8015318: Extend Collector with 'finish' operation

Reviewed-by: mduigou
Contributed-by: brian.goetz@oracle.com

src/share/classes/java/util/DoubleSummaryStatistics.java

@@ -25,6 +25,7 @@
 package java.util;
 
 import java.util.function.DoubleConsumer;
+import java.util.stream.Collector;
 
 /**
  * A state object for collecting statistics such as count, min, max, sum, and
@@ -35,24 +36,24 @@ import java.util.function.DoubleConsumer;
  * summary statistics on a stream of doubles with:
  * <pre> {@code
  * DoubleSummaryStatistics stats = doubleStream.collect(DoubleSummaryStatistics::new,
- *     DoubleSummaryStatistics::accept,
- *     DoubleSummaryStatistics::combine);
+ *                                                      DoubleSummaryStatistics::accept,
+ *                                                      DoubleSummaryStatistics::combine);
  * }</pre>
  *
  * <p>{@code DoubleSummaryStatistics} can be used as a
- * {@linkplain java.util.stream.Stream#reduce(java.util.function.BinaryOperator) reduction}
+ * {@linkplain java.util.stream.Stream#collect(Collector) reduction}
  * target for a {@linkplain java.util.stream.Stream stream}. For example:
  *
  * <pre> {@code
  * DoubleSummaryStatistics stats = people.stream()
- *     .collect(Collectors.toDoubleSummaryStatistics(Person::getWeight));
+ *     .collect(Collectors.summarizingDouble(Person::getWeight));
  *}</pre>
  *
  * This computes, in a single pass, the count of people, as well as the minimum,
  * maximum, sum, and average of their weights.
  *
  * @implNote This implementation is not thread safe. However, it is safe to use
- * {@link java.util.stream.Collectors#toDoubleSummaryStatistics(java.util.function.ToDoubleFunction)
+ * {@link java.util.stream.Collectors#summarizingDouble(java.util.function.ToDoubleFunction)
  * Collectors.toDoubleStatistics()} on a parallel stream, because the parallel
  * implementation of {@link java.util.stream.Stream#collect Stream.collect()}
  * provides the necessary partitioning, isolation, and merging of results for
@@ -152,7 +153,7 @@ public class DoubleSummaryStatistics implements DoubleConsumer {
     }
 
     /**
-     * Returns the average of values recorded, or zero if no values have been
+     * Returns the arithmetic mean of values recorded, or zero if no values have been
      * recorded. The average returned can vary depending upon the order in
      * which values are recorded. This is due to accumulated rounding error in
      * addition of values of differing magnitudes. Values sorted by increasing
@@ -160,7 +161,7 @@ public class DoubleSummaryStatistics implements DoubleConsumer {
      * value is a {@code NaN} or the sum is at any point a {@code NaN} then the
      * average will be {@code NaN}.
      *
-     * @return the average of values, or zero if none
+     * @return the arithmetic mean of values, or zero if none
      */
     public final double getAverage() {
         return getCount() > 0 ? getSum() / getCount() : 0.0d;

src/share/classes/java/util/IntSummaryStatistics.java

@@ -25,6 +25,7 @@
 package java.util;
 
 import java.util.function.IntConsumer;
+import java.util.stream.Collector;
 
 /**
  * A state object for collecting statistics such as count, min, max, sum, and
@@ -35,24 +36,24 @@ import java.util.function.IntConsumer;
  * summary statistics on a stream of ints with:
  * <pre> {@code
  * IntSummaryStatistics stats = intStream.collect(IntSummaryStatistics::new,
- *     IntSummaryStatistics::accept,
- *     IntSummaryStatistics::combine);
+ *                                                IntSummaryStatistics::accept,
+ *                                                IntSummaryStatistics::combine);
  * }</pre>
  *
  * <p>{@code IntSummaryStatistics} can be used as a
- * {@linkplain java.util.stream.Stream#reduce(java.util.function.BinaryOperator) reduction}
+ * {@linkplain java.util.stream.Stream#collect(Collector) reduction}
  * target for a {@linkplain java.util.stream.Stream stream}. For example:
  *
  * <pre> {@code
  * IntSummaryStatistics stats = people.stream()
- *     .collect(Collectors.toIntSummaryStatistics(Person::getDependents));
+ *                                    .collect(Collectors.summarizingInt(Person::getDependents));
  *}</pre>
  *
  * This computes, in a single pass, the count of people, as well as the minimum,
  * maximum, sum, and average of their number of dependents.
  *
  * @implNote This implementation is not thread safe. However, it is safe to use
- * {@link java.util.stream.Collectors#toIntSummaryStatistics(java.util.function.ToIntFunction)
+ * {@link java.util.stream.Collectors#summarizingInt(java.util.function.ToIntFunction)
  * Collectors.toIntStatistics()} on a parallel stream, because the parallel
  * implementation of {@link java.util.stream.Stream#collect Stream.collect()}
  * provides the necessary partitioning, isolation, and merging of results for
@@ -140,10 +141,10 @@ public class IntSummaryStatistics implements IntConsumer {
     }
 
     /**
-     * Returns the average of values recorded, or zero if no values have been
+     * Returns the arithmetic mean of values recorded, or zero if no values have been
      * recorded.
      *
-     * @return the average of values, or zero if none
+     * @return the arithmetic mean of values, or zero if none
      */
     public final double getAverage() {
         return getCount() > 0 ? (double) getSum() / getCount() : 0.0d;

src/share/classes/java/util/LongSummaryStatistics.java

@@ -26,6 +26,7 @@ package java.util;
 
 import java.util.function.IntConsumer;
 import java.util.function.LongConsumer;
+import java.util.stream.Collector;
 
