docs: fix header level

docs/source/contributor-guide/adding_a_new_expression.md

@@ -165,14 +165,14 @@ pub(super) fn spark_unhex(args: &[ColumnarValue]) -> Result<ColumnarValue, DataF
 
 > **_NOTE:_**  If you call the `make_comet_scalar_udf` macro with the data type, the function signature will look include the data type as a second argument.
 
-## API Differences Between Spark Versions
+### API Differences Between Spark Versions
 
 If the expression you're adding has different behavior across different Spark versions, you'll need to account for that in your implementation. There are two tools at your disposal to help with this:
 
 1. Shims that exist in `spark/src/main/spark-$SPARK_VERSION/org/apache/comet/shims/CometExprShim.scala` for each Spark version. These shims are used to provide compatibility between different Spark versions.
 2. Variables that correspond to the Spark version, such as `isSpark32`, which can be used to conditionally execute code based on the Spark version.
 
-## Shimming
+## Shimming to Support Different Spark Versions
 
 By adding shims for each Spark version, you can provide a consistent interface for the expression across different Spark versions. For example, `unhex` added a new optional parameter is Spark 3.4, for if it should `failOnError` or not. So for version 3.2 and 3.3, the shim is: