The 4 Essential Skills of the Software Developers

#coding #algorithms #computerscience #develop

There are 4 main skill groups where all programmers must have. Most of these skills are resistant in time and are not influenced by the development in specific technologies (that are changing constantly). These are the skills that any good programmer has and to which every beginner must strive:

coding (20%)
algorithmic thinking (30%)
computer science and software engineering concepts (25%)
languages and software technologies (25%)

Skill #1 – Coding (20%)

Writing code forms around 20% of the minimum knowledge and skills of a programmer, needed for starting a job in a software company. The skill of coding includes the following components:

Working with variables, conditional statements, loops
Using functions, methods, classes and objects
Data manipulation: arrays, lists, hash tables, strings

The skill of coding can be acquired in a few months of hard learning and solving practical problems by writing code every day. If you don't learn perfectly the material, you can't become a programmer. You are going to miss fundamentals and it will be harder in the future. For this reason, give enough time to programming basics: solve many problems and write code every day for months until you learn to solve every problem very easily. Then go ahead.

We specifically note that the programming language does not matter for the ability to code. You can code or not. If you can code with C#, you will easily learn to code with Java, C++ or other languages.

Skill #2 – Algorithmic Thinking (30%)

The algorithmic (logical, engineering, mathematical, abstract) thinking forms around 30% of the minimum skills of a programmer needed to start the profession. Algorithmic thinking is the ability to break a particular problem into a logical sequence (algorithm), to find a solution for every separate step and then assemble the steps into a working solution. That is the most important skill of any programmer.

How to build algorithmic thinking?

Algorithmic thinking is developed by solving multiple programming (1000+) problems, as diverse as possible. That is the recipe: solving thousands of practical problems, building algorithms and implementing the algorithms, along with debugging the issues that come up in the process.
Sciences like physics, mathematics and similar ones helps a lot, but they are not mandatory! People with engineering and technical skills usually learn very easily to think logically, because they already have problem solving skills, even if it is not algorithmic.
The ability of solving programming problems (for which algorithmic thinking is needed) is extremely important for a programmer. Many companies test particularly this skill during their job interviews.

To become good at this profession you must add logical thinking and problem solving skills. For example, working with data structures (arrays, lists, matrices, hash-tables, binary trees) and basic algorithms (searching, sorting, searching in tree structures, recursion, etc.).

As you may have guessed, the choice of programming language does not matter for the development of algorithmic thinking. It is a skill unrelated to Programming. Because of their well-developed logical thinking, there is the misconception that all programmers are smart people and having a high IQ is a requirement for entering into the profession.

Skill #3 – Computer Science and Software Engineering Concepts (25%)

Fundamental knowledge and skills for programming, software development, software engineering and computer science comprise around 25% of the developer's minimum skills to start a job. Here are the more important of these skills and knowledge:

basic mathematical concepts related to programming: coordinate systems, vectors and matrices, discrete and non-discrete mathematical functions, state automata and state machines, combinatorics and statistics concepts, algorithm complexity, mathematical modeling and others
programming skills – code writing, working with data, using conditional statements and loops, working with arrays, lists and associative arrays, strings and text processing, working with streams and files, using programming interfaces (APIs), working with IDE, debugger, developer tools, etc.
data structures and algorithms – lists, trees, hash-tables, graphs, search, sorting, recursion, binary search trees, etc.
object-oriented programming (OOP) – working with classes, objects, inheritance, polymorphism, abstraction, interfaces, data encapsulation, exceptions management, design pattern
functional programming (FP) – working with lambda functions, higher order functions, functions that return a function as a result, closure, etc.
databases – relational and non-relational databases, database modeling (tables and links between them), SQL query language, object-relational mapping (ORM), transactions and transaction management
network programming – network protocols, network communication, TCP/IP, concepts, tools and technologies from computer networks
client-server interaction, peer to peer communication, back-end technologies, front-end technologies, MVC architectures
technologies for server development (back-end) – Web server architecture, HTTP protocol, MVC architecture, REST architecture, web development frameworks, templating engines
front-end technologies (client-side development) – HTML, CSS, JS, HTTP, DOM, AJAX, communication with back-end, calling REST API, front-end frameworks, basic design and UX (user experience) concepts
mobile technologies – mobile apps, Android and iOS development, mobile user interface (UI), calling server logic
embedded systems – microcontrollers, digital and analog input and output control, sensor access, peripheral management
operating systems – working with operating systems (Linux, Windows, etc.), installation, configuration and basic system administration, process management, memory, file system, users, multitasking, virtualization and containers
parallel and asynchronous programming – thread management, asynchronous tasks, promises, common resources, and access synchronization
software engineering – source control systems, development management, task planning and management, software development methodologies, software requirements and prototypes, software design, software architectures, software documentation
software testing – unit testing, test-driven development, QA engineering, error reporting and error tracking, automation testing, build processes and continuous integration