 /**
  * A state object for collecting statistics such as count, min, max, sum, and
@@ -36,24 +37,24 @@ import java.util.function.LongConsumer;
  * summary statistics on a stream of longs with:
  * <pre> {@code
  * LongSummaryStatistics stats = longStream.collect(LongSummaryStatistics::new,
- *     LongSummaryStatistics::accept,
- *     LongSummaryStatistics::combine);
+ *                                                  LongSummaryStatistics::accept,
+ *                                                  LongSummaryStatistics::combine);
  * }</pre>
  *
  * <p>{@code LongSummaryStatistics} can be used as a
- * {@linkplain java.util.stream.Stream#reduce(java.util.function.BinaryOperator) reduction}
+ * {@linkplain java.util.stream.Stream#collect(Collector)} reduction}
  * target for a {@linkplain java.util.stream.Stream stream}. For example:
  *
  * <pre> {@code
  * LongSummaryStatistics stats = people.stream()
- *     .collect(Collectors.toLongSummaryStatistics(Person::getAge));
+ *                                     .collect(Collectors.summarizingLong(Person::getAge));
  *}</pre>
  *
  * This computes, in a single pass, the count of people, as well as the minimum,
- * maximum, sum, and average of their ages in milliseconds.
+ * maximum, sum, and average of their ages.
  *
  * @implNote This implementation is not thread safe. However, it is safe to use
- * {@link java.util.stream.Collectors#toLongSummaryStatistics(java.util.function.ToLongFunction)
+ * {@link java.util.stream.Collectors#summarizingLong(java.util.function.ToLongFunction)
  * Collectors.toLongStatistics()} on a parallel stream, because the parallel
  * implementation of {@link java.util.stream.Stream#collect Stream.collect()}
  * provides the necessary partitioning, isolation, and merging of results for
@@ -152,10 +153,10 @@ public class LongSummaryStatistics implements LongConsumer, IntConsumer {
     }
 
     /**
-     * Returns the average of values recorded, or zero if no values have been
+     * Returns the arithmetic mean of values recorded, or zero if no values have been
      * recorded.
      *
-     * @return The average of values, or zero if none
+     * @return The arithmetic mean of values, or zero if none
      */
     public final double getAverage() {
         return getCount() > 0 ? (double) getSum() / getCount() : 0.0d;

src/share/classes/java/util/StringJoiner.java

@@ -49,16 +49,17 @@ package java.util;
  * <p>
  * A {@code StringJoiner} may be employed to create formatted output from a
  * {@link java.util.stream.Stream} using
- * {@link java.util.stream.Collectors#toStringJoiner}. For example:
+ * {@link java.util.stream.Collectors#joining(CharSequence)}. For example:
  *
  * <pre> {@code
  * List<Integer> numbers = Arrays.asList(1, 2, 3, 4);
  * String commaSeparatedNumbers = numbers.stream()
  *     .map(i -> i.toString())
- *     .collect(Collectors.toStringJoiner(", ")).toString();
+ *     .collect(Collectors.joining(", "));
  * }</pre>
  *
- * @see java.util.stream.Collectors#toStringJoiner
+ * @see java.util.stream.Collectors#joining(CharSequence)
+ * @see java.util.stream.Collectors#joining(CharSequence, CharSequence, CharSequence)
  * @since  1.8
 */
 public final class StringJoiner {

src/share/classes/java/util/stream/Collector.java

@@ -25,40 +25,45 @@
 package java.util.stream;
 
 import java.util.Collections;
+import java.util.EnumSet;
 import java.util.Set;
-import java.util.function.BiFunction;
+import java.util.function.BiConsumer;
 import java.util.function.BinaryOperator;
+import java.util.function.Function;
 import java.util.function.Supplier;
 
