diff --git a/pytential/qbx/direct.py b/pytential/qbx/direct.py
index 496259c921f7e6a6fdba59ceb42eda48a805bcd1..eac3c7fc8d667ef6b48a7f3509ade5b2f21878e2 100644
--- a/pytential/qbx/direct.py
+++ b/pytential/qbx/direct.py
@@ -25,8 +25,8 @@ THE SOFTWARE.
 import loopy as lp
 import numpy as np
 
+from loopy.version import MOST_RECENT_LANGUAGE_VERSION
 from sumpy.qbx import LayerPotentialBase
-
 from pytential.version import PYTENTIAL_KERNEL_VERSION
 
 
@@ -98,7 +98,8 @@ class LayerPotentialOnTargetAndCenterSubset(LayerPotentialBase):
             arguments,
             name=self.name,
             assumptions="ntargets>=1 and nsources>=1",
-            fixed_parameters=dict(dim=self.dim))
+            fixed_parameters=dict(dim=self.dim),
+            lang_version=MOST_RECENT_LANGUAGE_VERSION)
 
         loopy_knl = lp.tag_inames(loopy_knl, "idim*:unr")
         for expn in self.expansions:
diff --git a/pytential/unregularized.py b/pytential/unregularized.py
index fc39217e21293d8cc94b2a089ee0c9847dad1cf9..4e8e3098e79e7211c2727be5472e2ed9c0d5bc7f 100644
--- a/pytential/unregularized.py
+++ b/pytential/unregularized.py
@@ -255,9 +255,8 @@ class UnregularizedLayerPotentialSource(LayerPotentialSourceBase):
         # }}}
 
         from boxtree.fmm import drive_fmm
-        timing_data = {}
         all_potentials_on_every_tgt = drive_fmm(
-                geo_data.traversal(), wrangler, strengths, timing_data)
+                geo_data.traversal(), wrangler, strengths, timing_data=None)
 
         # {{{ postprocess fmm
 
@@ -274,6 +273,7 @@ class UnregularizedLayerPotentialSource(LayerPotentialSourceBase):
 
         # }}}
 
+        timing_data = {}
         return result, timing_data
 
     # }}}
diff --git a/test/test_cost_model.py b/test/test_cost_model.py
index 7b24f56713dcd338cebbdcef7bb9d59c4e5cbcbf..55bf804f95cd8def1972297691e9d92ce0e1d645 100644
--- a/test/test_cost_model.py
+++ b/test/test_cost_model.py
@@ -101,12 +101,12 @@ def get_density(queue, lpot_source):
 
 # {{{ test that timing data gathering can execute succesfully
 
-def test_timing_data_gathering(ctx_getter):
+def test_timing_data_gathering(ctx_factory):
     """Test that timing data gathering can execute succesfully."""
 
     pytest.importorskip("pyfmmlib")
 
-    cl_ctx = ctx_getter()
+    cl_ctx = ctx_factory()
     queue = cl.CommandQueue(cl_ctx,
             properties=cl.command_queue_properties.PROFILING_ENABLE)
 
@@ -133,9 +133,9 @@ def test_timing_data_gathering(ctx_getter):
     (2, False),
     (3, False),
     (3, True)))
-def test_cost_model(ctx_getter, dim, use_target_specific_qbx):
+def test_cost_model(ctx_factory, dim, use_target_specific_qbx):
     """Test that cost model gathering can execute successfully."""
-    cl_ctx = ctx_getter()
+    cl_ctx = ctx_factory()
     queue = cl.CommandQueue(cl_ctx)
 
     lpot_source = (
@@ -156,7 +156,7 @@ def test_cost_model(ctx_getter, dim, use_target_specific_qbx):
 
     sym_op_S_plus_D = (
             sym.S(k_sym, sigma_sym, qbx_forced_limit=+1)
-            + sym.D(k_sym, sigma_sym))
+            + sym.D(k_sym, sigma_sym, qbx_forced_limit="avg"))
     op_S_plus_D = bind(lpot_source, sym_op_S_plus_D)
     cost_S_plus_D = op_S_plus_D.get_modeled_cost(queue, sigma=sigma)
     assert len(cost_S_plus_D) == 2
@@ -166,9 +166,9 @@ def test_cost_model(ctx_getter, dim, use_target_specific_qbx):
 
 # {{{ test cost model metadata gathering
 
-def test_cost_model_metadata_gathering(ctx_getter):
+def test_cost_model_metadata_gathering(ctx_factory):
     """Test that the cost model correctly gathers metadata."""
-    cl_ctx = ctx_getter()
+    cl_ctx = ctx_factory()
     queue = cl.CommandQueue(cl_ctx)
 
     from sumpy.expansion.level_to_order import SimpleExpansionOrderFinder
@@ -425,10 +425,10 @@ class OpCountingTranslationCostModel(object):
         (3, False, True),
         (3, True,  False),
         (3, True,  True)))
-def test_cost_model_correctness(ctx_getter, dim, off_surface,
+def test_cost_model_correctness(ctx_factory, dim, off_surface,
         use_target_specific_qbx):
     """Check that computed cost matches that of a constant-one FMM."""
-    cl_ctx = ctx_getter()
+    cl_ctx = ctx_factory()
     queue = cl.CommandQueue(cl_ctx)
 
     cost_model = (
@@ -516,12 +516,12 @@ CONSTANT_ONE_PARAMS = dict(
         )
 
 
-def test_cost_model_order_varying_by_level(ctx_getter):
+def test_cost_model_order_varying_by_level(ctx_factory):
     """For FMM order varying by level, this checks to ensure that the costs are
     different. The varying-level case should have larger cost.
     """
 
-    cl_ctx = ctx_getter()
+    cl_ctx = ctx_factory()
     queue = cl.CommandQueue(cl_ctx)
 
     # {{{ constant level to order
diff --git a/test/test_target_specific_qbx.py b/test/test_target_specific_qbx.py
index 34091af9a91e26f526ea3f2b371515b0c8992029..258a4d75a716b0b7b8f3068b35861ba941c0d4d3 100644
--- a/test/test_target_specific_qbx.py
+++ b/test/test_target_specific_qbx.py
@@ -133,10 +133,10 @@ def test_spherical_hankel_functions():
 @pytest.mark.parametrize("op", ["S", "D", "Sp"])
 @pytest.mark.parametrize("helmholtz_k", [0, 1.2, 12 + 1.2j])
 @pytest.mark.parametrize("qbx_order", [0, 1, 5])
-def test_target_specific_qbx(ctx_getter, op, helmholtz_k, qbx_order):
+def test_target_specific_qbx(ctx_factory, op, helmholtz_k, qbx_order):
     logging.basicConfig(level=logging.INFO)
 
-    cl_ctx = ctx_getter()
+    cl_ctx = ctx_factory()
     queue = cl.CommandQueue(cl_ctx)
 
     target_order = 4