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%% **** Container types common in programs
-Almost every program makes extensive use of container data structures -- structures which hold a collection of values.
-Often, programmers will have some requirements they want to impose on this collection, such as not storing duplicate elements, or storing the items in sorted order.
+Almost every program makes extensive use of container data types -- structures which hold a collection of values.
+Often, programmers will also have some requirements they want to impose on this collection, such as not storing duplicate elements, or storing the items in sorted order.
%% **** Functionally identical implementations
-However, implementing these collection types manually wastes time, and can be hard to do right for more complicated structures.
-Most programmers will simply use one or two of the collection types provided by their language.
-Some languages, such as Python, go a step further, providing built-in implementations of growable lists and associative maps, with special syntax for both.
+However, implementing these collection types wastes time, and can be hard to do right for more complicated structures.
+Most programmers will instead use one or two of the collection types provided by their language.
+Some languages, such as Python, go a step further, providing built-in implementations of common data structures, with special syntax and handling.
%% **** Large difference in performance
-Unfortunately, the underlying implementation of container types which function the same can have a drastic effect on performance (\cite{l_liu_perflint_2009}, \cite{jung_brainy_2011}).
+However, the underlying implementation of container types which function the same can have a drastic effect on performance (\cite{l_liu_perflint_2009}, \cite{jung_brainy_2011}).
By largely ignoring the performance characteristics of their implementation, programmers may be missing out on large performance gains.
%% *** Motivate w/ effectiveness claims