 /**
  * A <a href="package-summary.html#Reduction">reduction operation</a> that
- * supports folding input elements into a cumulative result.  The result may be
- * a value or may be a mutable result container.  Examples of operations
- * accumulating results into a mutable result container include: accumulating
- * input elements into a {@code Collection}; concatenating strings into a
- * {@code StringBuilder}; computing summary information about elements such as
- * sum, min, max, or average; computing "pivot table" summaries such as "maximum
- * valued transaction by seller", etc.  Reduction operations can be performed
- * either sequentially or in parallel.
+ * folds input elements into a mutable result container, optionally transforming
+ * the accumulated result into a final representation after all input elements
+ * have been processed.
+ *
+ * <p>Examples of mutable reduction operations include:
+ * accumulating elements into a {@code Collection}; concatenating
+ * strings using a {@code StringBuilder}; computing summary information about
+ * elements such as sum, min, max, or average; computing "pivot table" summaries
+ * such as "maximum valued transaction by seller", etc.  Reduction operations
+ * can be performed either sequentially or in parallel.
  *
  * <p>The following are examples of using the predefined {@code Collector}
  * implementations in {@link Collectors} with the {@code Stream} API to perform
  * mutable reduction tasks:
  * <pre>{@code
- *     // Accumulate elements into a List
- *     List<String> list = stream.collect(Collectors.toList());
+ *     // Accumulate names into a List
+ *     List<String> list = people.stream().map(Person::getName).collect(Collectors.toList());
  *
- *     // Accumulate elements into a TreeSet
- *     Set<String> list = stream.collect(Collectors.toCollection(TreeSet::new));
+ *     // Accumulate names into a TreeSet
+ *     Set<String> list = people.stream().map(Person::getName).collect(Collectors.toCollection(TreeSet::new));
  *
  *     // Convert elements to strings and concatenate them, separated by commas
- *     String joined = stream.map(Object::toString)
- *                           .collect(Collectors.toStringJoiner(", "))
- *                           .toString();
+ *     String joined = things.stream()
+ *                           .map(Object::toString)
+ *                           .collect(Collectors.joining(", "));
  *
  *     // Find highest-paid employee
  *     Employee highestPaid = employees.stream()
- *                                     .collect(Collectors.maxBy(Comparators.comparing(Employee::getSalary)));
+ *                                     .collect(Collectors.maxBy(Comparators.comparing(Employee::getSalary)))
+ *                                     .get();
  *
  *     // Group employees by department
  *     Map<Department, List<Employee>> byDept
@@ -66,7 +71,7 @@ import java.util.function.Supplier;
  *                    .collect(Collectors.groupingBy(Employee::getDepartment));
  *
  *     // Find highest-paid employee by department
- *     Map<Department, Employee> highestPaidByDept
+ *     Map<Department, Optional<Employee>> highestPaidByDept
  *         = employees.stream()
  *                    .collect(Collectors.groupingBy(Employee::getDepartment,
  *                                                   Collectors.maxBy(Comparators.comparing(Employee::getSalary))));
@@ -74,43 +79,42 @@ import java.util.function.Supplier;
  *     // Partition students into passing and failing
  *     Map<Boolean, List<Student>> passingFailing =
  *         students.stream()
- *                 .collect(Collectors.partitioningBy(s -> s.getGrade() >= PASS_THRESHOLD);
+ *                 .collect(Collectors.partitioningBy(s -> s.getGrade() >= PASS_THRESHOLD));
  *
  * }</pre>
  *
- * <p>A {@code Collector} is specified by three functions that work together to
- * manage a result or result container.  They are: creation of an initial
- * result, incorporating a new data element into a result, and combining two
- * results into one. The last function -- combining two results into one -- is
- * used during parallel operations, where subsets of the input are accumulated
- * in parallel, and then the subresults merged into a combined result. The
- * result may be a mutable container or a value.  If the result is mutable, the
- * accumulation and combination functions may either mutate their left argument
- * and return that (such as adding elements to a collection), or return a new
- * result, in which case it should not perform any mutation.
- *
- * <p>Collectors also have a set of characteristics, including
- * {@link Characteristics#CONCURRENT} and
- * {@link Characteristics#STRICTLY_MUTATIVE}.  These characteristics provide
+ * <p>A {@code Collector} is specified by four functions that work together to
+ * accumulate entries into a mutable result container, and optionally perform
+ * a final transform on the result.  They are: creation of a new result container,
+ * incorporating a new data element into a result container, combining two
+ * result containers into one, and performing a final transform on the container.
+ * The combiner function is used during parallel operations, where
+ * subsets of the input are accumulated into separate result
+ * containers, and then the subresults merged into a combined result.  The
+ * combiner function may merge one set of subresults into the other and return
+ * that, or it may return a new object to describe the combined results.
+ *
+ * <p>Collectors also have a set of characteristics, such as
+ * {@link Characteristics#CONCURRENT}.  These characteristics provide
  * hints that can be used by a reduction implementation to provide better
  * performance.
  *
  * <p>Libraries that implement reduction based on {@code Collector}, such as
  * {@link Stream#collect(Collector)}, must adhere to the following constraints:
  * <ul>
- *     <li>The first argument passed to the accumulator function, and both
- *     arguments passed to the combiner function, must be the result of a
- *     previous invocation of {@link #resultSupplier()}, {@link #accumulator()},
- *     or {@link #combiner()}.</li>
+ *     <li>The first argument passed to the accumulator function, both
+ *     arguments passed to the combiner function, and the argument passed to the
+ *     finisher function must be the result of a previous invocation of the
+ *     result supplier, accumulator, or combiner functions.</li>
  *     <li>The implementation should not do anything with the result of any of
  *     the result supplier, accumulator, or combiner functions other than to
- *     pass them again to the accumulator or combiner functions, or return them
- *     to the caller of the reduction operation.</li>
- *     <li>If a result is passed to the accumulator or combiner function, and
- *     the same object is not returned from that function, it is never used
- *     again.</li>
- *     <li>Once a result is passed to the combiner function, it is never passed
- *     to the accumulator function again.</li>
+ *     pass them again to the accumulator, combiner, or finisher functions,
+ *     or return them to the caller of the reduction operation.</li>
+ *     <li>If a result is passed to the combiner or finisher
+ *     function, and the same object is not returned from that function, it is
+ *     never used again.</li>
+ *     <li>Once a result is passed to the combiner or finisher function, it
+ *     is never passed to the accumulator function again.</li>
  *     <li>For non-concurrent collectors, any result returned from the result
  *     supplier, accumulator, or combiner functions must be serially
  *     thread-confined.  This enables collection to occur in parallel without
@@ -132,11 +136,10 @@ import java.util.function.Supplier;
  * Performing a reduction operation with a {@code Collector} should produce a
  * result equivalent to:
  * <pre>{@code
- *     BiFunction<R,T,R> accumulator = collector.accumulator();
- *     R result = collector.resultSupplier().get();
+ *     R container = collector.supplier().get();
  *     for (T t : data)
- *         result = accumulator.apply(result, t);
- *     return result;
+ *         collector.accumulator().accept(container, t);
+ *     return collector.finisher().apply(container);
  * }</pre>
  *
  * <p>However, the library is free to partition the input, perform the reduction
@@ -149,7 +152,7 @@ import java.util.function.Supplier;
  * is accumulating elements into a {@code TreeSet}. In this case, the {@code
  * resultSupplier()} function is {@code () -> new Treeset<T>()}, the
  * {@code accumulator} function is
- * {@code (set, element) -> { set.add(element); return set; }}, and the combiner
+ * {@code (set, element) -> set.add(element) }, and the combiner
  * function is {@code (left, right) -> { left.addAll(right); return left; }}.
  * (This behavior is implemented by
  * {@code Collectors.toCollection(TreeSet::new)}).
@@ -159,51 +162,49 @@ import java.util.function.Supplier;
  * @see Stream#collect(Collector)
  * @see Collectors
  *
- * @param <T> the type of input element to the collect operation
- * @param <R> the result type of the collect operation
+ * @param <T> the type of input elements to the reduction operation
+ * @param <A> the mutable accumulation type of the reduction operation (often
+ *           hidden as an implementation detail)
+ * @param <R> the result type of the reduction operation
  * @since 1.8
  */
-public interface Collector<T, R> {
+public interface Collector<T, A, R> {
     /**
-     * A function that creates and returns a new result that represents
-     * "no values".  If the accumulator or combiner functions may mutate their
-     * arguments, this must be a new, empty result container.
+     * A function that creates and returns a new mutable result container.
      *
-     * @return a function which, when invoked, returns a result representing
-     * "no values"
+     * @return a function which returns a new, mutable result container
      */
-    Supplier<R> resultSupplier();
+    Supplier<A> supplier();
 
     /**
-     * A function that folds a new value into a cumulative result.  The result
-     * may be a mutable result container or a value.  The accumulator function
-     * may modify a mutable container and return it, or create a new result and
-     * return that, but if it returns a new result object, it must not modify
-     * any of its arguments.
-     *
-     * <p>If the collector has the {@link Characteristics#STRICTLY_MUTATIVE}
-     * characteristic, then the accumulator function <em>must</em> always return
-     * its first argument, after possibly mutating its state.
+     * A function that folds a new value into a mutable result container.
      *
-     * @return a function which folds a new value into a cumulative result
+     * @return a function which folds a new value into a mutable result container
      */
-    BiFunction<R, T, R> accumulator();
+    BiConsumer<A, T> accumulator();
 
     /**
      * A function that accepts two partial results and merges them.  The
      * combiner function may fold state from one argument into the other and
-     * return that, or may return a new result object, but if it returns
-     * a new result object, it must not modify the state of either of its
-     * arguments.
-     *
-     * <p>If the collector has the {@link Characteristics#STRICTLY_MUTATIVE}
-     * characteristic, then the combiner function <em>must</em> always return
-     * its first argument, after possibly mutating its state.
+     * return that, or may return a new result object.
      *
      * @return a function which combines two partial results into a cumulative
      * result
      */
-    BinaryOperator<R> combiner();
+    BinaryOperator<A> combiner();
+
+    /**
+     * Perform the final transformation from the intermediate accumulation type
+     * {@code A} to the final result representation {@code R}.
+     *
+     * <p>If the characteristic {@code IDENTITY_TRANSFORM} is
+     * set, this function may be presumed to be an identity transform with an
+     * unchecked cast from {@code A} to {@code R}.
+     *
+     * @return a function which transforms the intermediate result to the final
+     * result
+     */
+    Function<A, R> finisher();
 
