When you think about quality software development, you think about good craftsmanship. With great sites like DesignSpark Mechanical, RPG Maker MV, and SuperPro Designer and an abundance of essential libraries, it does not take a village to prepare a decent software tool, at least not anymore.
These days a few engineers who know what they are doing can completely deliver systems. In this article, we will go through the top essential concepts every software engineer should know about.
A good software engineer should know and use design patterns; they must refactor codes, write test units and seek simplicity. Aside from the primary method which are concepts that every engineer should know about. These concepts go beyond the programming languages and projects, and they are not designed patterns, but wide areas that you will need to be familiar with.
Relational Databases:
This concept has recently got a bad name because they can’t scale well to support large web services. However, this was one of the fundamental achievements in computing that has carried the software landscape for two decades and will continue to remain strong. Relational databases are excellent for order management systems, corporate databases, and P&L data.
The technique of data normalization is about correcting our ways of portioning the data among tables to minimize data redundancy and increase the pace of retrieval.
Security:
With the rise of hacking and data sensitivity, the security of your information and software is vital. It’s a broad topic that is inclusive of authentication, authorization and information transmission. Authentication involves verification of user identity; a common website will prompt for a password, this authentication happens over SSL, it’s a way to transmit encrypted information over HTTP. Authorization is about permissions and is essential incorporates, especially the ones that define workflows. Another security area is network protection. This includes operating systems, configurations and monitoring to be aware of hackers. Networks are vulnerable, and any piece of software that is attached to these networks is susceptible as well.
Cloud Computing:
Commodity cloud computing is changing the way we deliver large scale web applications. They are hugely parallel, and cheap cloud computing can reduce costs and time for the market. Cloud computing came out of parallel computing and grew from it; it’s a concept that many problems can be solved quickly by running the computations in parallel. After the parallel algorithms, the idea of grid computing was introduced; this ran parallel computation on idle desktops.
Concurrency:
Concurrency is one concept that topic engineers usually get wrong and it’s understandable because the brain juggles so much stuff at a time and in schools, linear thinking is stressed on quite a lot. The idea of concurrency is emphasized on in the modern system. Concurrency refers to parallelism but inside the application. Many modern languages include a built-in concept of concurrency.
Caching:
Every modern website runs on a cache, and it’s an in-memory store that includes a subset of information that is typically stored in the database. The need for cache comes through the fact that creating results that are based on the database is expensive. If you have a site that lists books that were popular the week before, you would want to record this information and place it in the cache. User requests can bring the data from the cache instead of a searching database and regenerating the same information.
However, caching does come with a price, only the subset information can be stored in the memory, and the most common data cutting strategy is to remove items that are used the least. This removal method is efficient and is so that the application is fast and there are no lags in the future.
Hashing:
When sites and software use hashing, they do it with the intent of having quick access to the data. If the data is stored in sequence, the time required to find the item is proportional to the size of the list. Each element, a hash function calculates a number that is used as an index into the table. Once a hash is given the right purpose, it uniformly spreads the data along the table; the lookup time is a constant component. Perfecting the idea of hashing is tough and to deal with it can be a task, the functions can be complex and sophisticated, but modern libraries have reasonable defaults. The important thing here is knowing how they work, and you can tune them to get the most performance benefit.
