copyright notice that is included in or attached to the work
      (an example is provided in the Appendix below).

      "Derivative Works" shall mean any work, whether in Source or Object
      form, that is based on (or derived from) the Work and for which the
      editorial revisions, annotations, elaborations, or other modifications
      represent, as a whole, an original work of authorship. For the purposes

      copyright notice that is included in or attached to the work
      (an example is provided in the Appendix below).

      "Derivative Works" shall mean any work, whether in Source or Object
      form, that is based on (or derived from) the Work and for which the
      editorial revisions, annotations, elaborations, or other modifications
      represent, as a whole, an original work of authorship. For the purposes

      copyright notice that is included in or attached to the work
      (an example is provided in the Appendix below).

      "Derivative Works" shall mean any work, whether in Source or Object
      form, that is based on (or derived from) the Work and for which the
      editorial revisions, annotations, elaborations, or other modifications
      represent, as a whole, an original work of authorship. For the purposes

      copyright notice that is included in or attached to the work
      (an example is provided in the Appendix below).

      "Derivative Works" shall mean any work, whether in Source or Object
      form, that is based on (or derived from) the Work and for which the
      editorial revisions, annotations, elaborations, or other modifications
      represent, as a whole, an original work of authorship. For the purposes

            return metadata;
          }
        }
      }
      break;

    case tensorflow::AttrValue::kPlaceholder:
      metadata.is_list = 0;
      metadata.list_size = -1;
      metadata.type = TF_ATTR_PLACEHOLDER;
      metadata.total_size = -1;
      break;

    case tensorflow::AttrValue::kFunc:
      metadata.is_list = 0;
      metadata.list_size = -1;

                // this intentionally sticks to the old name
                assertEquals("/share/foo/bar/", fl2.getURLPath());
            }
        }
    }


    // test case for #30
    @Test ( expected = MalformedURLException.class )
    public void testInvalid () throws MalformedURLException, CIFSException {
        try ( SmbResource p = new SmbFile("smb:a", getContext()) ) {

	}

	return match, facts
}

func renderStringMatch(sm *v1alpha3.StringMatch) string {
	if sm == nil {
		return ""
	}

	switch x := sm.MatchType.(type) {
	case *v1alpha3.StringMatch_Exact:
		return x.Exact
	case *v1alpha3.StringMatch_Prefix:
		return x.Prefix + "*"
	}

	return sm.String()
}

func renderMatches(trafficMatches []*v1alpha3.HTTPMatchRequest) string {

        val tlsEquipPlan = planWithCurrentOrInitialConnectionSpec(connectionSpecs, sslSocket)
        val connectionSpec = connectionSpecs[tlsEquipPlan.connectionSpecIndex]

        // Figure out the next connection spec in case we need a retry.
        retryTlsConnection = tlsEquipPlan.nextConnectionSpec(connectionSpecs, sslSocket)

        connectionSpec.apply(sslSocket, isFallback = tlsEquipPlan.isTlsFallback)

///

## Password hashing

"Hashing" means converting some content (a password in this case) into a sequence of bytes (just a string) that looks like gibberish.

Whenever you pass exactly the same content (exactly the same password) you get exactly the same gibberish.

  TF_DeleteTensor(t);

  for (int i = 0; i < expected_values.size(); i++) {
    EXPECT_EQ(expected_values[i], actual_values[i])
        << "Mismatch in expected values at (zero-based) index " << i;
  }
}

void CheckRemoteMatMulExecutesOK(TFE_Context* ctx,
                                 const char* remote_device_name,
                                 const char* local_device_name) {