#!/usr/bin/env python
#
# Copyright 2017 the V8 project authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.


from os.path import join
import json
import math
import multiprocessing
import os
import random
import shlex
import sys
import time

# Adds testrunner to the path hence it has to be imported at the beggining.
import base_runner

from testrunner.local import execution
from testrunner.local import progress
from testrunner.local import testsuite
from testrunner.local import utils
from testrunner.local import verbose
from testrunner.objects import context


DEFAULT_SUITES = ["mjsunit", "webkit"]
TIMEOUT_DEFAULT = 60

# Double the timeout for these:
SLOW_ARCHS = ["arm",
              "mipsel"]
MAX_DEOPT = 1000000000
DISTRIBUTION_MODES = ["smooth", "random"]


class DeoptFuzzer(base_runner.BaseTestRunner):
  def __init__(self, *args, **kwargs):
    super(DeoptFuzzer, self).__init__(*args, **kwargs)

  class RandomDistribution:
    def __init__(self, seed=None):
      seed = seed or random.randint(1, sys.maxint)
      print "Using random distribution with seed %d" % seed
      self._random = random.Random(seed)

    def Distribute(self, n, m):
      if n > m:
        n = m
      return self._random.sample(xrange(1, m + 1), n)

  class SmoothDistribution:
    """Distribute n numbers into the interval [1:m].
    F1: Factor of the first derivation of the distribution function.
    F2: Factor of the second derivation of the distribution function.
    With F1 and F2 set to 0, the distribution will be equal.
    """
    def __init__(self, factor1=2.0, factor2=0.2):
      self._factor1 = factor1
      self._factor2 = factor2

    def Distribute(self, n, m):
      if n > m:
        n = m
      if n <= 1:
        return [ 1 ]

      result = []
      x = 0.0
      dx = 1.0
      ddx = self._factor1
      dddx = self._factor2
      for i in range(0, n):
        result += [ x ]
        x += dx
        dx += ddx
        ddx += dddx

      # Project the distribution into the interval [0:M].
      result = [ x * m / result[-1] for x in result ]

      # Equalize by n. The closer n is to m, the more equal will be the
      # distribution.
      for (i, x) in enumerate(result):
        # The value of x if it was equally distributed.
        equal_x = i / float(n - 1) * float(m - 1) + 1

        # Difference factor between actual and equal distribution.
        diff = 1 - (x / equal_x)

        # Equalize x dependent on the number of values to distribute.
        result[i] = int(x + (i + 1) * diff)
      return result


  def _distribution(self, options):
    if options.distribution_mode == "random":
      return self.RandomDistribution(options.seed)
    if options.distribution_mode == "smooth":
      return self.SmoothDistribution(options.distribution_factor1,
                                     options.distribution_factor2)


  def _add_parser_options(self, parser):
    parser.add_option("--command-prefix",
                      help="Prepended to each shell command used to run a test",
                      default="")
    parser.add_option("--coverage", help=("Exponential test coverage "
                      "(range 0.0, 1.0) - 0.0: one test, 1.0 all tests (slow)"),
                      default=0.4, type="float")
    parser.add_option("--coverage-lift", help=("Lifts test coverage for tests "
                      "with a small number of deopt points (range 0, inf)"),
                      default=20, type="int")
    parser.add_option("--distribution-factor1", help=("Factor of the first "
                      "derivation of the distribution function"), default=2.0,
                      type="float")
    parser.add_option("--distribution-factor2", help=("Factor of the second "
                      "derivation of the distribution function"), default=0.7,
                      type="float")
    parser.add_option("--distribution-mode", help=("How to select deopt points "
                      "for a given test (smooth|random)"),
                      default="smooth")
    parser.add_option("--dump-results-file", help=("Dump maximum number of "
                      "deopt points per test to a file"))
    parser.add_option("--extra-flags",
                      help="Additional flags to pass to each test command",
                      default="")
    parser.add_option("--isolates", help="Whether to test isolates",
                      default=False, action="store_true")
    parser.add_option("-j", help="The number of parallel tasks to run",
                      default=0, type="int")
    parser.add_option("-p", "--progress",
                      help=("The style of progress indicator"
                            " (verbose, dots, color, mono)"),
                      choices=progress.PROGRESS_INDICATORS.keys(),
                      default="mono")
    parser.add_option("--seed", help="The seed for the random distribution",
                      type="int")
    parser.add_option("-t", "--timeout", help="Timeout in seconds",
                      default= -1, type="int")
    parser.add_option("--random-seed", default=0, dest="random_seed",
                      help="Default seed for initializing random generator")
    parser.add_option("--fuzzer-random-seed", default=0,
                      help="Default seed for initializing fuzzer random "
                      "generator")
    return parser


