1769497, incorporated author feedback.

Author: john-par

docs/parallel/concrt/how-to-use-a-message-block-filter.md

@@ -32,7 +32,7 @@ Because the `transformer` object receives only prime numbers, the `transformer`
 
 The `transformer` object now processes only those values that are prime. In the previous example, `transformer` object processes all messages. Therefore, the previous example must receive the same number of messages that it sends. This example uses the result of the [concurrency::send](reference/concurrency-namespace-functions.md#send) function to determine how many messages to receive from the `transformer` object. The `send` function returns **`true`** when the message buffer accepts the message and **`false`** when the message buffer rejects the message. Therefore, the number of times that the message buffer accepts the message matches the count of prime numbers.
 
-## Example: Complete code sample
+## Example: Complete message block filter code sample
 
 The following code shows the complete example. The example calls both the `count_primes` function and the `count_primes_filter` function.
 

docs/parallel/concrt/how-to-use-exception-handling-to-break-from-a-parallel-loop.md

@@ -40,7 +40,7 @@ The following example creates a `tree` object and searches it for several values
 
 This example uses the [concurrency::parallel_invoke](reference/concurrency-namespace-functions.md#parallel_invoke) algorithm to search for values in parallel. For more information about this algorithm, see [Parallel Algorithms](../../parallel/concrt/parallel-algorithms.md).
 
-## Example: Complete code sample
+## Example: Complete exception handling code sample
 
 The following complete example uses exception handling to search for values in a basic tree structure.
 

docs/parallel/concrt/how-to-use-parallel-containers-to-increase-efficiency.md

@@ -10,7 +10,7 @@ This topic shows how to use parallel containers to efficiently store and access
 
 The example code computes the set of prime and Carmichael numbers in parallel. Then, for each Carmichael number, the code computes the prime factors of that number.
 
-## Example: is_prime function
+## Example: Determine if an input value is a prime number
 
 The following example shows the `is_prime` function, which determines whether an input value is a prime number, and the `is_carmichael` function, which determines whether the input value is a Carmichael number.
 
@@ -24,23 +24,23 @@ This example uses a [concurrency::concurrent_queue](../../parallel/concrt/refere
 
 [!code-cpp[concrt-carmichael-primes#2](../../parallel/concrt/codesnippet/cpp/how-to-use-parallel-containers-to-increase-efficiency_2.cpp)]
 
-## Example: prime_factors_of function
+## Example: Find all prime factors of a given value
 
 The following example shows the `prime_factors_of` function, which uses trial division to find all prime factors of the given value.
 
 This function uses the [concurrency::parallel_for_each](reference/concurrency-namespace-functions.md#parallel_for_each) algorithm to iterate through the collection of prime numbers. The `concurrent_vector` object enables the parallel loop to concurrently add prime factors to the result.
 
 [!code-cpp[concrt-carmichael-primes#3](../../parallel/concrt/codesnippet/cpp/how-to-use-parallel-containers-to-increase-efficiency_3.cpp)]
 
-## Example: Call the prime_factors_of function
+## Example: Processes each element in the queue of Carmichael numbers
 
 This example processes each element in the queue of Carmichael numbers by calling the `prime_factors_of` function to compute its prime factors. It uses a task group to perform this work in parallel. For more information about task groups, see [Task Parallelism](../../parallel/concrt/task-parallelism-concurrency-runtime.md).
 
 This example prints the prime factors for each Carmichael number if that number has more than four prime factors.
 
 [!code-cpp[concrt-carmichael-primes#4](../../parallel/concrt/codesnippet/cpp/how-to-use-parallel-containers-to-increase-efficiency_4.cpp)]
 
-## Example: Complete code sample
+## Example: Complete parallel container code sample
 
 The following code shows the complete example, which uses parallel containers to compute the prime factors of the Carmichael numbers.
 

docs/parallel/concrt/how-to-use-parallel-invoke-to-execute-parallel-operations.md

@@ -8,7 +8,7 @@ ms.assetid: a6aea69b-d647-4b7e-bf3b-e6a6a9880072
 
 This example shows how to use the [concurrency::parallel_invoke](reference/concurrency-namespace-functions.md#parallel_invoke) algorithm to improve the performance of a program that performs multiple operations on a shared data source. Because no operations modify the source, they can be executed in parallel in a straightforward manner.
 
-## Example: Create MyDataType variable
+## Example: Create, initialize, and perform operations on a variable
 
 Consider the following code example that creates a variable of type `MyDataType`, calls a function to initialize that variable, and then performs multiple lengthy operations on that data.
 

docs/parallel/concrt/how-to-write-a-parallel-for-loop.md

@@ -22,7 +22,7 @@ The following example shows the `parallel_matrix_multiply` function, which uses
 
 This example parallelizes the outer loop only because it performs enough work to benefit from the overhead for parallel processing. If you parallelize the inner loop, you will not receive a gain in performance because the small amount of work that the inner loop performs does not overcome the overhead for parallel processing. Therefore, parallelizing the outer loop only is the best way to maximize the benefits of concurrency on most systems.
 
-## Example: Complete code sample
+## Example: Complete parallel_for loop code sample
 
 The following more complete example compares the performance of the `matrix_multiply` function versus the `parallel_matrix_multiply` function.