diff --git a/spacy/tests/matcher/test_matcher_bugfixes.py b/spacy/tests/matcher/test_matcher_bugfixes.py
deleted file mode 100644
index 70946ec74..000000000
--- a/spacy/tests/matcher/test_matcher_bugfixes.py
+++ /dev/null
@@ -1,200 +0,0 @@
-import pytest
-import numpy
-import os
-
-import spacy
-from spacy.matcher import Matcher
-from spacy.attrs import ORTH, LOWER, ENT_IOB, ENT_TYPE
-from spacy.attrs import ORTH, TAG, LOWER, IS_ALPHA, FLAG63
-from spacy.symbols import DATE, LOC
-
-
-def test_overlap_issue118(EN):
-    '''Test a bug that arose from having overlapping matches'''
-    doc = EN.tokenizer(u'how many points did lebron james score against the boston celtics last night')
-    ORG = doc.vocab.strings['ORG']
-    matcher = Matcher(EN.vocab,
-        {'BostonCeltics':
-            ('ORG', {},
-                [
-                    [{LOWER: 'celtics'}],
-                    [{LOWER: 'boston'}, {LOWER: 'celtics'}],
-                ]
-            )
-        }
-    )
-    
-    assert len(list(doc.ents)) == 0
-    matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
-    assert matches == [(ORG, 9, 11), (ORG, 10, 11)]
-    doc.ents = matches[:1]
-    ents = list(doc.ents)
-    assert len(ents) == 1
-    assert ents[0].label == ORG
-    assert ents[0].start == 9
-    assert ents[0].end == 11
-
-
-def test_overlap_issue242():
-    '''Test overlapping multi-word phrases.'''
-
-    patterns = [
-        [{LOWER: 'food'}, {LOWER: 'safety'}],
-        [{LOWER: 'safety'}, {LOWER: 'standards'}],
-    ]
-
-    if os.environ.get('SPACY_DATA'):
-        data_dir = os.environ.get('SPACY_DATA')
-    else:
-        data_dir = None
- 
-    nlp = spacy.en.English(path=data_dir, tagger=False, parser=False, entity=False)
-    nlp.matcher = Matcher(nlp.vocab)
-
-    nlp.matcher.add('FOOD', 'FOOD', {}, patterns)
-
-    doc = nlp.tokenizer(u'There are different food safety standards in different countries.')
-
-    matches = [(ent_type, start, end) for ent_id, ent_type, start, end in nlp.matcher(doc)]
-    doc.ents += tuple(matches)
-    food_safety, safety_standards = matches
-    assert food_safety[1] == 3
-    assert food_safety[2] == 5
-    assert safety_standards[1] == 4
-    assert safety_standards[2] == 6
-
-
-def test_overlap_reorder(EN):
-    '''Test order dependence'''
-    doc = EN.tokenizer(u'how many points did lebron james score against the boston celtics last night')
-    ORG = doc.vocab.strings['ORG']
-    matcher = Matcher(EN.vocab,
-        {'BostonCeltics':
-            ('ORG', {},
-                [
-                    [{LOWER: 'boston'}, {LOWER: 'celtics'}],
-                    [{LOWER: 'celtics'}],
-                ]
-            )
-        }
-    )
-    
-    assert len(list(doc.ents)) == 0
-    matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
-    assert matches == [(ORG, 9, 11), (ORG, 10, 11)]
-    doc.ents = matches[:1]
-    ents = list(doc.ents)
-    assert len(ents) == 1
-    assert ents[0].label == ORG
-    assert ents[0].start == 9
-    assert ents[0].end == 11
-
-
-def test_overlap_prefix(EN):
-    '''Test order dependence'''
-    doc = EN.tokenizer(u'how many points did lebron james score against the boston celtics last night')
