Craft over Art

This method talks about how indulging in your own artistic nature isn’t always the best option even if you think the product would turn out better if you did it this way. If you are being paid to build something that will solve a problem, this method of Craft over Art explains you need to really consider the situation at hand. In this method, the situation that is discussed is that you believe that you are able to do something outstanding and fantastic that will impress your colleagues. In this situation, you are building something for a user. You shouldn’t be indulging in artistic expression. A lot of the times when we are handed with a task, we can sometimes think about the most outstanding ways to do something, rather than just to get the task done. This can go two ways. Doing something outstanding for a task can be great and have it’s benefits, but what will it cost the effectiveness of it? On the other hand, we can do the task at hand and that will be that. We won’t be able to put any personal expression in it, but is that a bad thing? Of course it isn’t a bad thing. This method seems to be very similar to function over form.

It is a matter of situational awareness. This is something I really enjoyed from this article. Make more straightforward choices and do not try to “sugar coat” solutions. As soon as you start making unfavorable trade offs in certain scenarios, the outcome will not always be as you like. in other words if you want a straightforward answer, you should provide a straight forward solution. Even though this isn’t always the case, I learned that you should always try your best to just try and perform the basic tasks first without adding anything extra or unique. Quality takes time, but having the correct operations in a product is what can make all the difference.

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Dig Deeper

Often times, as programmers, we will run into problems and will not know how to deal with these issues. Figuring out how to proceed is one of the most difficult things to do. What if the tool I am using doesn’t work? What if I am not fluent in a certain programming language to understand how to overcome a certain bug or fix a certain algorithm? These are all questions that concern us. The Dig Deeper method is very helpful in that it tells you to not just take everything that you learn for face value. Although tight deadlines and code maintenance may be daunting, you should always try your best in order to make sure that the code is clean. What we mean by this is that if you look up tutorials on how to do a certain task, those tutorials may have helped you solved the issue, but they could also have set you up for a lot of issues in the future. The tutorials may have cut corners or not complete things as efficiently as they should.

I really like this idea of Digging Deeper because we often try things sequentially that we find and just hope that the first or second method works. And if it does work we tend to just stick with it without even batting an eye at potential issues or large overhead that can carry. By completing tasks fully and really understanding problems inside and out, it is good to check multiple sources or tutorials. Code maintenance is huge aspect of live design programming. If you were to just look up random tutorials on how to do certain things for your code, you can get confused. You could look sup so many tutorials for each problem and eventually you won’t even be able to understand what does what action in your own code. And at that point, is it even yours? Being curious and making sure that you understand your code in a meaningful way will help you succeed and make further improvements to it. And the nice thing about this method, and many other methods, is that they don’t only apply to programming, but actually working with your team.

Efficiency, Inside and Out.

Creating efficient programs is very important, in that it allows processes to run faster and in some cases, with less memory. Program optimization is key in making fast and reusable code. Currently, we are learning about various ways to create efficient implementations of object-specific attributes. By doing these, we need to understand that we need to be careful and consistent with our designs because if, in the future, things need to be modified or added, it can be done with ease. Database querying is a process in which mass amounts of data are sifted through by algorithms to extract to inject specific data. The article I choose mentions that, not only do we have to be efficient with the database query algorithms, but also within other aspect such as power consumption.

The article explains how cache servers are very expensive because they use the “power-hungry” and expensive Random Access Memory modules. However, some cache servers are starting to implement and test Flash Memory databases. Since flash memory is so cheap and has much more storage density that RAM, it would seem like and obvious switch. However, along with the cheap speed comes slower performance than RAM.

I choose the article because working with efficient materials and hardware can lead to innovations and new implantation of design ideas. We discuss design principles so that we can understand the advantages and disadvantage to the better and worse outcomes of issues, respectively. From the article “The more important concern is keeping up with the requests flooding the data center. From the article, “The CSAIL researchers’ system, dubbed BlueCache, does that by using the common computer science technique of ‘pipelining.’ Before a flash-based cache server returns the result of the first query to reach it, it can begin executing the next 10,000 queries. The first query might take 200 microseconds to process, but the responses to the succeeding ones will emerge at .02-microsecond intervals.”

In the future, I expect to apply what was learned by finding ways to further conserve memory and creating the most efficient design principles for my projects. This is important because querying mass amounts of data can take very long (and can use a lot of power) and it is important in recognizing that there are certain design principles that work better in certain situations. The article also states that “A data center for a major web service such as Google or Facebook might have as many as 1,000 servers dedicated just to caching.”, and if you are performing that many calculations, you will need to have efficient modeling and understand good design patterns to handle all of the data correctly. This also made me realize that there are a lot of other factors, such as processing and energy costs, that are considered in certain stages of program modeling.

Source: (https://www.sciencedaily.com/releases/2017/08/170831115210.htm)