Liam's Computer Science Learning Journal

Week 1 Learning Reflection                     It is safe to say that Operating Systems has come on strong and fast with myriad moving pieces. Week 1 has seen me revisiting binary and hexadecimal number systems, C syntax, computer architecture (in a simultaneously and confoundingly more granular and universal way than the class that goes by that name), PowerShell, Docker, WSL, Linux, and surely more to be revealed. This is what I wanted! By way of lectures, Professor Ogden provided a profound lore dump on the history of operating systems and why C is such a vastly powerful language that lives within all major computer systems. This was a great diving board moment into the pool where Linus Torvalds concocted Linux from a guy who concocted a book on making an OS from Unix which is its own series of inspirations and concoctions eventually leading all the way back to Alan Turing. Other memorable moments from lectures included discu...

Briefly summarize the what you consider to be the three (3) most important things you learned in this course.           On the other side of CST363 Intro to Database Systems , I have gained a deeper understanding of how databases are a foundational part of the programming landscape and how they integrate with broader software systems. One of the most important takeaways was learning how data is not only organized but also preserved and managed for long-term use, ensuring reliability and consistency in real-world applications in industries with small margin for error, such as medical, educational and financial technology. I also developed a clearer grasp of how entities and their attributes relate within a database, which helped me understand data modeling and relational structures more intuitively. Finally, working hands-on with MySQL Workbench, Java integration, and MongoDB gave me practical experience in both relational and non-relational systems, reinfor...

  Prompt for this week's journal entry. Compare MongoDB with MySQL.  What are some similarities?  What are some differences?  When would you choose one over the other?           While MySQL provided a very point-and-shoot process with its application, MongoDB has felt a little more abstract and esoteric running predominantly through commands and notepad scripts instead of a central program. Having only previously worked in IDE's, I found MySQL to be instantly familiar. Learning and troubleshooting in MySQL is not completely unlike Java--having a log that acts as a console from which to diagnose error messages is fundamentally parallel to troubleshooting in an IDE. Writing code in a notepad file and saving it as a JavaScript file is quite removed from my prior coding experience but felt quite magical to get familiar with for these MongoDB assignments. I would say the conceptual database functions are where MongoDB and MySQL are most simi...

          Week 6 of CST363 offered many learning opportunities both in assigned reading and labs. While the reading gave the initial rundown on database connections, query execution, and the use of prepared statements through APIs like JDBC, the Java labs offered hands-on teaching moments that clarified how to use these concepts in practice. Working directly with JDBC to manage connections, execute SQL queries, and handle transactions worked wonders in solidifying the material. Experiencing Java interface with SQL through IntelliJ and MySQL Workbench additionally contextualized using Connections and using prepared statements to aid prevention of SQL injection attacks. The conceptual topics tackled in the reading are an aspect of computer science that I am always compelled to learn about--in this case it is the different programming paradigms when considering SQL in the context of application development. Qualifying the differences between imperative and dec...

 Referencing  Slow Indexes in RDBMS : if indexes are supposed to speed up performance of query, what does the author mean by a slow index?       In my time working with indexes thus far, I have seen what miracles they can work for improving query performance. This is my first encounter with unpacking how indexes could actually slow a query down. Author Markus Winand illustrates how index lookups can still be slow and expensive even when functioning properly. Winand explains how index performance entails more than just tree traversal in a clear and inviting fashion. First, the lookup conducts the tree traversal by navigating down the index B-tree to reach the intended leaf node. Upon following the leaf node chain, multiple hits can mean the database needs to retrieve all matching index entries. For each matching index entry, the database will then access the corresponding row in the table, which could be located entirely elsewhere in memory or disk blocks. W...