diff --git a/tests/test_community_fault_model.py b/tests/test_community_fault_model.py
index 8c37193..fbe0e41 100644
--- a/tests/test_community_fault_model.py
+++ b/tests/test_community_fault_model.py
@@ -1,8 +1,9 @@
 import numpy as np
 import pandas as pd
+import pytest
 
 from source_modelling import community_fault_model
-from source_modelling.community_fault_model import NodalPlane
+from source_modelling.community_fault_model import MovementSense, NodalPlane
 
 
 def test_can_load_community_fault_model():
@@ -20,6 +21,64 @@ def test_can_load_community_fault_model():
     assert len(gdf) == 880
 
 
+def test_loaded_faults_have_sense():
+    model = community_fault_model.get_community_fault_model()
+    for fault in model:
+        assert fault.sense != MovementSense(0), fault.name
+
+
+@pytest.mark.parametrize(
+    "unit, expected",
+    [
+        ("", None),
+        ("yrs", 1),
+        ("100 yrs", 100),
+        ("1,000s yrs", 1000),
+        ("Ma", 1_000_000),
+    ],
+)
+def test_parse_timeframe_unit(unit: str, expected: int | None):
+    assert community_fault_model.parse_timeframe_unit(unit) == expected
+
+
+@pytest.mark.parametrize("unit", ["days", "kyr", "1000"])
+def test_parse_timeframe_unit_unknown(unit: str):
+    with pytest.raises(ValueError, match="Unknown time unit"):
+        community_fault_model.parse_timeframe_unit(unit)
+
+
+@pytest.mark.parametrize(
+    "sense, expected",
+    [
+        ("", MovementSense(0)),
+        ("dextral", MovementSense.DEXTRAL),
+        ("sinistral", MovementSense.SINISTRAL),
+        ("normal", MovementSense.NORMAL),
+        ("reverse", MovementSense.REVERSE),
+        ("reverse dextral", MovementSense.DEXTRAL | MovementSense.REVERSE),
+        ("normal sinistral", MovementSense.NORMAL | MovementSense.SINISTRAL),
+    ],
+)
+def test_fault_sense_parse(sense: str, expected: MovementSense):
+    assert community_fault_model.fault_sense_parse(sense) == expected
+
+
+@pytest.mark.parametrize(
+    "point_b, expected",
+    [
+        ([5_010_000, 1_500_000], 0.0),
+        ([5_000_000, 1_510_000], 90.0),
+        ([4_990_000, 1_500_000], 180.0),
+        ([5_000_000, 1_490_000], 270.0),
+    ],
+)
+def test_line_segment_strike(point_b: list[float], expected: float):
+    strike = community_fault_model.line_segment_strike([5_000_000, 1_500_000], point_b)
+    # Allow for NZTM grid convergence (< ~3 degrees in New Zealand).
+    misfit = (strike - expected + 180) % 360 - 180
+    assert abs(misfit) < 3
+
+
 def test_most_likely_nodal_plane():
     solutions = pd.read_csv("tests/data/nodal_plane_labels.csv")
     model = community_fault_model.get_community_fault_model()