     /**
      * Returns a {@code Set} of {@code Collector.Characteristics} indicating
@@ -213,6 +214,62 @@ public interface Collector<T, R> {
      */
     Set<Characteristics> characteristics();
 
+    /**
+     * Returns a new {@code Collector} described by the given {@code supplier},
+     * {@code accumulator}, and {@code combiner} functions.  The resulting
+     * {@code Collector} has the {@code Collector.Characteristics.IDENTITY_FINISH}
+     * characteristic.
+     *
+     * @param supplier The supplier function for the new collector
+     * @param accumulator The accumulator function for the new collector
+     * @param combiner The combiner function for the new collector
+     * @param characteristics The collector characteristics for the new
+     *                        collector
+     * @param <T> The type of input elements for the new collector
+     * @param <R> The type of intermediate accumulation result, and final result,
+     *           for the new collector
+     * @return the new {@code Collector}
+     */
+    public static<T, R> Collector<T, R, R> of(Supplier<R> supplier,
+                                              BiConsumer<R, T> accumulator,
+                                              BinaryOperator<R> combiner,
+                                              Characteristics... characteristics) {
+        Set<Characteristics> cs = (characteristics.length == 0)
+                                  ? Collectors.CH_ID
+                                  : Collections.unmodifiableSet(EnumSet.of(Collector.Characteristics.IDENTITY_FINISH,
+                                                                           characteristics));
+        return new Collectors.CollectorImpl<>(supplier, accumulator, combiner, cs);
+    }
+
+    /**
+     * Returns a new {@code Collector} described by the given {@code supplier},
+     * {@code accumulator}, {@code combiner}, and {@code finisher} functions.
+     *
+     * @param supplier The supplier function for the new collector
+     * @param accumulator The accumulator function for the new collector
+     * @param combiner The combiner function for the new collector
+     * @param finisher The finisher function for the new collector
+     * @param characteristics The collector characteristics for the new
+     *                        collector
+     * @param <T> The type of input elements for the new collector
+     * @param <A> The intermediate accumulation type of the new collector
+     * @param <R> The final result type of the new collector
+     * @return the new {@code Collector}
+     */
+    public static<T, A, R> Collector<T, A, R> of(Supplier<A> supplier,
+                                                 BiConsumer<A, T> accumulator,
+                                                 BinaryOperator<A> combiner,
+                                                 Function<A, R> finisher,
+                                                 Characteristics... characteristics) {
+        Set<Characteristics> cs = Collectors.CH_NOID;
+        if (characteristics.length > 0) {
+            cs = EnumSet.noneOf(Characteristics.class);
+            Collections.addAll(cs, characteristics);
+            cs = Collections.unmodifiableSet(cs);
+        }
+        return new Collectors.CollectorImpl<>(supplier, accumulator, combiner, finisher, cs);
+    }
+
     /**
      * Characteristics indicating properties of a {@code Collector}, which can
      * be used to optimize reduction implementations.
@@ -222,8 +279,7 @@ public interface Collector<T, R> {
          * Indicates that this collector is <em>concurrent</em>, meaning that
          * the result container can support the accumulator function being
          * called concurrently with the same result container from multiple
-         * threads. Concurrent collectors must also always have the
-         * {@code STRICTLY_MUTATIVE} characteristic.
+         * threads.
          *
          * <p>If a {@code CONCURRENT} collector is not also {@code UNORDERED},
          * then it should only be evaluated concurrently if applied to an
@@ -238,12 +294,10 @@ public interface Collector<T, R> {
         UNORDERED,
 
         /**
-         * Indicates that this collector operates by strict mutation of its
-         * result container. This means that the {@link #accumulator()} and
-         * {@link #combiner()} functions will always modify the state of and
-         * return their first argument, rather than returning a different result
-         * container.
+         * Indicates that the finisher function is the identity function and
+         * can be elided.  If set, it must be the case that an unchecked cast
+         * from A to R will succeed.
          */
-        STRICTLY_MUTATIVE
+        IDENTITY_FINISH
     }
 }

src/share/classes/java/util/stream/DelegatingStream.java

@@ -209,7 +209,7 @@ public class DelegatingStream<T> implements Stream<T> {
     }
 
     @Override
-    public <R> R collect(Collector<? super T, R> collector) {
+    public <R, A> R collect(Collector<? super T, A, ? extends R> collector) {
         return delegate.collect(collector);
     }
 

src/share/classes/java/util/stream/DoubleStream.java

@@ -527,7 +527,7 @@ public interface DoubleStream extends BaseStream<Double, DoubleStream> {
     long count();
 
     /**
-     * Returns an {@code OptionalDouble} describing the average of elements of
+     * Returns an {@code OptionalDouble} describing the arithmetic mean of elements of
      * this stream, or an empty optional if this stream is empty.  The average
      * returned can vary depending upon the order in which elements are
      * encountered. This is due to accumulated rounding error in addition of

src/share/classes/java/util/stream/IntStream.java

@@ -517,7 +517,7 @@ public interface IntStream extends BaseStream<Integer, IntStream> {
     long count();
 
     /**
-     * Returns an {@code OptionalDouble} describing the average of elements of
+     * Returns an {@code OptionalDouble} describing the arithmetic mean of elements of
      * this stream, or an empty optional if this stream is empty.  This is a
      * special case of a
      * <a href="package-summary.html#MutableReduction">reduction</a>.

src/share/classes/java/util/stream/LongStream.java

@@ -517,7 +517,7 @@ public interface LongStream extends BaseStream<Long, LongStream> {
     long count();
 
     /**
-     * Returns an {@code OptionalDouble} describing the average of elements of
+     * Returns an {@code OptionalDouble} describing the arithmetic mean of elements of
      * this stream, or an empty optional if this stream is empty.  This is a
      * special case of a
      * <a href="package-summary.html#MutableReduction">reduction</a>.

