"""Tests for AdaptiveInterviewEnv. Teammate 1 owns this file. """ import pytest from hypothesis import given, settings import hypothesis.strategies as st # Feature: adaptive-interview-env, Property 1: Reset initializes all skill dimensions to 0.5 @settings(max_examples=100) @given(seed=st.one_of(st.integers(), st.none())) def test_reset_initializes_skill_profile_to_0_5(seed): # TODO (Teammate 1) pass # Feature: adaptive-interview-env, Property 2: Seeded reset is deterministic @settings(max_examples=100) @given(seed=st.integers()) def test_seeded_reset_is_deterministic(seed): # TODO (Teammate 1) pass # Feature: adaptive-interview-env, Property 3: step() returns valid 5-tuple for any valid action @settings(max_examples=100) @given(action=st.fixed_dictionaries({ "correctness": st.floats(0.0, 1.0), "edge_case_coverage": st.floats(0.0, 1.0), "complexity_analysis": st.floats(0.0, 1.0), "tradeoff_reasoning": st.floats(0.0, 1.0), "communication_clarity": st.floats(0.0, 1.0), })) def test_step_returns_valid_tuple_for_valid_action(action): # TODO (Teammate 1) pass # Feature: adaptive-interview-env, Property 4: step() raises ValueError for malformed action def test_step_raises_value_error_for_malformed_action(): # TODO (Teammate 1) pass # Feature: adaptive-interview-env, Property 7: Skill profile values always in [0.0, 1.0] def test_skill_profile_values_always_in_range(): # TODO (Teammate 1) pass # Feature: adaptive-interview-env, Property 8: Skill profile history length equals step count def test_skill_profile_history_length_equals_step_count(): # TODO (Teammate 1) pass # Feature: adaptive-interview-env, Property 16: info dict always contains reward component keys def test_info_contains_reward_component_keys(): # TODO (Teammate 1) pass # Feature: adaptive-interview-env, Property 18: metrics() rolling mean correctness @settings(max_examples=100) @given(rewards=st.lists(st.floats(-1.0, 1.0), min_size=1, max_size=200)) def test_metrics_rolling_mean_correctness(rewards): # TODO (Teammate 1) pass