src/java.base/share/classes/java/util/stream/package-info.java

*** 413,423 ****
   * over a mutative accumulation such as the above.  Not only is a reduction
   * "more abstract" -- it operates on the stream as a whole rather than individual
   * elements -- but a properly constructed reduce operation is inherently
   * parallelizable, so long as the function(s) used to process the elements
   * are <a href="package-summary.html#Associativity">associative</a> and
!  * <a href="package-summary.html#NonInterfering">stateless</a>.
   * For example, given a stream of numbers for which we want to find the sum, we
   * can write:
   * <pre>{@code
   *    int sum = numbers.stream().reduce(0, (x,y) -> x+y);
   * }</pre>
--- 413,423 ----
   * over a mutative accumulation such as the above.  Not only is a reduction
   * "more abstract" -- it operates on the stream as a whole rather than individual
   * elements -- but a properly constructed reduce operation is inherently
   * parallelizable, so long as the function(s) used to process the elements
   * are <a href="package-summary.html#Associativity">associative</a> and
!  * <a href="package-summary.html#Statelessness">stateless</a>.
   * For example, given a stream of numbers for which we want to find the sum, we
   * can write:
   * <pre>{@code
   *    int sum = numbers.stream().reduce(0, (x,y) -> x+y);
   * }</pre>