DataStoreCrawlingException exception = new DataStoreCrawlingException(url, message, cause, abort);

        // Call aborted() multiple times
        assertTrue(exception.aborted());
        assertTrue(exception.aborted());
        assertTrue(exception.aborted());
    }

    @Test
    public void test_getUrl_multipleCallsReturnSameValue() {

        then:
        1 * delegate.completed("testId1", testCompleteEvent1)
        1 * delegate.completed("rootId", rootCompleteEvent)
    }

    def "events for aborted tests are ignored"() {
        given:
        def delegate = Mock(TestResultProcessor)
        def processor = new RerunTestResultProcessor(delegate);
        def rootDescriptor = descriptor("rootId")

	}

	uploadContent := "The specified multipart upload does not exist. The upload ID might be invalid, or the multipart upload might have been aborted or completed."
	var opts ObjectOptions
	// check before paging occurs.
	for i := range 5 {
		key := "obj" + strconv.Itoa(i)

      }
    }

    /**
     * Returns a new unbuffered output stream to write the value at [index]. If the underlying
     * output stream encounters errors when writing to the filesystem, this edit will be aborted
     * when [commit] is called. The returned output stream does not throw IOExceptions.
     */
    fun newSink(index: Int): Sink {
      synchronized(this@DiskLruCache) {
        check(!done)

// This operation lists in-progress multipart uploads. An in-progress
// multipart upload is a multipart upload that has been initiated,
// using the Initiate Multipart Upload request, but has not yet been
// completed or aborted. This operation returns at most 1,000 multipart
// uploads in the response.
func (api objectAPIHandlers) ListMultipartUploadsHandler(w http.ResponseWriter, r *http.Request) {
	ctx := newContext(r, w, "ListMultipartUploads")

- If the user specifies an invalid timeout in the request URL, the request will be aborted with an HTTP 400.

  EXPECT_EQ(TF_FAILED_PRECONDITION,
            static_cast<TF_Code>(tensorflow::error::FAILED_PRECONDITION));
  EXPECT_EQ(TF_ABORTED, static_cast<TF_Code>(tensorflow::error::ABORTED));
  EXPECT_EQ(TF_OUT_OF_RANGE,
            static_cast<TF_Code>(tensorflow::error::OUT_OF_RANGE));
  EXPECT_EQ(TF_UNIMPLEMENTED,
            static_cast<TF_Code>(tensorflow::error::UNIMPLEMENTED));

  restrictions that already apply to CustomResourceDefinition.
  If rule evaluation uses more compute than the limit, the API server aborts the evaluation and the
  admission check that was being performed is aborted; the `failurePolicy` for the ValidatingAdmissionPolicy
  determines the outcome. ([#115747](https://github.com/kubernetes/kubernetes/pull/115747), [@cici37](https://github.com/cici37))

- If the user specifies an invalid timeout in the request URL, the request will be aborted with an HTTP 400.

- DRA: When the prioritized list feature was used in a request and the resulting number of allocated devices exceeded the number of allowed devices per claim, the scheduler aborted the attempt to allocate devices early. Previously, it tried to many different combinations, which could take a long time. ([#130593](https://github.com/kubernetes/kubernetes/pull/130593), [@mortent](https://github.com/mortent)) [SIG Apps, Node, Scheduling...