wehub-resource-sync
195 lines
7.3 KiB
Python
195 lines
7.3 KiB
Python
"""Tests for semantically_similar_to edge support."""
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import networkx as nx
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import pytest
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from graphify.build import build_from_json
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from graphify.analyze import surprising_connections, _surprise_score
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from graphify.report import generate
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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def _make_extraction_with_semantic_edge():
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"""Two nodes in separate files connected by a semantically_similar_to edge."""
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return {
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"nodes": [
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{"id": "a_validate_input", "label": "validate_input", "file_type": "code",
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"source_file": "auth/validators.py", "source_location": "L5"},
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{"id": "b_check_input", "label": "check_input", "file_type": "code",
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"source_file": "api/checks.py", "source_location": "L12"},
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],
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"edges": [
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{
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"source": "a_validate_input",
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"target": "b_check_input",
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"relation": "semantically_similar_to",
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"confidence": "INFERRED",
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"confidence_score": 0.82,
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"source_file": "auth/validators.py",
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"source_location": None,
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"weight": 0.82,
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}
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],
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"input_tokens": 100,
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"output_tokens": 50,
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}
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def _make_graph_with_semantic_edge():
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return build_from_json(_make_extraction_with_semantic_edge())
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def _make_two_edge_graph():
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"""Graph with one semantically_similar_to edge and one references edge, both cross-file."""
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G = nx.Graph()
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for nid, label, src in [
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("a", "ValidateInput", "auth/validators.py"),
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("b", "CheckInput", "api/checks.py"),
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("c", "LoadConfig", "config/loader.py"),
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("d", "ReadConfig", "utils/reader.py"),
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]:
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G.add_node(nid, label=label, source_file=src, file_type="code")
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# semantically_similar_to edge
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G.add_edge("a", "b", relation="semantically_similar_to", confidence="INFERRED",
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confidence_score=0.82, source_file="auth/validators.py", weight=0.82,
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_src="a", _tgt="b")
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# plain references edge (same confidence tier)
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G.add_edge("c", "d", relation="references", confidence="INFERRED",
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confidence_score=0.7, source_file="config/loader.py", weight=0.7,
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_src="c", _tgt="d")
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return G
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# ---------------------------------------------------------------------------
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# Test 1: semantically_similar_to passes through build_from_json without being dropped
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# ---------------------------------------------------------------------------
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def test_semantic_edge_survives_build_from_json():
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G = _make_graph_with_semantic_edge()
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assert G.number_of_edges() == 1
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u, v, data = next(iter(G.edges(data=True)))
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assert data["relation"] == "semantically_similar_to"
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def test_semantic_edge_nodes_present():
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G = _make_graph_with_semantic_edge()
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assert "a_validate_input" in G.nodes
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assert "b_check_input" in G.nodes
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# ---------------------------------------------------------------------------
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# Test 2: confidence_score is preserved for semantically_similar_to edges
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# ---------------------------------------------------------------------------
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def test_semantic_edge_confidence_score_preserved():
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G = _make_graph_with_semantic_edge()
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u, v, data = next(iter(G.edges(data=True)))
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assert data.get("confidence_score") == pytest.approx(0.82)
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assert data.get("confidence") == "INFERRED"
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# ---------------------------------------------------------------------------
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# Test 3: surprising_connections scores semantically_similar_to edges higher
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# than references edges with the same community membership
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# ---------------------------------------------------------------------------
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def test_semantic_edge_scores_higher_than_references():
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G = _make_two_edge_graph()
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communities = {0: ["a", "b"], 1: ["c", "d"]}
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node_community = {"a": 0, "b": 0, "c": 1, "d": 1}
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score_sem, reasons_sem = _surprise_score(
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G, "a", "b", G.edges["a", "b"], node_community,
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"auth/validators.py", "api/checks.py"
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)
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score_ref, _ = _surprise_score(
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G, "c", "d", G.edges["c", "d"], node_community,
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"config/loader.py", "utils/reader.py"
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)
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assert score_sem > score_ref
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def test_semantic_edge_reason_mentions_similarity():
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G = _make_two_edge_graph()
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communities = {0: ["a", "b"], 1: ["c", "d"]}
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node_community = {"a": 0, "b": 0, "c": 1, "d": 1}
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_, reasons = _surprise_score(
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G, "a", "b", G.edges["a", "b"], node_community,
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"auth/validators.py", "api/checks.py"
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)
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assert any("similar" in r for r in reasons)
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# ---------------------------------------------------------------------------
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# Test 4: report renders [semantically similar] tag for these edges
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# ---------------------------------------------------------------------------
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def _make_report_with_semantic_surprise():
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G = _make_graph_with_semantic_edge()
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communities = {0: ["a_validate_input", "b_check_input"]}
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cohesion = {0: 0.5}
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labels = {0: "Validators"}
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gods = []
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surprises = [
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{
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"source": "validate_input",
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"target": "check_input",
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"relation": "semantically_similar_to",
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"confidence": "INFERRED",
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"confidence_score": 0.82,
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"source_files": ["auth/validators.py", "api/checks.py"],
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"why": "semantically similar concepts with no structural link",
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}
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]
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detection = {"total_files": 2, "total_words": 500, "needs_graph": True, "warning": None}
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tokens = {"input": 100, "output": 50}
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return generate(G, communities, cohesion, labels, gods, surprises, detection, tokens, "./project")
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def test_report_renders_semantically_similar_tag():
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report = _make_report_with_semantic_surprise()
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assert "[semantically similar]" in report
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def test_report_semantic_tag_on_correct_line():
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report = _make_report_with_semantic_surprise()
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for line in report.splitlines():
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if "semantically_similar_to" in line:
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assert "[semantically similar]" in line
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break
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else:
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pytest.fail("No line with semantically_similar_to found in report")
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def test_report_no_semantic_tag_for_other_relations():
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"""Non-semantic edges must not get the [semantically similar] tag."""
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G = nx.Graph()
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for nid, label, src in [
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("x", "Alpha", "repo1/a.py"),
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("y", "Beta", "repo2/b.py"),
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]:
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G.add_node(nid, label=label, source_file=src, file_type="code")
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G.add_edge("x", "y", relation="references", confidence="EXTRACTED",
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confidence_score=1.0, source_file="repo1/a.py", weight=1.0)
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communities = {0: ["x", "y"]}
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cohesion = {0: 0.5}
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labels = {0: "Misc"}
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gods = []
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surprises = [
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{
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"source": "Alpha",
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"target": "Beta",
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"relation": "references",
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"confidence": "EXTRACTED",
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"source_files": ["repo1/a.py", "repo2/b.py"],
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"why": "cross-file connection",
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}
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]
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detection = {"total_files": 2, "total_words": 200, "needs_graph": True, "warning": None}
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tokens = {"input": 50, "output": 25}
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report = generate(G, communities, cohesion, labels, gods, surprises, detection, tokens, "./project")
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assert "[semantically similar]" not in report
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