diff --git a/samples/features/in-memory/code-snacks/sqlonwindows/in-mem_columnstore/README.md b/samples/features/in-memory/code-snacks/sqlonwindows/in-mem_columnstore/README.md
index 71e15921..54c72abb 100644
--- a/samples/features/in-memory/code-snacks/sqlonwindows/in-mem_columnstore/README.md
+++ b/samples/features/in-memory/code-snacks/sqlonwindows/in-mem_columnstore/README.md
@@ -1,4 +1,4 @@
-# In-Memory & Columnar Store Code Snack
+# In-Memory & Columnar Store Code Snack (SQL Server 2016)
 In this code snack, developers will experience the benefit of performing real-time operation analytics enabled by leveraging a memory optimized table in combination with a columnstore index. The Visual Studio project contains a load generator that will be used to simulate a write heavy workload. They will initially run the simulator against a disk based table with a clustered index (btree) and take note of the rows inserted per second, and will measure the performance of a provided analytics query while the system is under the heavy write load. They will then author the T-SQL to create the memory optimized table with a columnstore index, update the load generator to target the memory optimized table and observe the improved performance characteristics.
 
 ## Requirements
diff --git a/samples/features/r-services/code-snacks/clustering_in_R/README.md b/samples/features/r-services/code-snacks/clustering_in_R/README.md
index f8a41365..9fd6394e 100644
--- a/samples/features/r-services/code-snacks/clustering_in_R/README.md
+++ b/samples/features/r-services/code-snacks/clustering_in_R/README.md
@@ -1,4 +1,4 @@
-# Clustering in R
+# Clustering in R (SQL Server 2016)
 In this code snack, developers will experience authoring R code to help them run a clustering exercise that “magically” groups data into distinct populations by using an unsupervised clustering algorithm, k-means. The k-means script will be packaged within a SQL stored procedure for convenient execution from a .NET application.
 
 ## About Clustering
diff --git a/samples/features/security/code-snacks/sqlonwindows/README.md b/samples/features/security/code-snacks/sqlonwindows/README.md
index c87723a8..9f0d2c3f 100644
--- a/samples/features/security/code-snacks/sqlonwindows/README.md
+++ b/samples/features/security/code-snacks/sqlonwindows/README.md
@@ -1,4 +1,4 @@
-#  Dynamic Data Masking & Row Level Security Code Snack
+#  Dynamic Data Masking & Row Level Security Code Snack (SQL Server 2016)
 In this code snack, developers will create a database having human resources data, including a table containing simulated employee pay data. They will be guided thru the sample data to highlight the sensitive information it contains (e.g., social security numbers and salaries) and then configuring the masking of the sensitive data. In addition, they will enable Row Level Security to handle three different roles: contractors (who have no visibility to any rows except their own in the table), HR (who can view all employee rows except those of executives) and Executives (who can view all employee rows). They will complete a .NET application that queries the database to see the differing outcomes that result based on Row Level Security policy.
 
 ## Requirements