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diff --git a/chapters/sigmod23/conclusion.tex b/chapters/sigmod23/conclusion.tex
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 \section{Conclusion}

 \label{sec:conclusion}

 

-This chapter discussed the creation of a framework for the dynamic extension of

-static indexes designed for various sampling problems. Specifically, extensions

-were created for the alias structure (WSS), the in-memory ISAM tree (IRS), and

-the alias-augmented B+tree (WIRS). In each case, the SSIs were extended

-successfully with support for updates and deletes, without compromising their

-sampling performance advantage relative to existing dynamic baselines. This was

-accomplished by leveraging ideas borrowed from the Bentley-Saxe method and the

-design space of the LSM tree to divide the static index into multiple shards,

-which could be individually reconstructed in a systematic fashion to

-accommodate new data. This framework provides a large design space for trading

-between update performance, sampling performance, and memory usage, which was

-explored experimentally. The resulting extended indexes were shown to approach

-or match the insertion performance of the B+tree, while simultaneously

-performing significantly faster in sampling operations under most situations.

+In this chapter, we discussed the creation of a dynamization system
+based
 upon the Bentley-Saxe method that can be used to create dynamized
+sampling
 data structures that outperform dynamic baselines and feature a
+configurable
 design space. Specifically, we discussed dynamized versions
+of the alias
 structure for weighted set sampling, the alias-augmented
+B+tree for
 weighted independent range sampling, and the ISAM tree for
+independent
 range sampling. In each case, the static structures were
+dynamized with
 support for inserts and deletes without compromising
+their query performance
 advantage over dynamic baselines, and while

+matching or exceeding the dynamic structures' insertion performance.

+

+The techniques proposed in chapter, however, are limited to a very
+specific class
 of data structures for addressing a very specific type
+of search problem. While these results are promising, they fall short
+of a general
 solution to data structure dynamization that addresses
+the
 limitations of classical dynamization techniques discussed in
+Chapter~\ref{chap:background}. In the next chapter, we will take several

+of the results of this chapter, generalize them, and apply them to a much

+wider range of data structures.