I\u2019d advise you to go deep and focus on learning the ins and outs of a single programming language<\/a>, so you can feel really confident in your ability to write code in that language.<\/p>\n You should have some experience and mastery of at least one development platform and the related technologies or frameworks that go with it.<\/p>\n What do I mean by platform?<\/em><\/p>\n Well, generally it means operating system (OS), but it can also apply to other abstractions that act similar to operating systems.<\/p>\n For example, you could be a Mac developer or Windows developer focusing on the Mac or Windows operating systems, but you could also be a web developer focused on a specific web platform.<\/p>\n It\u2019s not so important what you choose, so much as it is that you choose something. Companies usually hire developers to develop for a specific platform or technology. You\u2019ll have a much easier time getting a job as an iOS developer if you have expertise with that specific platform.<\/p>\n This means being familiar with the platform itself, as well as what development tools, idiomatic patterns, and common frameworks programmers typically use when developing for that platform.<\/p>\n So don\u2019t just pick a language; pick a platform as well.<\/p>\n A framework is simply a set of libraries<\/strong><\/a> that are used to develop code on a particular platform or on multiple platforms<\/strong>. It usually makes common programming tasks on that platform easier.<\/p>\n For example: Most C# developers use the .NET Framework for writing C# applications. The .NET Framework consists of many libraries and classes that allow a C# developer to work at a higher level of abstraction since he doesn\u2019t have to completely reinvent the wheel every time he wants to do something.<\/p>\n A stack is a bit different. A stack is a set of technologies, usually including a framework, that are commonly used together to create a full application<\/strong>.<\/p>\n For example, there is a common stack called the MEAN stack. It stands for MongoDB, Express.js, AngularJS, and Node.js.<\/p>\n MongoDB<\/em> is a database technology. Express.js<\/em> is a Node.js framework for creating web applications. AngularJS<\/em> is a front end JavaScript framework for creating the user interfaces for web applications. Node.js<\/em> is a runtime environment for developing web-based applications in JavaScript.<\/p>\n If you know all those technologies and frameworks, you\u2019ll be able to develop an entire web application. Learning a stack can be extremely valuable because it means you have all the required skills to develop a full application.<\/p>\n There are two main database technologies<\/strong>: relational databases and document databases.<\/p>\n At the very least, you should know:<\/p>\n In addition, know how to retrieve and store data programmatically from your code<\/strong> with your chosen platform and \/ or framework.<\/p>\n Most developers are expected to be able to write code that can interact with a database.<\/p>\n Logical thinking is the number one skill required for programming.<\/p>\n The best way to get better at programming logic<\/a> is to create software. Problems will come up, and you\u2019ll have to use logic to figure out the solution.<\/p>\n This is a superior way of improvement compared to memorizing syntax or pieces of code. It\u2019s focusing on the logic behind the code, and then having a purpose for implementing the syntax \u2013 leading to deep understanding and skill.<\/p>\n Algorithms<\/strong> are the common ways of solving various computer science \/ programming problems.<\/p>\n For example, there are several algorithms that are commonly used for sorting lists of things programmatically. Each of these sorting algorithms has a different set of properties regarding speed, memory size requirements, and the ideal kind of data it works on.<\/p>\n There are many of these algorithms in the field of computer science, and it is also important to understand how to write your own variations of these algorithms to solve the kind of tricky problems you might encounter when solving real programming problems.<\/p>\n Often, being good with algorithms<\/a> can allow one developer to solve a problem in an hour that might take another developer several days to figure out.<\/p>\n Data structures<\/strong> fall into a similar category and work in conjunction with algorithms.There are several data structures all software developers should be familiar with including:<\/p>\n By having a good grasp of data structures and algorithms, you can easily and elegantly solve many difficult programming problems.