During the last week, our class discussed more foundational and abstract algorithms in the perspective of the computer. First, we talked about two different means of searching, linear search, and binary search. They were different in the way of searching the target data and this led to higher or lower efficiency in certain situations. The linear search conducted a sequential search starting from the first data of the range. This mean of searching was very straightforward and take more time than other methods but it was advantageous when the data were not sorted. In contrast, the binary search had a specific algorithm which allowed shorter trials until reaching to the target data. The only shortcoming of it was that it cannot be conducted if the user doesn’t know how the data is sorted.

I could better understand the application of these methods after the Huffman encoding tree. It was interesting to see during the lab that the most frequent letter appears near the top of the tree where the depth is not large. This allowed the data to be compressed as much as possible.

Overall, these discussions and materials were about a very small segment of data search, which includes farther accuracy, memory, and re-usability, other than just efficiency. This approach was coherent to what one of the readings said in the class. In order to develop a human familiar software and applications, understanding the foundational algorithm of how the computer inherently works should be prioritized.