if !reflect.DeepEqual(lc.Keys(), []string{"key1"}) {
		t.Fatalf("value differs from expected")
	}

	if lc.Resize(0) != 0 {
		t.Fatalf("evicted count differs from expected")
	}
	if lc.Resize(2) != 0 {
		t.Fatalf("evicted count differs from expected")
	}
	lc.Add("key2", "val2")
	if lc.Resize(1) != 1 {
		t.Fatalf("evicted count differs from expected")
	}
}

func TestLRUEdgeCases(t *testing.T) {

        Optional<Long> size = byteSource.sizeIfKnown();
        // if we know the size and it fits in an int
        if (size.isPresent() && size.get().longValue() == size.get().intValue()) {
          // otherwise try to presize a StringBuilder
          // it is kind of lame that we need to construct a decoder to access this value.
          // if this is a concern we could add special cases for some known charsets (like utf8)

 * good job of distributing the elements to the buckets to a distribution not far from uniform), and
 * amortized since some operations can trigger a hash table resize.
 *
 * <p>Unlike {@code java.util.HashSet}, iteration is only proportional to the actual {@code size()},
 * which is optimal, and <i>not</i> the size of the internal hashtable, which could be much larger

        final String testCommand = "convert ${url} -resize 100x100 ${outputFile}";
        final String tempPath = "/tmp/source.pdf";
        final String outputPath = "/tmp/thumbnail.jpg";

        final String expandedCommand = testCommand.replace("${url}", tempPath).replace("${outputFile}", outputPath);

        assertEquals("convert /tmp/source.pdf -resize 100x100 /tmp/thumbnail.jpg", expandedCommand);

}

// Len returns the number of items in the cache.
func (c *LRU[K, V]) Len() int {
	c.mu.Lock()
	defer c.mu.Unlock()
	return c.evictList.Length()
}

// Resize changes the cache size. Size of 0 means unlimited.
func (c *LRU[K, V]) Resize(size int) (evicted int) {
	c.mu.Lock()
	defer c.mu.Unlock()
	if size <= 0 {
		c.size = 0
		return 0
	}
	diff := c.evictList.Length() - size
	if diff < 0 {

 * function doing a good job of distributing the elements to the buckets to a distribution not far
 * from uniform), and amortized since some operations can trigger a hash table resize.
 *
 * <p>Unlike {@code java.util.HashMap}, iteration is only proportional to the actual {@code size()},
 * which is optimal, and <i>not</i> the size of the internal hashtable, which could be much larger

 * good job of distributing the elements to the buckets to a distribution not far from uniform), and
 * amortized since some operations can trigger a hash table resize.
 *
 * <p>This implementation consumes significantly less memory than {@code java.util.LinkedHashSet} or
 * even {@code java.util.HashSet}, and places considerably less load on the garbage collector. Like

 * function doing a good job of distributing the elements to the buckets to a distribution not far
 * from uniform), and amortized since some operations can trigger a hash table resize.
 *
 * <p>Unlike {@code java.util.HashMap}, iteration is only proportional to the actual {@code size()},
 * which is optimal, and <i>not</i> the size of the internal hashtable, which could be much larger

      // Always presize to at least 1, since we only bother creating a value collection if there's
      // at least one element.
      this.expectedValuesPerKey = max(expectedValuesPerKey, 1);

      return this;
    }

    /**
     * By default, if we are handed a value collection bigger than expectedValuesPerKey, presize to
     * accept that many elements.
     *

- The pod `status.resize` field is now deprecated and will no longer be set. The status of a pod resize will be exposed under two new conditions: `PodResizeInProgress` and `PodResizePending` instead. ([#130733](https://github.com/kubernetes/kubernetes/pull/130733), [@natasha41575](https://github.com/natasha41575))...