diff --git a/tests/test_adl1.py b/tests/test_adl1.py
deleted file mode 100644
index f305b66..0000000
--- a/tests/test_adl1.py
+++ /dev/null
@@ -1,38 +0,0 @@
-import time
-
-import awkward as ak
-import hist
-import matplotlib.pyplot as plt
-import numpy as np
-from coffea.nanoevents import NanoEventsFactory, NanoAODSchema
-from coffea import processor
-
-import dask
-import dask_awkward as dak
-import hist.dask as hda
-
-from distributed import Client
-client=Client()
-
-# The opendata files are non-standard NanoAOD, so some optional data columns are missing
-NanoAODSchema.warn_missing_crossrefs = False
-
-# The warning emitted below indicates steps_per_file is for initial data exploration
-# and test. When running at scale there are better ways to specify processing chunks
-# of files.
-events = NanoEventsFactory.from_root(
-    "root://eospublic.cern.ch//eos/root-eos/Run2012B_SingleMu.root:Events",
-    steps_per_file=500,
-    metadata={"dataset": "SingleMu"}
-    ).events()
-
-
-@pytest.mark.coffeacalver
-def test_adl1():
-    q1_hist = (
-        hda.Hist.new.Reg(100, 0, 200, name="met", label="$E_{T}^{miss}$ [GeV]")
-        .Double()
-        .fill(events.MET.pt)
-    )
-    q1_hist.compute().plot1d(flow="none")
-    dak.necessary_columns(q1_hist)
diff --git a/tests/test_dimuon.py b/tests/test_dimuon.py
index 97b7552..df95fcf 100644
--- a/tests/test_dimuon.py
+++ b/tests/test_dimuon.py
@@ -6,6 +6,7 @@
 from coffea.nanoevents import NanoEventsFactory, BaseSchema
 
 from dask.distributed import Client
+import pytest
 
 fileset = {
     'DoubleMuon': [
@@ -61,7 +62,7 @@ def process(self, events):
     def postprocess(self, accumulator):
         pass
 
-@pytest.mark.coffeav0
+@pytest.mark.v0
 def test_processor_dimu_mass():
     client = Client()
     iterative_run = processor.Runner(executor = processor.dask_executor,
diff --git a/tests/test_doublemuon.py b/tests/test_doublemuon.py
new file mode 100644
index 0000000..dc60409
--- /dev/null
+++ b/tests/test_doublemuon.py
@@ -0,0 +1,76 @@
+import hist
+import dask
+import awkward as ak
+import hist.dask as hda
+import dask_awkward as dak
+
+from coffea import processor
+from coffea.nanoevents.methods import candidate
+from coffea.nanoevents import NanoEventsFactory, BaseSchema
+
+from distributed import Client
+
+import pytest
+
+client = Client()
+
+
+class MyProcessor(processor.ProcessorABC):
+    def __init__(self):
+        pass
+
+    def process(self, events):
+        dataset = events.metadata['dataset']
+        muons = ak.zip(
+            {
+                "pt": events.Muon_pt,
+                "eta": events.Muon_eta,
+                "phi": events.Muon_phi,
+                "mass": events.Muon_mass,
+                "charge": events.Muon_charge,
+            },
+            with_name="PtEtaPhiMCandidate",
+            behavior=candidate.behavior,
+        )
+
+        h_mass = (
+            hda.Hist.new
+            .StrCat(["opposite", "same"], name="sign")
+            .Log(1000, 0.2, 200., name="mass", label="$m_{\mu\mu}$ [GeV]")
+            .Int64()
+        )
+
+        cut = (ak.num(muons) == 2) & (ak.sum(muons.charge, axis=1) == 0)
+        # add first and second muon in every event together
+        dimuon = muons[cut][:, 0] + muons[cut][:, 1]
+        h_mass.fill(sign="opposite", mass=dimuon.mass)
+
+        cut = (ak.num(muons) == 2) & (ak.sum(muons.charge, axis=1) != 0)
+        dimuon = muons[cut][:, 0] + muons[cut][:, 1]
+        h_mass.fill(sign="same", mass=dimuon.mass)
+
+        return {
+            dataset: {
+                "entries": ak.num(events, axis=0),
+                "mass": h_mass,
+            }
+        }
+
+    def postprocess(self, accumulator):
+        pass
+
+filename = "root://eospublic.cern.ch//eos/root-eos/cms_opendata_2012_nanoaod/Run2012B_DoubleMuParked.root"
+
+events = NanoEventsFactory.from_root(
+    {filename: "Events"},
+    metadata={"dataset": "DoubleMuon"},
+    schemaclass=BaseSchema,
+).events()
+
+
+@pytest.mark.calver
+def test_adl1():
+    p = MyProcessor()
+    out = p.process(events)
+    (computed,) = dask.compute(out)
+    print(computed)