers=4)
    self.assertEqual(len(logs), len(names))

  def test_fuzzing_malformed_dependencies(self):
    class MalformedDep:
      def __init__(self, name):
        self._name = name
      def hashed(self):
        if random.random() < 0.5:
          raise Exception("Malformed hash")
        return self._name
      @property
      def rule_name(self):
        return ''
      @property
      def why(self):
        return []
      def remove_loop(self):
        return self
    deps = [MalformedDep(f"bad{i}") for i in range(20)]
    for dep in deps:
      result = tb.safe_traceback(dep)
      self.assertTrue(result is None or isinstance(result, list))

  def test_plugin_chaining_and_dynamic_loading(self):
    class PluginA(tb.TracebackPlugin):
      def analyze(self, log):
        return 'A'
    class PluginB(tb.TracebackPlugin):
      def analyze(self, log):
        return 'B'
    pm = tb.TracebackPluginManager()
    pm.register('A', PluginA())
    pm.register('B', PluginB())
    log = [([DummyDep('A')], [DummyDep('B')])]
    results = pm.run_all(log)
    self.assertEqual(results['A'], 'A')
    self.assertEqual(results['B'], 'B')
    # Dynamic loading simulation
    for i in range(10):
      pm.register(f"dyn{i}", PluginA())
    results = pm.run_all(log)
    self.assertEqual(results['dyn9'], 'A')

  def test_streaming_under_failure(self):
    log = [([DummyDep('A')], [DummyDep('B')]) for _ in range(5)]
    streamer = tb.TracebackStreamer()
    results = []
    def faulty_listener(step):
      if len(results) == 2:
        raise Exception("Listener failure")
      results.append(step)
    streamer.add_listener(faulty_listener)
    t = threading.Thread(target=lambda: streamer.stream(log))
    t.start()
    t.join()
    self.assertGreaterEqual(len(results), 2)

  def test_provenance_export_and_import(self):
    log = [([DummyDep('A')], [DummyDep('B')]) for _ in range(3)]
    with tempfile.NamedTemporaryFile(delete=False) as f:
      tb.export_traceback_provenance(log, f.name)
      self.assertTrue(os.path.exists(f.name))
      with open(f.name, 'r', encoding='utf-8') as fin:
        data = fin.read()
        self.assertIn('prems', data)
    os.remove(f.name)

  def test_compliance_logging_and_error_propagation(self):
    logger = logging.getLogger('traceback_compliance')
    logger.setLevel(logging.INFO)
    with self.assertLogs('traceback_compliance', level='INFO') as cm:
      logger.info('Compliance event')
    self.assertIn('Compliance event', cm.output[0])

  def test_stress_parallel_streaming(self):
    log = [([DummyDep(f"A{i}")], [DummyDep(f"B{i}")]) for i in range(100)]
    streamer = tb.TracebackStreamer()
    results = []
    streamer.add_listener(lambda step: results.append(step))
    t = threading.Thread(target=lambda: streamer.stream(log))
    t.start()
    t.join()
    self.assertEqual(len(results), 100)
    class DummyDep:
      def __init__(self, name):
        self._name = name
      def hashed(self):
        return self._name
      @property
      def rule_name(self):
        return ''
      @property
      def why(self):
        return []
      def remove_loop(self):
        return self
    queries = [DummyDep(n) for n in names]
    logs = tb.parallel_recursive_traceback(queries, max_workers=2)
    self.assertEqual(len(logs), len(names))

  def test_empty_and_cyclic(self):
    # Empty log
    stats = tb.traceback_statistics([])
    self.assertEqual(stats['num_steps'], 0)
    # Cyclic dependency (should not hang)
    class CyclicDep:
      def __init__(self, name):
        self._name = name
      def hashed(self):
        return self._name
      @property
      def rule_name(self):
        return ''
      @property
      def why(self):
        return [self]
      def remove_loop(self):
        return self
    result = tb.safe_traceback(CyclicDep('cycle'))
    self.assertIsInstance(result, list)

  def test_plugin_chaining(self):
    class PluginA(tb.TracebackPlugin):
      def analyze(self, log):
        return 'A'
    class PluginB(tb.TracebackPlugin):
      def analyze(self, log):
        return 'B'
    pm = tb.TracebackPluginManager()
    pm.register('A', PluginA())
    pm.register('B', PluginB())
    log = [([DummyDep('A')], [DummyDep('B')])]
    results = pm.run_all(log)
    self.assertEqual(results['A'], 'A')
    self.assertEqual(results['B'], 'B')

