Index: doc/theses/aaron_moss_PhD/phd/type-environment.tex
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--- doc/theses/aaron_moss_PhD/phd/type-environment.tex	(revision 1836081bd1f9cea4e4c6358063a5670374b96070)
+++ doc/theses/aaron_moss_PhD/phd/type-environment.tex	(revision d438111c9a21e364ddbdd5277ae5652b3c5cc5d5)
@@ -5,5 +5,5 @@
 As discussed in Chapter~\ref{resolution-chap}, being able to efficiently determine which type variables are bound to which concrete types or whether two type environments are compatible is a core requirement of the resolution algorithm. 
 Furthermore, expression resolution involves a search through many related possible solutions, so the ability to re-use shared subsets of type-environment data and to switch between environments quickly is desirable for performance. 
-In this chapter, I discuss a number of type environment data-structure variants, including some novel variations on the union-find \cite{Galler64} data structure introduced in this thesis. 
+In this chapter, I discuss a number of type-environment data-structure variants, including some novel variations on the union-find \cite{Galler64} data structure introduced in this thesis. 
 Chapter~\ref{expr-chap} contains empirical comparisons of the performance of these data structures when integrated into the resolution algorithm.
 
@@ -274,5 +274,5 @@
 \section{Conclusion \& Future Work}
 
-This chapter presents the type environment data structure in Section~\ref{env-defn-sec}, as well as some more sophisticated approaches to optimize performance for workloads encountered in the expression resolution problem in Section~\ref{env-approaches-sec}, and asymptotic analysis of each approach in Section~\ref{env-analysis-sec}. 
+This chapter presents the type environment abstract data type, some type-environment data-structures optimized for workloads encountered in the expression resolution problem, and asymptotic analysis of each data structure. 
 Chapter~\ref{expr-chap} provides experimental performance results for a representative set of these approaches. 
 One contribution of this thesis is the union-find with classes data structure for efficient retrieval of union-find class members, along with a related algorithm for reversing the history of $union$ operations in this data structure.