src/share/classes/java/util/stream/ReduceOps.java

@@ -148,17 +148,17 @@ final class ReduceOps {
      * reference values.
      *
      * @param <T> the type of the input elements
-     * @param <R> the type of the result
+     * @param <I> the type of the intermediate reduction result
      * @param collector a {@code Collector} defining the reduction
      * @return a {@code ReduceOp} implementing the reduction
      */
-    public static <T,R> TerminalOp<T, R>
-    makeRef(Collector<? super T,R> collector) {
-        Supplier<R> supplier = Objects.requireNonNull(collector).resultSupplier();
-        BiFunction<R, ? super T, R> accumulator = collector.accumulator();
-        BinaryOperator<R> combiner = collector.combiner();
-        class ReducingSink extends Box<R>
-                implements AccumulatingSink<T, R, ReducingSink> {
+    public static <T, I> TerminalOp<T, I>
+    makeRef(Collector<? super T, I, ?> collector) {
+        Supplier<I> supplier = Objects.requireNonNull(collector).supplier();
+        BiConsumer<I, ? super T> accumulator = collector.accumulator();
+        BinaryOperator<I> combiner = collector.combiner();
+        class ReducingSink extends Box<I>
+                implements AccumulatingSink<T, I, ReducingSink> {
             @Override
             public void begin(long size) {
                 state = supplier.get();
@@ -166,9 +166,7 @@ final class ReduceOps {
 
             @Override
             public void accept(T t) {
-                R newResult = accumulator.apply(state, t);
-                if (state != newResult)
-                    state = newResult;
+                accumulator.accept(state, t);
             }
 
             @Override
@@ -176,7 +174,7 @@ final class ReduceOps {
                 state = combiner.apply(state, other.state);
             }
         }
-        return new ReduceOp<T, R, ReducingSink>(StreamShape.REFERENCE) {
+        return new ReduceOp<T, I, ReducingSink>(StreamShape.REFERENCE) {
             @Override
             public ReducingSink makeSink() {
                 return new ReducingSink();

src/share/classes/java/util/stream/ReferencePipeline.java

@@ -490,16 +490,21 @@ abstract class ReferencePipeline<P_IN, P_OUT>
     }
 
     @Override
-    public final <R> R collect(Collector<? super P_OUT, R> collector) {
+    public final <R, A> R collect(Collector<? super P_OUT, A, ? extends R> collector) {
+        A container;
         if (isParallel()
                 && (collector.characteristics().contains(Collector.Characteristics.CONCURRENT))
                 && (!isOrdered() || collector.characteristics().contains(Collector.Characteristics.UNORDERED))) {
-            R container = collector.resultSupplier().get();
-            BiFunction<R, ? super P_OUT, R> accumulator = collector.accumulator();
-            forEach(u -> accumulator.apply(container, u));
-            return container;
+            container = collector.supplier().get();
+            BiConsumer<A, ? super P_OUT> accumulator = collector.accumulator();
+            forEach(u -> accumulator.accept(container, u));
         }
-        return evaluate(ReduceOps.makeRef(collector));
+        else {
+            container = evaluate(ReduceOps.makeRef(collector));
+        }
+        return collector.characteristics().contains(Collector.Characteristics.IDENTITY_FINISH)
+               ? (R) container
+               : collector.finisher().apply(container);
     }
 
     @Override

src/share/classes/java/util/stream/Stream.java

@@ -651,12 +651,13 @@ public interface Stream<T> extends BaseStream<T, Stream<T>> {
      * }</pre>
      *
      * @param <R> the type of the result
+     * @param <A> the intermediate accumulation type of the {@code Collector}
      * @param collector the {@code Collector} describing the reduction
      * @return the result of the reduction
      * @see #collect(Supplier, BiConsumer, BiConsumer)
      * @see Collectors
      */
-    <R> R collect(Collector<? super T, R> collector);
+    <R, A> R collect(Collector<? super T, A, ? extends R> collector);
 
     /**
      * Returns the minimum element of this stream according to the provided

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

@@ -547,7 +547,7 @@
  *     List<String> l = new ArrayList(Arrays.asList("one", "two"));
  *     Stream<String> sl = l.stream();
  *     l.add("three");
- *     String s = sl.collect(toStringJoiner(" ")).toString();
+ *     String s = sl.collect(joining(" "));
  * }</pre>
  * First a list is created consisting of two strings: "one"; and "two". Then a stream is created from that list.
  * Next the list is modified by adding a third string: "three".  Finally the elements of the stream are collected
@@ -557,7 +557,7 @@
  * <pre>{@code
  *     List<String> l = new ArrayList(Arrays.asList("one", "two"));
  *     Stream<String> sl = l.stream();
- *     String s = sl.peek(s -> l.add("BAD LAMBDA")).collect(toStringJoiner(" ")).toString();
+ *     String s = sl.peek(s -> l.add("BAD LAMBDA")).collect(joining(" "));
  * }</pre>
  * then a {@code ConcurrentModificationException} will be thrown since the {@code peek} operation will attempt
  * to add the string "BAD LAMBDA" to the list after the terminal operation has commenced.

test/java/util/stream/test/org/openjdk/tests/java/util/FillableStringTest.java

@@ -40,17 +40,17 @@ public class FillableStringTest {
     }
 
     public void testStringBuilder() {
-        String s = generate().collect(Collectors.toStringBuilder()).toString();
+        String s = generate().collect(Collectors.joining());
         assertEquals(s, "THREEFOURFIVE");
     }
 
     public void testStringBuffer() {
-        String s = generate().collect(Collectors.toStringBuilder()).toString();
+        String s = generate().collect(Collectors.joining());
         assertEquals(s, "THREEFOURFIVE");
     }
 
     public void testStringJoiner() {
-        String s = generate().collect(Collectors.toStringJoiner("-")).toString();
+        String s = generate().collect(Collectors.joining("-"));
         assertEquals(s, "THREE-FOUR-FIVE");
     }
 }

test/java/util/stream/test/org/openjdk/tests/java/util/stream/GroupByOpTest.java

@@ -36,7 +36,6 @@ import java.util.stream.Collectors;
 import java.util.stream.LambdaTestHelpers;
 import java.util.stream.OpTestCase;
 import java.util.stream.Stream;
-import java.util.stream.StreamOpFlagTestHelper;
 import java.util.stream.StreamTestDataProvider;
 import java.util.stream.TestData;
 
@@ -59,13 +58,14 @@ import static java.util.stream.LambdaTestHelpers.pTrue;
 public class GroupByOpTest extends OpTestCase {
 
     public void testBypassCollect() {
-        Collector<Integer, Map<Boolean, List<Integer>>> collector
-                = Collectors.groupingBy(LambdaTestHelpers.forPredicate(pEven, true, false));
+        @SuppressWarnings("unchecked")
+        Collector<Integer, Map<Boolean, List<Integer>>, Map<Boolean, List<Integer>>> collector
+                = (Collector<Integer, Map<Boolean, List<Integer>>, Map<Boolean, List<Integer>>>) Collectors.groupingBy(LambdaTestHelpers.forPredicate(pEven, true, false));
 
-        Map<Boolean, List<Integer>> m = collector.resultSupplier().get();
+        Map<Boolean, List<Integer>> m = collector.supplier().get();
         int[] ints = countTo(10).stream().mapToInt(e -> (int) e).toArray();
         for (int i : ints)
-            m = collector.accumulator().apply(m, i);
+            collector.accumulator().accept(m, i);
 
         assertEquals(2, m.keySet().size());
         for(Collection<Integer> group : m.values()) {
@@ -130,7 +130,7 @@ public class GroupByOpTest extends OpTestCase {
         //     - Total number of values equals size of data
 
         for (MapperData<Integer, ?> md : getMapperData(data)) {
-            Collector<Integer, Map<Object, List<Integer>>> tab = Collectors.groupingBy(md.m);
+            Collector<Integer, ?, Map<Object, List<Integer>>> tab = Collectors.groupingBy(md.m);
             Map<Object, List<Integer>> result =
                     withData(data)
                     .terminal(s -> s, s -> s.collect(tab))

test/java/util/stream/test/org/openjdk/tests/java/util/stream/SummaryStatisticsTest.java

@@ -43,9 +43,9 @@ import static java.util.stream.LambdaTestHelpers.countTo;
 public class SummaryStatisticsTest extends OpTestCase {
     public void testIntStatistics() {
         List<IntSummaryStatistics> instances = new ArrayList<>();
-        instances.add(countTo(1000).stream().collect(Collectors.toIntSummaryStatistics(i -> i)));
+        instances.add(countTo(1000).stream().collect(Collectors.summarizingInt(i -> i)));
         instances.add(countTo(1000).stream().mapToInt(i -> i).summaryStatistics());
-        instances.add(countTo(1000).parallelStream().collect(Collectors.toIntSummaryStatistics(i -> i)));
+        instances.add(countTo(1000).parallelStream().collect(Collectors.summarizingInt(i -> i)));
         instances.add(countTo(1000).parallelStream().mapToInt(i -> i).summaryStatistics());
 
         for (IntSummaryStatistics stats : instances) {
@@ -58,9 +58,9 @@ public class SummaryStatisticsTest extends OpTestCase {
 
     public void testLongStatistics() {
         List<LongSummaryStatistics> instances = new ArrayList<>();
-        instances.add(countTo(1000).stream().collect(Collectors.toLongSummaryStatistics(i -> i)));
+        instances.add(countTo(1000).stream().collect(Collectors.summarizingLong(i -> i)));
         instances.add(countTo(1000).stream().mapToLong(i -> i).summaryStatistics());
-        instances.add(countTo(1000).parallelStream().collect(Collectors.toLongSummaryStatistics(i -> i)));
+        instances.add(countTo(1000).parallelStream().collect(Collectors.summarizingLong(i -> i)));
         instances.add(countTo(1000).parallelStream().mapToLong(i -> i).summaryStatistics());
 
         for (LongSummaryStatistics stats : instances) {
@@ -73,9 +73,9 @@ public class SummaryStatisticsTest extends OpTestCase {
 
     public void testDoubleStatistics() {
         List<DoubleSummaryStatistics> instances = new ArrayList<>();
-        instances.add(countTo(1000).stream().collect(Collectors.toDoubleSummaryStatistics(i -> i)));
+        instances.add(countTo(1000).stream().collect(Collectors.summarizingDouble(i -> i)));
         instances.add(countTo(1000).stream().mapToDouble(i -> i).summaryStatistics());
-        instances.add(countTo(1000).parallelStream().collect(Collectors.toDoubleSummaryStatistics(i -> i)));
+        instances.add(countTo(1000).parallelStream().collect(Collectors.summarizingDouble(i -> i)));
         instances.add(countTo(1000).parallelStream().mapToDouble(i -> i).summaryStatistics());
 
         for (DoubleSummaryStatistics stats : instances) {

test/java/util/stream/test/org/openjdk/tests/java/util/stream/TabulatorsTest.java

@@ -23,13 +23,17 @@
 package org.openjdk.tests.java.util.stream;
 
 import java.util.ArrayList;
+import java.util.Arrays;
 import java.util.Collection;
+import java.util.Comparator;
 import java.util.HashMap;
 import java.util.HashSet;
 import java.util.Iterator;
 import java.util.List;
 import java.util.Map;
 import java.util.Optional;
+import java.util.Set;
+import java.util.StringJoiner;
 import java.util.TreeMap;
 import java.util.concurrent.ConcurrentHashMap;
 import java.util.concurrent.ConcurrentSkipListMap;
@@ -53,7 +57,10 @@ import static java.util.stream.Collectors.groupingByConcurrent;
 import static java.util.stream.Collectors.partitioningBy;
 import static java.util.stream.Collectors.reducing;
 import static java.util.stream.Collectors.toCollection;
+import static java.util.stream.Collectors.toConcurrentMap;
 import static java.util.stream.Collectors.toList;
+import static java.util.stream.Collectors.toMap;
+import static java.util.stream.Collectors.toSet;
 import static java.util.stream.LambdaTestHelpers.assertContents;
 import static java.util.stream.LambdaTestHelpers.assertContentsUnordered;
 import static java.util.stream.LambdaTestHelpers.mDoubler;
@@ -65,16 +72,6 @@ import static java.util.stream.LambdaTestHelpers.mDoubler;
  */
 @SuppressWarnings({"rawtypes", "unchecked"})
 public class TabulatorsTest extends OpTestCase {
-    // There are 8 versions of groupingBy:
-    //   groupingBy: { map supplier, not } x { downstream collector, not } x { concurrent, not }
-    // There are 2 versions of partition: { map supplier, not }
-    // There are 4 versions of toMap
-    //   mappedTo(function, mapSupplier?, mergeFunction?)
-    // Each variety needs at least one test
-    // Plus a variety of multi-level tests (groupBy(..., partition), partition(..., groupBy))
-    // Plus negative tests for mapping to null
-    // Each test should be matched by a nest of asserters (see TabulationAssertion...)
-
 
     private static abstract class TabulationAssertion<T, U> {
         abstract void assertValue(U value,
@@ -101,7 +98,7 @@ public class TabulatorsTest extends OpTestCase {
                          boolean ordered) throws ReflectiveOperationException {
             if (!clazz.isAssignableFrom(map.getClass()))
                 fail(String.format("Class mismatch in GroupedMapAssertion: %s, %s", clazz, map.getClass()));
-            assertContentsUnordered(map.keySet(), source.get().map(classifier).collect(Collectors.toSet()));
+            assertContentsUnordered(map.keySet(), source.get().map(classifier).collect(toSet()));
             for (Map.Entry<K, ? extends V> entry : map.entrySet()) {
                 K key = entry.getKey();
                 downstream.assertValue(entry.getValue(),
@@ -111,6 +108,39 @@ public class TabulatorsTest extends OpTestCase {
         }
     }
 
+    static class ToMapAssertion<T, K, V, M extends Map<K,V>> extends TabulationAssertion<T, M> {
+        private final Class<? extends Map> clazz;
+        private final Function<T, K> keyFn;
+        private final Function<T, V> valueFn;
+        private final BinaryOperator<V> mergeFn;
+
+        ToMapAssertion(Function<T, K> keyFn,
+                       Function<T, V> valueFn,
+                       BinaryOperator<V> mergeFn,
+                       Class<? extends Map> clazz) {
+            this.clazz = clazz;
+            this.keyFn = keyFn;
+            this.valueFn = valueFn;
+            this.mergeFn = mergeFn;
+        }
+
+        @Override
+        void assertValue(M map, Supplier<Stream<T>> source, boolean ordered) throws ReflectiveOperationException {
+            Set<K> uniqueKeys = source.get().map(keyFn).collect(toSet());
+            assertTrue(clazz.isAssignableFrom(map.getClass()));
+            assertEquals(uniqueKeys, map.keySet());
+            source.get().forEach(t -> {
+                K key = keyFn.apply(t);
+                V v = source.get()
+                            .filter(e -> key.equals(keyFn.apply(e)))
+                            .map(valueFn)
+                            .reduce(mergeFn)
+                            .get();
+                assertEquals(map.get(key), v);
+            });
+        }
+    }
+
     static class PartitionAssertion<T, D> extends TabulationAssertion<T, Map<Boolean,D>> {
         private final Predicate<T> predicate;
         private final TabulationAssertion<T,D> downstream;
@@ -204,7 +234,7 @@ public class TabulatorsTest extends OpTestCase {
 
     private <T> ResultAsserter<T> mapTabulationAsserter(boolean ordered) {
         return (act, exp, ord, par) -> {
-            if (par & (!ordered || !ord)) {
+            if (par && (!ordered || !ord)) {
                 TabulatorsTest.nestedMapEqualityAssertion(act, exp);
             }
             else {
@@ -215,7 +245,7 @@ public class TabulatorsTest extends OpTestCase {
 
     private<T, M extends Map>
     void exerciseMapTabulation(TestData<T, Stream<T>> data,
-                               Collector<T, ? extends M> collector,
+                               Collector<T, ?, ? extends M> collector,
                                TabulationAssertion<T, M> assertion)
             throws ReflectiveOperationException {
         boolean ordered = !collector.characteristics().contains(Collector.Characteristics.UNORDERED);
@@ -248,6 +278,172 @@ public class TabulatorsTest extends OpTestCase {
             assertEquals(o1, o2);
     }
 