<\/p>\n The ability to name your pieces of code appropriately is essential to being a good Software Engineer.<\/p>\n Your variables, functions and classes should be named such that anyone reading your code can grasp their meaning.<\/p>\n Choosing good names for your code<\/a> makes it easy for yourself or others to work with or on your code without wasting time and extra brainpower.<\/p>\n How readable a programmer\u2019s code is depends on the knowledge level of who\u2019s reading the code, as well as the capabilities of the programming language itself. <\/p>\n A few things hold true no matter what, though:<\/p>\n These are some principles for readable code<\/a>. Do keep in mind who will be reading it and how they\u2019ll perceive it based on their own skill background.<\/p>\n The ability to write quality code is one of the biggest differentiators between beginner and advanced developers. With high-quality code come fewer bugs<\/a> \u2013 making the lives of the development team, QA, and management easier at the same time.<\/p>\n But how do you achieve \u201cquality code\u201d?<\/p>\n Simplicity and testability are key. Don\u2019t make your code more complex than it needs to be, and split it up into independent modules as much as possible.<\/p>\n This also ensures it\u2019s easy to test. Testing your code and writing it in a way that facilitates testing is at the heart of quality code.<\/p>\n Sure, this can take more time up front \u2013 but the quality code you\u2019ve created as a result of your diligence will make for a more useful and valuable product.<\/p>\n It\u2019s easy for duplication to sneak into our code. To have the ability to prevent it means you\u2019ll be wasting less time, space, and maintenance effort.<\/p>\n The three types of code duplication<\/a> that can happen are data duplication, type duplication and algorithm duplication.<\/p>\n After you\u2019ve identified these in your code, you can use the technical skill of refactoring to eliminate them.<\/p>\n Great Software Engineers know how to write clean code.<\/p>\n They do it because it\u2019s necessary for improving time efficiency, collaborating on your code, debugging and maintenance. <\/p>\n Some principles you should follow to write clean code<\/a> are simplicity, consistency and clarity in naming, avoiding repetition, and readability.<\/p>\n Clean code is a delight to read and work with, and any Software Engineer worth his weight will aim to produce the cleanest code possible.<\/p>\n In software development, we are always trying to manage complexity.<\/p>\n Thinking in terms of objects helps us do that because it allows us to define and design a complicated system out of a bunch of interacting components, rather than trying to tackle the entire complexity as a whole.<\/p>\n The most popular languages and patterns you\u2019ll find in software development are still heavily, if not completely, influenced by object oriented design and analysis.<\/p>\n You should have a good understanding of what a class is, what the different types of inheritance are\u2014and when to use them\u2014as well as understanding terms like polymorphism and encapsulation.<\/p>\n A design pattern (e.g. the bridge pattern<\/a>) is a guideline for solving a problem that\u2019s recurring in your programs. This helps prevent issues that can come up with ad-hoc solutions.<\/p>\n Design patterns can be classified into creational patterns, structural patterns, and behavioral patterns.<\/p>\n Although they\u2019re useful in many instances, it\u2019s important for Software Engineers not to get obsessed with applying design patterns<\/a> whenever possible.<\/p>\n Sometimes leaving the code as-is<\/em> makes more sense \u2013 you need to use discernment.<\/p>\n It used to be that we developers would write a bunch of code and \u201cthrow it over the wall\u201d<\/strong> to a bunch of testers who would find all kinds of bugs in our code, we\u2019d fix the bugs, and that was that.<\/p>\n Not anymore.<\/p>\n With so many software projects adopting what is called an Agile process, (we\u2019ll discuss this more when we get to methodologies), software developers and testers are having to work much more closely together.<\/p>\n You should at least be familiar with some basic terms like:<\/p>\n A good developer\u2014and I\u2019m assuming you want to at least become a good developer\u2014tests their own code<\/a> before giving it to someone else.