-    ORG = doc.vocab.strings['ORG']
-    matcher = Matcher(EN.vocab,
-        {'BostonCeltics':
-            ('ORG', {},
-                [
-                    [{LOWER: 'boston'}],
-                    [{LOWER: 'boston'}, {LOWER: 'celtics'}],
-                ]
-            )
-        }
-    )
-    
-    assert len(list(doc.ents)) == 0
-    matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
-    doc.ents = matches[1:]
-    assert matches == [(ORG, 9, 10), (ORG, 9, 11)]
-    ents = list(doc.ents)
-    assert len(ents) == 1
-    assert ents[0].label == ORG
-    assert ents[0].start == 9
-    assert ents[0].end == 11
-
-
-def test_overlap_prefix_reorder(EN):
-    '''Test order dependence'''
-    doc = EN.tokenizer(u'how many points did lebron james score against the boston celtics last night')
-    ORG = doc.vocab.strings['ORG']
-    matcher = Matcher(EN.vocab,
-        {'BostonCeltics':
-            ('ORG', {},
-                [
-                    [{LOWER: 'boston'}, {LOWER: 'celtics'}],
-                    [{LOWER: 'boston'}],
-                ]
-            )
-        }
-    )
-    
-    assert len(list(doc.ents)) == 0
-    matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
-    doc.ents += tuple(matches)[1:]
-    assert matches == [(ORG, 9, 10), (ORG, 9, 11)]
-    ents = doc.ents
-    assert len(ents) == 1
-    assert ents[0].label == ORG
-    assert ents[0].start == 9
-    assert ents[0].end == 11
-
-
-# @pytest.mark.models
-# def test_ner_interaction(EN):
-#     EN.matcher.add('LAX_Airport', 'AIRPORT', {}, [[{ORTH: 'LAX'}]])
-#     EN.matcher.add('SFO_Airport', 'AIRPORT', {}, [[{ORTH: 'SFO'}]])
-#     doc = EN(u'get me a flight from SFO to LAX leaving 20 December and arriving on January 5th')
-
-#     ents = [(ent.label_, ent.text) for ent in doc.ents]
-#     assert ents[0] == ('AIRPORT', 'SFO')
-#     assert ents[1] == ('AIRPORT', 'LAX')
-#     assert ents[2] == ('DATE', '20 December')
-#     assert ents[3] == ('DATE', 'January 5th')
- 
-
-# @pytest.mark.models
-# def test_ner_interaction(EN):
-#     # ensure that matcher doesn't overwrite annotations set by the NER model
-#     doc = EN.tokenizer.tokens_from_list(u'get me a flight from SFO to LAX leaving 20 December and arriving on January 5th'.split(' '))
-#     EN.tagger(doc)
-
-#     columns = [ENT_IOB, ENT_TYPE]
-#     values = numpy.ndarray(shape=(len(doc),len(columns)), dtype='int32')
-#     # IOB values are 0=missing, 1=I, 2=O, 3=B 
-#     iobs = [2,2,2,2,2,3,2,3,2,3,1,2,2,2,3,1]
-#     types = [0,0,0,0,0,LOC,0,LOC,0,DATE,DATE,0,0,0,DATE,DATE]
-#     values[:] = zip(iobs,types)
-#     doc.from_array(columns,values)
-
-#     assert doc[5].ent_type_ == 'LOC'
-#     assert doc[7].ent_type_ == 'LOC'
-#     assert doc[9].ent_type_ == 'DATE'
-#     assert doc[10].ent_type_ == 'DATE'
-#     assert doc[14].ent_type_ == 'DATE'
-#     assert doc[15].ent_type_ == 'DATE'
-
-#     EN.matcher.add('LAX_Airport', 'AIRPORT', {}, [[{ORTH: 'LAX'}]])
-#     EN.matcher.add('SFO_Airport', 'AIRPORT', {}, [[{ORTH: 'SFO'}]])
-#     EN.matcher(doc)
-
-#     assert doc[5].ent_type_ != 'AIRPORT'
-#     assert doc[7].ent_type_ != 'AIRPORT'
-#     assert doc[5].ent_type_ == 'LOC'
-#     assert doc[7].ent_type_ == 'LOC'