  def test_external_prover_stub(self):
    called = []
    def prover_api(step):
      called.append(step)
    log = [([DummyDep('A')], [DummyDep('B')]) for _ in range(3)]
    tb.integrate_external_prover(log, prover_api)
    self.assertEqual(len(called), 3)

  def test_logging_and_compliance(self):
    logger = logging.getLogger('traceback_test')
    logger.setLevel(logging.INFO)
    with self.assertLogs('traceback_test', level='INFO') as cm:
      logger.info('Compliance log test')
    self.assertIn('Compliance log test', cm.output[0])



class DummyDep:
  def __init__(self, name):
    self._name = name
  def hashed(self):
    return self._name
  @property
  def rule_name(self):
    return random.choice(['', 'c0', 'collx', 'coll'])
  @property
  def why(self):
    return []
  def remove_loop(self):
    return self

class TracebackAdvancedTest(unittest.TestCase):
  def test_traceback_statistics(self):
    log = [[DummyDep('A')], [DummyDep('B')]]
    log = [(l, [DummyDep('C')]) for l in log]
    stats = tb.traceback_statistics(log)
    self.assertIn('num_steps', stats)

  def test_export_provenance(self):
    log = [([DummyDep('A')], [DummyDep('B')])]
    with tempfile.NamedTemporaryFile(delete=False) as f:
      tb.export_traceback_provenance(log, f.name)
      self.assertTrue(os.path.exists(f.name))
    os.remove(f.name)

  def test_visualization(self):
    log = [([DummyDep('A')], [DummyDep('B')])]
    tb.visualize_traceback_graph(log, show=False)

  def test_parallel_traceback(self):
    queries = [DummyDep(f"Q{i}") for i in range(10)]
    logs = tb.parallel_recursive_traceback(queries, max_workers=2)
    self.assertEqual(len(logs), 10)

  def test_streaming(self):
    log = [([DummyDep('A')], [DummyDep('B')]) for _ in range(5)]
    streamer = tb.TracebackStreamer()
    results = []
    streamer.add_listener(lambda step: results.append(step))
    t = threading.Thread(target=lambda: streamer.stream(log))
    t.start()
    t.join()
    self.assertEqual(len(results), 5)

  def test_plugin_system(self):
    class StepCountPlugin(tb.TracebackPlugin):
      def analyze(self, log):
        return len(log)
    pm = tb.TracebackPluginManager()
    pm.register("step_count", StepCountPlugin())
    log = [([DummyDep('A')], [DummyDep('B')]) for _ in range(3)]
    results = pm.run_all(log)
    self.assertEqual(results['step_count'], 3)

  def test_safe_traceback(self):
    class BadDep:
      def hashed(self):
        raise Exception("fail")
      def remove_loop(self):
        return self
    result = tb.safe_traceback(BadDep())
    self.assertIsNone(result)

  def test_benchmark_large_dag(self):
    # Stress test with a large number of dummy dependencies
    n = 1000
    queries = [DummyDep(f"Q{i}") for i in range(n)]
    start = time.time()
    logs = tb.parallel_recursive_traceback(queries, max_workers=8)
    elapsed = time.time() - start
    self.assertEqual(len(logs), n)
    self.assertLess(elapsed, 10)  # Should finish quickly

  @classmethod
  def setUpClass(cls):
    super().setUpClass()
    cls.defs = pr.Definition.from_txt_file('defs.txt', to_dict=True)
    cls.rules = pr.Theorem.from_txt_file('rules.txt', to_dict=True)

  def test_orthocenter_dependency_difference(self):
    txt = 'a b c = triangle a b c; d = on_tline d b a c, on_tline d c a b; e = on_line e a c, on_line e b d ? perp a d b c'  # pylint: disable=line-too-long
    p = pr.Problem.from_txt(txt)
    g, _ = gh.Graph.build_problem(p, TracebackTest.defs)

    ddar.solve(g, TracebackTest.rules, p)

    goal_args = g.names2nodes(p.goal.args)
    query = pr.Dependency(p.goal.name, goal_args, None, None)

    setup, aux, _, _ = tb.get_logs(query, g, merge_trivials=False)

    # Convert each predicates to its hash string:
    setup = [p.hashed() for p in setup]
    aux = [p.hashed() for p in aux]

    self.assertCountEqual(
        setup, [('perp', 'a', 'c', 'b', 'd'), ('perp', 'a', 'b', 'c', 'd')]
    )

    self.assertCountEqual(
        aux, [('coll', 'a', 'c', 'e'), ('coll', 'b', 'd', 'e')]
    )



if __name__ == '__main__':
  absltest.main()