diff --git a/dace/transformation/interstate/sdfg_nesting.py b/dace/transformation/interstate/sdfg_nesting.py
index a25d819a2d..1d4a7eb2e5 100644
--- a/dace/transformation/interstate/sdfg_nesting.py
+++ b/dace/transformation/interstate/sdfg_nesting.py
@@ -956,22 +956,6 @@ def _candidates(
                         continue
                     in_candidates[e.data.data] = (e.data, nstate, set(range(len(e.data.subset))))
 
-        # Check interstate edges for candidates
-        for e in nsdfg.sdfg.edges():
-            for m in e.data.get_read_memlets(nsdfg.sdfg.arrays):
-                # If more than one unique element detected, remove from candidates
-                if m.data in in_candidates:
-                    memlet, ns, indices = in_candidates[m.data]
-                    # Try to find dimensions in which there is a mismatch and remove them from list
-                    for i, (s1, s2) in enumerate(zip(m.subset, memlet.subset)):
-                        if s1 != s2 and i in indices:
-                            indices.remove(i)
-                    if len(indices) == 0:
-                        ignore.add(m.data)
-                    in_candidates[m.data] = (memlet, ns, indices)
-                    continue
-                in_candidates[m.data] = (m, None, set(range(len(m.subset))))
-
         # Check in/out candidates
         for cand in in_candidates.keys() & out_candidates.keys():
             s1, nstate1, ind1 = in_candidates[cand]
@@ -1000,7 +984,7 @@ def _check_cand(candidates, outer_edges):
                     continue
 
                 # Check w.r.t. loops
-                if nstate is not None and len(nstate.ranges) > 0:
+                if len(nstate.ranges) > 0:
                     # Re-annotate loop ranges, in case someone changed them
                     # TODO: Move out of here!
                     for ns in nsdfg.sdfg.states():
diff --git a/tests/transformations/refine_nested_access_test.py b/tests/transformations/refine_nested_access_test.py
deleted file mode 100644
index 30d2a3e77e..0000000000
--- a/tests/transformations/refine_nested_access_test.py
+++ /dev/null
@@ -1,101 +0,0 @@
-# Copyright 2019-2023 ETH Zurich and the DaCe authors. All rights reserved.
-""" Tests for the RefineNestedAccess transformation. """
-
-import dace
-import numpy as np
-
-from dace.transformation.interstate import RefineNestedAccess
-
-
-def test_refine_dataflow():
-
-    i = dace.symbol('i')
-    j = dace.symbol('j')
-
-    @dace.program
-    def inner_sdfg(A: dace.int32[5, 5], B: dace.int32[5, 5]):
-        B[i, j] = A[j, i]
-
-    sdfg = dace.SDFG('refine_dataflow')
-    sdfg.add_array('A', [5, 5], dace.int32)
-    sdfg.add_array('B', [5, 5], dace.int32)
-
-    state = sdfg.add_state()
-    A = state.add_access('A')
-    B = state.add_access('B')
-    me, mx = state.add_map('m', dict(i='0:5', j='0:5'))
-    nsdfg = state.add_nested_sdfg(inner_sdfg.to_sdfg(), sdfg, {'A'}, {'B'}, {'i': 'i', 'j': 'j'})
-    state.add_memlet_path(A, me, nsdfg, dst_conn='A', memlet=dace.Memlet.from_array('A', sdfg.arrays['A']))
-    state.add_memlet_path(nsdfg, mx, B, src_conn='B', memlet=dace.Memlet.from_array('B', sdfg.arrays['B']))
-
-    num = sdfg.apply_transformations_repeated(RefineNestedAccess)
-    assert num == 1
-
-    for edge in state.out_edges(me):
-        assert edge.data.subset == dace.subsets.Range([(j, j, 1), (i, i, 1)])
-    for edge in state.in_edges(mx):
-        assert edge.data.subset == dace.subsets.Range([(i, i, 1), (j, j, 1)])
-
-    A = np.arange(25, dtype=np.int32).reshape(5, 5).copy()
-    B = np.empty((5, 5), dtype=np.int32)
-    sdfg(A=A, B=B)
-    assert np.allclose(B, A.T)
-
-
-def test_refine_interstate():
-
-    i = dace.symbol('i')
-    j = dace.symbol('j')
-
-    @dace.program
-    def inner_sdfg(A: dace.int32[5, 5], B: dace.int32[5, 5], select: dace.bool[5, 5]):
-        if select[i, j]:
-            B[i, j] = A[j, i]
-        else:
-            B[i, j] = A[i, j]
-
-    sdfg = dace.SDFG('refine_dataflow')
-    sdfg.add_array('A', [5, 5], dace.int32)
-    sdfg.add_array('B', [5, 5], dace.int32)
-    sdfg.add_array('select', [5, 5], dace.bool)
-
-    state = sdfg.add_state()
-    A = state.add_access('A')
-    B = state.add_access('B')
-    select = state.add_access('select')
-    me, mx = state.add_map('m', dict(i='0:5', j='0:5'))
-    nsdfg = state.add_nested_sdfg(inner_sdfg.to_sdfg(), sdfg, {'A', 'select'}, {'B'}, {'i': 'i', 'j': 'j'})
-    state.add_memlet_path(A, me, nsdfg, dst_conn='A', memlet=dace.Memlet.from_array('A', sdfg.arrays['A']))
-    state.add_memlet_path(select,
-                          me,
-                          nsdfg,
-                          dst_conn='select',
-                          memlet=dace.Memlet.from_array('select', sdfg.arrays['select']))
-    state.add_memlet_path(nsdfg, mx, B, src_conn='B', memlet=dace.Memlet.from_array('B', sdfg.arrays['B']))
-
-    num = sdfg.apply_transformations_repeated(RefineNestedAccess)
-    assert num == 1
-
-    for edge in state.out_edges(me):
-        if edge.data.data == 'A':
-            expr = dace.symbolic.pystr_to_symbolic('Max(i, j)')
-            assert edge.data.subset == dace.subsets.Range([(0, expr, 1), (0, expr, 1)])
-        else:
-            assert edge.data.subset == dace.subsets.Range([(i, i, 1), (j, j, 1)])
-    for edge in state.in_edges(mx):
-        assert edge.data.subset == dace.subsets.Range([(i, i, 1), (j, j, 1)])
-
-    A = np.arange(25, dtype=np.int32).reshape(5, 5).copy()
-    B = np.empty((5, 5), dtype=np.int32)
-    select = np.empty((5, 5), dtype=np.bool_)
-    select[:] = True
-    upper = np.triu(select, k=0)
-    sdfg(A=A, B=B, select=upper)
-    lower = np.tril(A, k=0)
-    diag = np.diag(np.diag(A))
-    assert np.allclose(B, lower.T + lower - diag)
-
-
-if __name__ == '__main__':
-    test_refine_dataflow()
-    test_refine_interstate()