We need to once again mention that the programming language does not matter for acquiring all these skills. You will accumulate them slowly, over years. Some fundamental knowledge can be learned theoretically, but to get an in-depth understanding of it you need a lot of practice.

Having basic knowledge in the areas listed above is enough to start a job as a programmer. Your further improvement will come as a result of the technology and development tools you will use in your day-to-day work.

Skill #4 – Programming Languages and Software Technologies (25%)

Programming languages and software development technologies form around 25% of a programmer's skills. They have the largest learning content, but they change very fast over time. If we look at the job offers in the software industry, they usually mention words like the ones below, but in the job offers they secretly mention the three main skills: coding, algorithmic thinking and knowing the fundamentals of computer science and software engineering.

For those clearly technological skills the programming language does matter.

Note: only for these 25% of the profession the programming language does matter!
For the rest 75% of the skills the programming language doesn't matter, and these skills are resistant in time and transferable between different languages and technologies.
Here are some commonly used software development stacks which software companies are looking for (as of Jan 2023):

C# + OOP + FP + classes from .NET + SQL Server databases + Entity Framework (EF) + ASP.NET MVC + HTTP + HTML + CSS + JS + DOM + jQuery + cloud + containers
JavaScript (JS) + OOP + FP + databases + MongoDB or MySQL + HTTP + web programming + HTML + CSS + JS + DOM + jQuery + Node.js + Express + Angular or React + cloud + containers
Python + OOP + FP + databases + MongoDB or MySQL + HTTP + web development + HTML + CSS + JS + DOM + jQuery + Django or Flask + cloud + containers
Java + Java API classes + OOP + FP + databases + MySQL + HTTP + web programming + HTML + CSS + JS + DOM + jQuery + JSP / Servlets + Spring MVC or Java EE / JSF + cloud + containers
PHP + OOP + databases + MySQL + HTTP + web development + HTML + CSS + JS + DOM + jQuery + Laravel or Symfony or other MVC framework for PHP + cloud + containers
C++ + OOP + STL + Boost + native development + databases + HTTP + other languages and technologies
Swift + OOP + MacOS + iOS + Cocoa + Cocoa Touch + XCode + HTTP + REST + other languages and technologies
Go + OOP + Linux + Protobuf + gRPC + cloud + containers + other languages and technologies

If the words above look scary and incomprehensible, then you are at the very beginning of your career and you need many years of learning until you reach the profession of a software engineer. Do not worry, every programmer goes through one or several technology stacks and needs to study a set of interconnected technologies, but it is imperative for you is know how to write programming logic (to code) and think algorithmically (to solve programming problems). Becoming a good software engineer is impossible without those skills!

To be a software developer, you need to learn coding (20%), learn algorithmic thinking, and solve problems (30%), to have fundamental knowledge of programming and computer science (25%) and to master a specific programming language and the technologies around it (25%). Be patient, for a year or two all this can be mastered on a good starting level, if you are serious.