  def _process_options(self, options):
    # Special processing of other options, sorted alphabetically.
    options.command_prefix = shlex.split(options.command_prefix)
    options.extra_flags = shlex.split(options.extra_flags)
    if options.j == 0:
      options.j = multiprocessing.cpu_count()
    while options.random_seed == 0:
      options.random_seed = random.SystemRandom().randint(-2147483648,
                                                          2147483647)
    if not options.distribution_mode in DISTRIBUTION_MODES:
      print "Unknown distribution mode %s" % options.distribution_mode
      return False
    if options.distribution_factor1 < 0.0:
      print ("Distribution factor1 %s is out of range. Defaulting to 0.0"
          % options.distribution_factor1)
      options.distribution_factor1 = 0.0
    if options.distribution_factor2 < 0.0:
      print ("Distribution factor2 %s is out of range. Defaulting to 0.0"
          % options.distribution_factor2)
      options.distribution_factor2 = 0.0
    if options.coverage < 0.0 or options.coverage > 1.0:
      print ("Coverage %s is out of range. Defaulting to 0.4"
          % options.coverage)
      options.coverage = 0.4
    if options.coverage_lift < 0:
      print ("Coverage lift %s is out of range. Defaulting to 0"
          % options.coverage_lift)
      options.coverage_lift = 0
    return True

  def _calculate_n_tests(self, m, options):
    """Calculates the number of tests from m deopt points with exponential
    coverage.
    The coverage is expected to be between 0.0 and 1.0.
    The 'coverage lift' lifts the coverage for tests with smaller m values.
    """
    c = float(options.coverage)
    l = float(options.coverage_lift)
    return int(math.pow(m, (m * c + l) / (m + l)))

  def _get_default_suite_names(self):
    return DEFAULT_SUITES

  def _do_execute(self, suites, args, options):
    print(">>> Running tests for %s.%s" % (self.build_config.arch,
                                           self.mode_name))

    dist = self._distribution(options)

    # Populate context object.
    timeout = options.timeout
    if timeout == -1:
      # Simulators are slow, therefore allow a longer default timeout.
      if self.build_config.arch in SLOW_ARCHS:
        timeout = 2 * TIMEOUT_DEFAULT;
      else:
        timeout = TIMEOUT_DEFAULT;

    timeout *= self.mode_options.timeout_scalefactor
    ctx = context.Context(self.build_config.arch,
                          self.mode_options.execution_mode,
                          self.outdir,
                          self.mode_options.flags, options.verbose,
                          timeout, options.isolates,
                          options.command_prefix,
                          options.extra_flags,
                          False,  # Keep i18n on by default.
                          options.random_seed,
                          True,  # No sorting of test cases.
                          0,  # Don't rerun failing tests.
                          0,  # No use of a rerun-failing-tests maximum.
                          False,  # No no_harness mode.
                          False,  # Don't use perf data.
                          False)  # Coverage not supported.