<\/p>\n If you really want to be considered a professional and not just a hack, this is non-negotiable<\/strong>.<\/p>\n You’re going to spend perhaps 90% of your time as a software developer figuring out why your code doesn\u2019t work<\/strong>.<\/p>\n Using the debugger is not all that the skill of debugging is about. Instead, a good Software Engineer or Developer will first apply their problem-solving brain to the issue.<\/p>\n He\u2019ll look for where the bug is coming from, theorize about possible causes, and test out solutions. <\/p>\n If you still can\u2019t get to the root of the issue, try doing away with parts of the program and focus on smaller pieces at a time. This way you can isolate where the bug is coming from.<\/p>\n Finally, if you\u2019ve fixed a bug, make sure you understand the solution and can reproduce it at will.<\/p>\n You\u2019ll have much code maintenance to do in your Software Engineering career \u2013 both of others\u2019, and your own.<\/p>\n Maintaining code well<\/a> means improving it every time you work on it:<\/p>\n Whether it be creating unit tests, clearing up names, making new methods, or refactoring whole code segments.<\/p>\n Your goal is to end up with code that\u2019s a lot more readable, so the next round of maintenance will be even easier for whoever is doing it.<\/p>\n Try to automate as much of this process as possible to save time and energy down the road. And only add (high-quality!) comments if absolutely necessary.<\/p>\n Source control at its most basic level allows you to keep a history of the changes made to different files in a software project.<\/p>\n It also allows for multiple developers to work on the same code at the same time and to merge those changes back together.<\/p>\n You should know how to use at least one source control system very well<\/strong>, and you should be familiar with most of the basic source control concepts.<\/p>\n If a programmer is working on a software together with others, he has to know how to manage different versions of its source code that his team might be working with.<\/p>\n Good source control<\/a> also mitigates the risk of the source code being accidentally deleted. But most importantly, it helps coordinate a team of developers working on the same software.<\/p>\n A source control system includes a repository to store the code, which individual developers can then \u201ccheck out\u201d a copy of onto their local drive.<\/p>\n After making changes, you then \u201ccheck-in\u201d the modified code to the repository. New versions can such be managed between multiple programmers. <\/p>\n The most popular source control systems today are Git, CVS, Subversion and Mercurial.<\/p>\n Git is the number one source control system for programmers today<\/a> \u2013 and more and more development teams are switching to it over time. It offers many features, but its basics are easy to learn.<\/p>\n Git\u2019s codebase is also constantly evolving, making it a future proof system for version control.<\/p>\n There\u2019s no reason why being proficient in Git shouldn\u2019t be something in every developer\u2019s toolbox.<\/p>\n Programmers should reuse code to speed up development and reduce costs, as well as make a better product for the user.<\/p>\n But they need to know when reusing code is feasible<\/a> \u2013 and <\/em>the code has to be of high quality in the first place<\/em>.<\/p>\n This calls for the developer to have advanced knowledge and skill. <\/p>\n If you\u2019re aware of the benefits and challenges, and follow the best practices of code reuse, it\u2019s a powerful tool for building software better and more efficiently.<\/p>\n Today, the most common software development methodologies are waterfall development and Agile development<\/a>.<\/p>\n Learn how to use the principles of Software Architecture<\/a> to properly design software, and be able to understand and communicate its workings as a whole.<\/p>\n These include the five SOLID principles (Single Responsibility Principle, Open-Closed Principle, Liskov Substitution Principle, Interface Segregation Principle and Dependency Inversion Principle), economic principles (Opportunity Cost Principle, Cost of Delay Principle), as well as the \u201cLeast\u201d, or minimalist principles (Principle of Least Astonishment and Principle of Least Effort).<\/p>\n If you respect Software Architecture principles, your development projects will be more coherent, executed more smoothly, and have a higher chance of success.