+    private<T, R> void assertCollect(TestData.OfRef<T> data,
+                                     Collector<T, ?, R> collector,
+                                     Function<Stream<T>, R> streamReduction) {
+        R check = streamReduction.apply(data.stream());
+        withData(data).terminal(s -> s.collect(collector)).expectedResult(check).exercise();
+    }
+
+    @Test(dataProvider = "StreamTestData<Integer>", dataProviderClass = StreamTestDataProvider.class)
+    public void testReduce(String name, TestData.OfRef<Integer> data) throws ReflectiveOperationException {
+        assertCollect(data, Collectors.reducing(0, Integer::sum),
+                      s -> s.reduce(0, Integer::sum));
+        assertCollect(data, Collectors.reducing(Integer.MAX_VALUE, Integer::min),
+                      s -> s.min(Integer::compare).orElse(Integer.MAX_VALUE));
+        assertCollect(data, Collectors.reducing(Integer.MIN_VALUE, Integer::max),
+                      s -> s.max(Integer::compare).orElse(Integer.MIN_VALUE));
+
+        assertCollect(data, Collectors.reducing(Integer::sum),
+                      s -> s.reduce(Integer::sum));
+        assertCollect(data, Collectors.minBy(Comparator.naturalOrder()),
+                      s -> s.min(Integer::compare));
+        assertCollect(data, Collectors.maxBy(Comparator.naturalOrder()),
+                      s -> s.max(Integer::compare));
+
+        assertCollect(data, Collectors.reducing(0, x -> x*2, Integer::sum),
+                      s -> s.map(x -> x*2).reduce(0, Integer::sum));
+
+        assertCollect(data, Collectors.summingLong(x -> x * 2L),
+                      s -> s.map(x -> x*2L).reduce(0L, Long::sum));
+        assertCollect(data, Collectors.summingInt(x -> x * 2),
+                      s -> s.map(x -> x*2).reduce(0, Integer::sum));
+        assertCollect(data, Collectors.summingDouble(x -> x * 2.0d),
+                      s -> s.map(x -> x * 2.0d).reduce(0.0d, Double::sum));
+
+        assertCollect(data, Collectors.averagingInt(x -> x * 2),
+                      s -> s.mapToInt(x -> x * 2).average().orElse(0));
+        assertCollect(data, Collectors.averagingLong(x -> x * 2),
+                      s -> s.mapToLong(x -> x * 2).average().orElse(0));
+        assertCollect(data, Collectors.averagingDouble(x -> x * 2),
+                      s -> s.mapToDouble(x -> x * 2).average().orElse(0));
+
+        // Test explicit Collector.of
+        Collector<Integer, long[], Double> avg2xint = Collector.of(() -> new long[2],
+                                                                   (a, b) -> {
+                                                                       a[0] += b * 2;
+                                                                       a[1]++;
+                                                                   },
+                                                                   (a, b) -> {
+                                                                       a[0] += b[0];
+                                                                       a[1] += b[1];
+                                                                       return a;
+                                                                   },
+                                                                   a -> a[1] == 0 ? 0.0d : (double) a[0] / a[1]);
+        assertCollect(data, avg2xint,
+                      s -> s.mapToInt(x -> x * 2).average().orElse(0));
+    }
+
+    @Test(dataProvider = "StreamTestData<Integer>", dataProviderClass = StreamTestDataProvider.class)
+    public void testJoin(String name, TestData.OfRef<Integer> data) throws ReflectiveOperationException {
+        withData(data)
+                .terminal(s -> s.map(Object::toString).collect(Collectors.joining()))
+                .expectedResult(join(data, ""))
+                .exercise();
+
+        Collector<String, StringBuilder, String> likeJoining = Collector.of(StringBuilder::new, StringBuilder::append, (sb1, sb2) -> sb1.append(sb2.toString()), StringBuilder::toString);
+        withData(data)
+                .terminal(s -> s.map(Object::toString).collect(likeJoining))
+                .expectedResult(join(data, ""))
+                .exercise();
+
+        withData(data)
+                .terminal(s -> s.map(Object::toString).collect(Collectors.joining(",")))
+                .expectedResult(join(data, ","))
+                .exercise();
+
+        withData(data)
+                .terminal(s -> s.map(Object::toString).collect(Collectors.joining(",", "[", "]")))
+                .expectedResult("[" + join(data, ",") + "]")
+                .exercise();
+
+        withData(data)
+                .terminal(s -> s.map(Object::toString)
+                                .collect(StringBuilder::new, StringBuilder::append, StringBuilder::append)
+                                .toString())
+                .expectedResult(join(data, ""))
+                .exercise();
+
+        withData(data)
+                .terminal(s -> s.map(Object::toString)
+                                .collect(() -> new StringJoiner(","),
+                                         (sj, cs) -> sj.add(cs),
+                                         (j1, j2) -> j1.merge(j2))
+                                .toString())
+                .expectedResult(join(data, ","))
+                .exercise();
+
+        withData(data)
+                .terminal(s -> s.map(Object::toString)
+                                .collect(() -> new StringJoiner(",", "[", "]"),
+                                         (sj, cs) -> sj.add(cs),
+                                         (j1, j2) -> j1.merge(j2))
+                                .toString())
+                .expectedResult("[" + join(data, ",") + "]")
+                .exercise();
+    }
+
+    private<T> String join(TestData.OfRef<T> data, String delim) {
+        StringBuilder sb = new StringBuilder();
+        boolean first = true;
+        for (T i : data) {
+            if (!first)
+                sb.append(delim);
+            sb.append(i.toString());
+            first = false;
+        }
+        return sb.toString();
+    }
+
+    @Test(dataProvider = "StreamTestData<Integer>", dataProviderClass = StreamTestDataProvider.class)
+    public void testSimpleToMap(String name, TestData.OfRef<Integer> data) throws ReflectiveOperationException {
+        Function<Integer, Integer> keyFn = i -> i * 2;
+        Function<Integer, Integer> valueFn = i -> i * 4;
+
+        List<Integer> dataAsList = Arrays.asList(data.stream().toArray(Integer[]::new));
+        Set<Integer> dataAsSet = new HashSet<>(dataAsList);
+
+        BinaryOperator<Integer> sum = Integer::sum;
+        for (BinaryOperator<Integer> op : Arrays.asList((u, v) -> u,
+                                                        (u, v) -> v,
+                                                        sum)) {
+            try {
+                exerciseMapTabulation(data, toMap(keyFn, valueFn),
+                                      new ToMapAssertion<>(keyFn, valueFn, op, HashMap.class));
+                if (dataAsList.size() != dataAsSet.size())
+                    fail("Expected ISE on input with duplicates");
+            }
+            catch (IllegalStateException e) {
+                if (dataAsList.size() == dataAsSet.size())
+                    fail("Expected no ISE on input without duplicates");
+            }
+
+            exerciseMapTabulation(data, toMap(keyFn, valueFn, op),
+                                  new ToMapAssertion<>(keyFn, valueFn, op, HashMap.class));
+
+            exerciseMapTabulation(data, toMap(keyFn, valueFn, op, TreeMap::new),
+                                  new ToMapAssertion<>(keyFn, valueFn, op, TreeMap.class));
+        }
+
+        // For concurrent maps, only use commutative merge functions
+        try {
+            exerciseMapTabulation(data, toConcurrentMap(keyFn, valueFn),
+                                  new ToMapAssertion<>(keyFn, valueFn, sum, ConcurrentHashMap.class));
+            if (dataAsList.size() != dataAsSet.size())
+                fail("Expected ISE on input with duplicates");
+        }
+        catch (IllegalStateException e) {
+            if (dataAsList.size() == dataAsSet.size())
+                fail("Expected no ISE on input without duplicates");
+        }
+
+        exerciseMapTabulation(data, toConcurrentMap(keyFn, valueFn, sum),
+                              new ToMapAssertion<>(keyFn, valueFn, sum, ConcurrentHashMap.class));
+
+        exerciseMapTabulation(data, toConcurrentMap(keyFn, valueFn, sum, ConcurrentSkipListMap::new),
+                              new ToMapAssertion<>(keyFn, valueFn, sum, ConcurrentSkipListMap.class));
+    }
+
     @Test(dataProvider = "StreamTestData<Integer>", dataProviderClass = StreamTestDataProvider.class)
     public void testSimpleGroupBy(String name, TestData.OfRef<Integer> data) throws ReflectiveOperationException {
         Function<Integer, Integer> classifier = i -> i % 3;

test/jdk/lambda/MethodReferenceTestInstanceMethod.java

@@ -47,7 +47,7 @@ public class MethodReferenceTestInstanceMethod {
     }
 
     public void testStringBuffer() {
-        String s = generate().collect(Collectors.toStringBuilder()).toString();
+        String s = generate().collect(Collectors.joining());
         assertEquals(s, "THREEFOURFIVE");
     }
 

test/jdk/lambda/separate/TestHarness.java

@@ -119,7 +119,7 @@ public class TestHarness {
         Class stub = new Class(specimen.getName(), cm);
 
         String params =
-            Arrays.asList(args).stream().collect(Collectors.toStringJoiner(", ")).toString();
+            Arrays.asList(args).stream().collect(Collectors.joining(", ")).toString();
 
         ConcreteMethod sm = new ConcreteMethod(
             method.getReturnType(), method.getName(),
@@ -150,7 +150,7 @@ public class TestHarness {
             null, Arrays.asList((Method)method));
         Class cstub = new Class(specimen.getName());
 
-        String params = Arrays.asList(args).stream().collect(Collectors.toStringJoiner(", ")).toString();
+        String params = Arrays.asList(args).stream().collect(Collectors.joining(", ")).toString();
 
         ConcreteMethod sm = new ConcreteMethod(
             "int", SourceModel.stdMethodName,