-#     assert doc[9].ent_type_ == 'DATE'
-#     assert doc[10].ent_type_ == 'DATE'
-#     assert doc[14].ent_type_ == 'DATE'
-#     assert doc[15].ent_type_ == 'DATE'
-
-
-
-
-
-
-
-
-
-
diff --git a/spacy/tests/regression/test_issue118.py b/spacy/tests/regression/test_issue118.py
new file mode 100644
index 000000000..7996b1f2f
--- /dev/null
+++ b/spacy/tests/regression/test_issue118.py
@@ -0,0 +1,55 @@
+# coding: utf-8
+"""Test a bug that arose from having overlapping matches"""
+
+
+from __future__ import unicode_literals
+
+from ...matcher import Matcher
+from ...attrs import ORTH, LOWER
+
+import pytest
+
+
+pattern1 = [[{LOWER: 'celtics'}], [{LOWER: 'boston'}, {LOWER: 'celtics'}]]
+pattern2 = [[{LOWER: 'boston'}, {LOWER: 'celtics'}], [{LOWER: 'celtics'}]]
+pattern3 = [[{LOWER: 'boston'}], [{LOWER: 'boston'}, {LOWER: 'celtics'}]]
+pattern4 = [[{LOWER: 'boston'}, {LOWER: 'celtics'}], [{LOWER: 'boston'}]]
+
+
+@pytest.fixture
+def doc(en_tokenizer):
+    text = "how many points did lebron james score against the boston celtics last night"
+    doc = en_tokenizer(text)
+    return doc
+
+
+@pytest.mark.parametrize('pattern', [pattern1, pattern2])
+def test_issue118(doc, pattern):
+    ORG = doc.vocab.strings['ORG']
+    matcher = Matcher(doc.vocab, {'BostonCeltics': ('ORG', {}, pattern)})
+
+    assert len(list(doc.ents)) == 0
+    matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
+    assert matches == [(ORG, 9, 11), (ORG, 10, 11)]
+    doc.ents = matches[:1]
+    ents = list(doc.ents)
+    assert len(ents) == 1
+    assert ents[0].label == ORG
+    assert ents[0].start == 9
+    assert ents[0].end == 11
+
+
+@pytest.mark.parametrize('pattern', [pattern3, pattern4])
+def test_issue118_prefix_reorder(doc, pattern):
+    ORG = doc.vocab.strings['ORG']
+    matcher = Matcher(doc.vocab, {'BostonCeltics': ('ORG', {}, pattern)})
+
+    assert len(list(doc.ents)) == 0
+    matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
+    doc.ents += tuple(matches)[1:]
+    assert matches == [(ORG, 9, 10), (ORG, 9, 11)]
+    ents = doc.ents
+    assert len(ents) == 1
+    assert ents[0].label == ORG
+    assert ents[0].start == 9
+    assert ents[0].end == 11
diff --git a/spacy/tests/regression/test_issue242.py b/spacy/tests/regression/test_issue242.py
new file mode 100644
index 000000000..752620209
--- /dev/null
+++ b/spacy/tests/regression/test_issue242.py
@@ -0,0 +1,27 @@
+# coding: utf-8
+from __future__ import unicode_literals
+
+from ...matcher import Matcher
+from ...attrs import LOWER
+
+import pytest
+
+
+def test_issue242(en_tokenizer):
+    """Test overlapping multi-word phrases."""
+
+    text = "There are different food safety standards in different countries."
+    patterns = [[{LOWER: 'food'}, {LOWER: 'safety'}],
+                [{LOWER: 'safety'}, {LOWER: 'standards'}]]
+
+    doc = en_tokenizer(text)
+    matcher = Matcher(doc.vocab)
+    matcher.add('FOOD', 'FOOD', {}, patterns)
+
+    matches = [(ent_type, start, end) for ent_id, ent_type, start, end in matcher(doc)]
+    doc.ents += tuple(matches)
+    match1, match2 = matches
+    assert match1[1] == 3
+    assert match1[2] == 5
+    assert match2[1] == 4
+    assert match2[2] == 6