<\/p>\n A developer should be able to engineer a detailed plan for what tasks lie ahead and how exactly they should be completed \u2013 before he ever starts to dive into development.<\/p>\n This software implementation plan<\/a> should be extensive, detailed, precise and well-structured. You can set up the plan as a checklist with subheadings for the different parts of the task (e.g. Back End, Front End, etc.)<\/p>\n Programmers can use this approach to bring clarity and direction to the development process.<\/p>\n Being able to type fast is one ingredient to improving coding speed<\/a>. But it\u2019s not the only one. The most important thing is to become a subject matter expert.<\/p>\n By expanding your knowledge, you\u2019ll be able to see the big picture. You can then lay out your tasks with precision \u2013 which helps you optimize your code creation.<\/p>\n Use time management to properly plan and execute your workflow.<\/p>\n Finally, if you focus on code quality\/cleanliness, you\u2019ll be able to read, debug, and change it much faster if you need to.<\/p>\n Today, most software development projects have some kind of automated build and deployment system.<\/p>\n There are several different software applications out there that help teams to automate both of these tasks, which used to be manual and, for some teams, still are.<\/p>\n You know how you write that code and check it into a source control system?<\/p>\n You need some way to make sure that code actually works after you check it in<\/strong>.<\/p>\n That\u2019s where a build system comes in.<\/em><\/p>\n At least, a build system is going to compile all the code and make sure there are no compilation errors.<\/p>\n A sophisticated build system may also run unit tests or user tests, run code quality checks, and provide some reporting<\/strong> on the current state of the code base.<\/p>\n A deployment system<\/strong> will be responsible for deploying the code either to a production machine or perhaps to some kind of a test environment.<\/p>\n Often, the actual responsibilities for creating and maintaining a build and deployment system will belong to a quickly growing field called DevOps (short for developer operations).<\/p>\n But, that doesn\u2019t excuse you from understanding at least the basics of how this process works.<\/p>\n Some best practices for software deployment<\/a> Software Engineers should know about are:<\/p>\n First test your application in a virtual environment. Then test it with power users \u2013 you might want to choose members of your company for this. <\/p>\n There\u2019s different methods for deployment, e.g. rolling out new software only to few users, deploying it in phases, releasing it on one server at a time, or creating two environments, one live and one waiting to go live.<\/p>\n Which method you\u2019ll choose for deploying your software depends on the scope of your project, and how much time and resources you have available.<\/p>\n In object-oriented programming languages, an interface<\/a> can force properties on a number of classes. It declares which actions are allowed by these classes.<\/p>\n If a programmer knows how to do it, using interfaces will make his programs them easier to test, expand on and maintain.<\/p>\n Dynamic Programming helps optimize solutions that need recurring work to be done.<\/p>\n You can apply DP when a problem has an optimal substructure \u2013 i.e. the best solution to its sub-problems is the best solution for the main problem as well \u2013 AND it needs to have overlapping subproblems.<\/p>\n This means you\u2019ll be solving the same problem multiple times. <\/p>\n Use a solution structure as your guide to solving problems using Dynamic Programming<\/a>, and you\u2019ll soon become confident wielding DP as a powerful tool.<\/p>\n Why would an experienced Software Engineer bother with using low-code tools to develop (parts of) their software?<\/p>\n Saved time is the biggest benefit of low-code development vs traditional coding<\/a>. Low-code platforms work like page builders for websites, which allow you to insert pre-coded blocks, instead of having to write each line of every piece manually.<\/p>\n This can even lead to a better product \u2013 because your team can focus more on the customer\u2019s needs when it isn\u2019t bogged down by repetitive coding tasks.<\/p>\n Don\u2019t scoff at the idea of low-code development. Rather think of it as an easily applicable skill you can use to your advantage.<\/p>\n By visualizing code in a flowchart<\/a> before writing it, a programmer can better understand the challenges of a development project \u2013 and more effectively design the right solutions.