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@@ -347,5 +347,24 @@ is efficient sorting, correct usage of registers, memory and syscalls will great
 affect and boost performance. 
 
 \section{Conclusion}
-    
+In this project insertionsort and quicksort have been implemented in assembly x86 64 
+with the goal of studying efficient sorting. Although the algorithms perform the same task,
+ they are in fact very different. Firstly, from the benchmarks we have learned that the
+algorithms are heavily affected by the dataset itself. Both algorithms have very
+different run times on the sorted, reversed, and random datasets, despite the sets
+having the same size. As discussed, earlier insertionsort and quicksort have roughly
+the same performance on reversed datasets, insertionsort is optimal on sorted or
+small datasets, and quicksort excels on random and very large datasets. So one
+could say that efficient sorting requires an efficient algorithm well suited for
+the dataset. But it should also be mentioned that in most general cases with
+random output quicksort will most likely outperform insertionsort. Furthermore,
+from the testings we have learned that the stable tests used on insertion sort
+cannot be used on quicksort, since quicksort doesn’t preserve the order the inputs.
+This means that the algorithms might produce different results even if used
+on the same dataset. Another important observation has been that although the algorithms
+themselves determine the asymptotic run times, the concrete implementations also matter
+for the total run times. Which means that memory usage, registers, stack management, and
+syscalls should also be considered while trying to create a fast sorting algorithm. Summing
+all these observations up in one sentence, we can conclude that a recipe to efficient sorting
+is choosing a well suited algorithm supported by a smart implementation. 
 \end{document}