    # Find available test suites and read test cases from them.
    variables = {
      "arch": self.build_config.arch,
      "asan": self.build_config.asan,
      "byteorder": sys.byteorder,
      "dcheck_always_on": self.build_config.dcheck_always_on,
      "deopt_fuzzer": True,
      "gc_fuzzer": False,
      "gc_stress": False,
      "gcov_coverage": self.build_config.gcov_coverage,
      "isolates": options.isolates,
      "mode": self.mode_options.status_mode,
      "msan": self.build_config.msan,
      "no_harness": False,
      "no_i18n": self.build_config.no_i18n,
      "no_snap": self.build_config.no_snap,
      "novfp3": False,
      "predictable": self.build_config.predictable,
      "simulator": utils.UseSimulator(self.build_config.arch),
      "simulator_run": False,
      "system": utils.GuessOS(),
      "tsan": self.build_config.tsan,
      "ubsan_vptr": self.build_config.ubsan_vptr,
    }
    num_tests = 0
    test_id = 0

    # Remember test case prototypes for the fuzzing phase.
    test_backup = dict((s, []) for s in suites)

    for s in suites:
      s.ReadStatusFile(variables)
      s.ReadTestCases(ctx)
      if len(args) > 0:
        s.FilterTestCasesByArgs(args)
      s.FilterTestCasesByStatus(False)

      test_backup[s] = s.tests
      analysis_flags = ["--deopt-every-n-times", "%d" % MAX_DEOPT,
                        "--print-deopt-stress"]
      s.tests = [t.create_variant(t.variant, analysis_flags, 'analysis')
                 for t in s.tests]
      num_tests += len(s.tests)
      for t in s.tests:
        t.id = test_id
        t.cmd = t.get_command(ctx)
        test_id += 1

    if num_tests == 0:
      print "No tests to run."
      return 0

    print(">>> Collection phase")
    progress_indicator = progress.PROGRESS_INDICATORS[options.progress]()
    runner = execution.Runner(suites, progress_indicator, ctx)

    exit_code = runner.Run(options.j)

    print(">>> Analysis phase")
    num_tests = 0
    test_id = 0
    for s in suites:
      test_results = {}
      for t in s.tests:
        for line in runner.outputs[t].stdout.splitlines():
          if line.startswith("=== Stress deopt counter: "):
            test_results[t.path] = MAX_DEOPT - int(line.split(" ")[-1])
      for t in s.tests:
        if t.path not in test_results:
          print "Missing results for %s" % t.path
      if options.dump_results_file:
        results_dict = dict((t.path, n) for (t, n) in test_results.iteritems())
        with file("%s.%d.txt" % (options.dump_results_file, time.time()),
                  "w") as f:
          f.write(json.dumps(results_dict))

      # Reset tests and redistribute the prototypes from the collection phase.
      s.tests = []
      if options.verbose:
        print "Test distributions:"
      for t in test_backup[s]:
        max_deopt = test_results.get(t.path, 0)
        if max_deopt == 0:
          continue
        n_deopt = self._calculate_n_tests(max_deopt, options)
        distribution = dist.Distribute(n_deopt, max_deopt)
        if options.verbose:
          print "%s %s" % (t.path, distribution)
        for n, d in enumerate(distribution):
          fuzzing_flags = ["--deopt-every-n-times", "%d" % d]
          s.tests.append(t.create_variant(t.variant, fuzzing_flags, n))
      num_tests += len(s.tests)
      for t in s.tests:
        t.id = test_id
        t.cmd = t.get_command(ctx)
        test_id += 1

    if num_tests == 0:
      print "No tests to run."
      return exit_code

    print(">>> Deopt fuzzing phase (%d test cases)" % num_tests)
    progress_indicator = progress.PROGRESS_INDICATORS[options.progress]()
    runner = execution.Runner(suites, progress_indicator, ctx)

    code = runner.Run(options.j)
    return exit_code or code


if __name__ == '__main__':
  sys.exit(DeoptFuzzer().execute())