<\/p>\n A software flowchart includes a starting point, multiple processes (algorithms), inputs and outputs, decision points, connectors, documents, and manual inputs.<\/p>\n Not only does this make coding easier, it also helps with communicating how the software will work, analyzing functionality, identifying bugs, as well as documentation and maintenance.<\/p>\n Knowing how to create and work with these charts is a great skill to have for any professional programmer.<\/p>\n Static methods are useful for declaring a global constant or creating an object in OOP \u2013 which is why the skill of creating them is useful to programmers.<\/p>\n A static method is not part of a class, and can be called from anywhere.<\/p>\n This does go against object oriented design \u2013 so apart from the cases mentioned, you shouldn\u2019t be using static methods<\/a>:<\/p>\n They can\u2019t be overridden, are hard to test, and increase complexity.<\/p>\n Nowadays customers expect frequent real-time interaction and immediate influence on the development process.<\/p>\n As a programmer, you need to have the flexibility to cater to these demands.<\/p>\n Customer-centric programming<\/a> requires meticulous planning and prototyping, excellent communication, and incorporating feedback in a timely manner. <\/p>\n The benefit for you is that this close connection to the customer forges a loyal bond to your brand.<\/p>\n Tech writers and customers will be made happy by Software Engineers creating helpful end-user guides with visual elements<\/a>. Making these guides valuable starts with choosing a proper title and building out the table of contents.<\/p>\n Every section of the guide should be created like a user story. Use screenshots wherever you can to make everything less dry and more easy to follow.<\/p>\n Developers who can write high-quality end-user guides like this will be loved by project managers and customers alike.<\/p>\n This skill sounds basic. And backing up your code doesn\u2019t have to be complicated. But you do need a strategy, and you need to execute it, or you\u2019re risking some bad outcomes.<\/p>\n Here\u2019s a simple backup strategy for software developers<\/a>:<\/p>\n Programmers need to know the European GDPR (General Data Protection Regulation) and know how to build features compliant with these laws.<\/p>\n Examples of these features are a \u201ccache delete\u201d method, the ability for users to export their data, notifying third-party services of data deletion, options for personalization, and functionality for users to give their consent.<\/p>\n A developer who knows GDPR<\/a> and its intricacies will be confident working with European customers and will greatly reduce the risk of producing violations.<\/p>\n Evaluating the quality of your solutions against those of others in coding competitions like HackerRank is a good way to measure your programming skills<\/a>.<\/p>\n Also seek out feedback from others, especially those ahead of you.<\/p>\n Measure your progression: For short-term improvement, track one skill. For medium to long term, track multiple.<\/p>\n Reading thick programming books cover to cover might give you some new knowledge \u2013 but it\u2019s not the most efficient way to upgrade your abilities.<\/p>\n2. Mastering a Development Platform<\/h3>\n
3. A Framework or Stack<\/h3>\n
4. Basic Database Knowledge<\/h3>\n
\n
5. Programming logic<\/h3>\n
6. Algorithms & Data Structures<\/h3>\n
\n
7. Naming<\/h3>\n
8. Readable code<\/h3>\n
\n
9. Writing quality code = reducing bugs<\/h3>\n
10. Avoiding code duplication<\/h3>\n
11. Clean code principles<\/h3>\n
12. Understanding Object-Oriented Design<\/h3>\n
13. Design patterns<\/h3>\n
14. Testing<\/h3>\n
\n
15. Debugging<\/h3>\n
\n
16. Code maintenance<\/h3>\n
17. Source control<\/h3>\n
Proficiency in Git<\/h4>\n
18. Code Reuse<\/h3>\n
19. Methodologies<\/h3>\n
20. Software Architecture<\/h3>\n
21. Software Implementation Plans<\/h3>\n
22. High coding speed<\/h3>\n
23. Build & Deployment<\/h3>\n
Deployment systems<\/h4>\n
Best practices for deployment<\/h4>\n
24. Understanding Interfaces<\/h3>\n
25. Dynamic Programming<\/h3>\n
26. Low-Code Development<\/h3>\n
27. Flowcharts<\/h3>\n
28. Creating Static Methods<\/h3>\n
29. Customer-Centric Programming<\/h3>\n
30. Creating End-User Guides<\/h3>\n
31. Data Backup Strategy<\/h3>\n
\n
32. GDPR Knowledge<\/h3>\n
How to measure your programming ability<\/h2>\n
How to improve your technical skills<\/h2>\n