Will Software Development Be Automated in the Future?

The Basics of Software Development

Let’s start with the basics: software development is the process of creating software. Software is written by software developers and follows a process called the software development lifecycle, which you can read more about here.

As you know, the software industry is fast-paced and relies on staying on the cutting edge to remain competitive and profitable. It’s no secret then that the topic of automation is a hot-button issue in the industry. But should developers be concerned about being replaced by automation?

The short answer is no – software developers (and even machine learning engineers!) shouldn’t worry about programming jobs being replaced by automation. We’ve still got a long way to go from Watson beating Ken Jennings and Brad Rutter on Jeopardy to it replacing developers outright.

That isn’t to say that automation tools aren’t useful for developing software! Together, let’s look at how a developer’s job has changed and how automation can be used as a tool to help developers, not replace them.

How Software Development Has Evolved

To understand the impacts of automation on developer jobs, we need to understand how software developers solve problems and some of the organizational approaches commonly used in the industry.

One of the more traditional approaches to the software development process is the Waterfall methodology. Think of Waterfall methodology as a linear, sequential approach to a problem or project. Following this style of methodology requires extremely detailed documentation.

While the Waterfall methodology’s linear path can be a great strength for seeing the “big picture” of a software project, it can also be its biggest weakness. Projects with changing requirements and dependencies may benefit more from an Agile approach.

One of the newer trends in software development is the Agile methodology. Popularized by The Manifesto for Agile Software Development in 2001, the Agile methodology focuses on the continual improvement of a feature or product. Using shorter periods of time, the Agile approach has let development teams work together in a collaborative, flexible environment.

The Agile approach can be thought of as incremental. A team is constantly improving and updating features and requirements instead of waiting for the project’s completion to reassess and change its approach.

The jump from the Waterfall method to Agile is a great example of how software engineering has changed over the last 30 years. Here, we see a shift towards a more dynamic system that developers exist within.

Developers working in an Agile environment can be more flexible in their approach to problems. Additionally, a focus on an Agile environment puts a greater emphasis on cross-functional teams and higher-level problem-solving. Here, developers are encouraged to use their technical and critical thinking skills in tandem as the project evolves.

Recent Software Development Trends

In recent years, the job market for developers has exploded. According to the US Bureau of Labor Statistics, the average growth rate of all occupations sits at 5%. Software developers knock this statistic out of the park with a 25% growth rate projected for 2021-2031! But what does this explosive amount of opportunities mean for the industry?

As the field changes, there is a rise in different branches of software engineering, and some developers are even taking on tasks performed by data scientists and project managers. How does automation fit into the fluid role of a modern developer?

Current Automation Tools

Could a computer replace developer jobs? Not at the moment, no. But that doesn’t mean that a developer today is completely removed from automation.

Modern IDEs, or integrated development environments, contain many tools that utilize the principles of machine learning to help write code. Machine learning is a subset of Artificial Intelligence that lets a computer “solve problems” by inputting a variety of scenarios and solutions.

So how does machine learning help someone write code today?

Let’s start with some of the biggest help an IDE provides – autocomplete! Using a variety of constraints set by a programming language, an IDE can help a user autocomplete lines of code by auto-populating variable names, fixing small syntax errors, and assisting with semantic searching.

As the program better understands what a human user is trying to implement, the easier tasks can become for the users. Though computers aren’t quite the best at programming themselves yet: most readily available AI-based tools, like Copilot and GPT-3, are prone to errors and bugs just like human developers.

There are many other things that we can trust AI to do today, from helping you find what show you’d like to watch next to being able to help you park your car. It stands to reason that over the next few decades, we’ll be seeing plenty of ways we can use AI and machine learning to help make programmers’ lives easier.

What Can We Automate in Software Development?

Based on the state of current automation tools and artificial intelligence as a field, what can we expect to see next?

Something that artificial intelligence can do well is doing tasks at scale. Simply put, if you asked a computer to print (“Hello World!”) 1,000 times, it could do so in a fraction of a second. Asking someone to do it manually? The computer clearly wins.

We can apply that to writing code: AI can help users auto-complete lines and even smaller functions within their code. This lets the program take over repetitive tasks while a user focuses on the how and why of complex tasks.

Another time-consuming task for a software developer is debugging. Having to trawl through thousands of lines of code can derail sprint goals and even delay a project’s launch. Automating this process lets AI comb through and find what it suspects is the problem.

The goal of introducing further automation tools to a developer’s toolbox is not to replace them. Just like humans, these tools are not perfect and still require code reviews and further scrutiny to ensure that they produce code that is functional. Rather, they allow developers to work more efficiently and eliminate redundancies in their workdays.

Will Automation Replace Developers?

Do these current automation tools mean that automation is poised to replace humans? No! Automating part of the software development process doesn’t mean we’ll completely replace developers, but what a developer spends most of their time on may change.

Humans are good at solving unique and complex problems. Automation can help provide the foundation for the code to solve them! Turning their focus to higher-order tasks means that software engineers can spend coding time getting to the root of a problem.

Though another important trend to notice that automation will affect is the soft skills a developer needs to succeed in the industry. Humans are social beings, and being able to better communicate with their peers makes for a more well-rounded and efficient development team!

All in all, the goal of increasing the amount of automation in the near future is to expand what humans can do, not replace them with computers. Think of editing services available to writers. While spellcheck doesn’t replace the technical skills that good writers should have, it does help you decide between “affect” and “effect” and correct minor misspellings.

Is There a Future for Programming?

But what does the future of programming look like if artificial intelligence and machine learning are involved?

Software is no stranger to constantly evolving technical knowledge. Many programming jobs today involve writing code in multiple languages. It’s important for developers to know how to code in multiple languages to keep up with demand and the ever-changing market.

Just like developers are expected to move with the larger trends of languages, AI tools can be approached in the same way. The help they provide in tackling data management and time-consuming tasks makes these tools extremely useful. As these new technologies become more mainstream, we will see a wider adoption within the industry.

Another large fact of machine learning is how AI tools develop their neural networks. As they constantly evolve and update, these machine-learning resources need to have a set of data to pull from and learn from. In addition, as they get more complex, artificial intelligence will need to be trained to be more responsive to natural language inputs. This helps bridge the gap with users who can utilize these tools in their day-to-day jobs as well!

When you start a new job, it’s natural to have someone to ask questions to and even take a look over your work when you run into bugs and issues. Think of current programs as new hires: we still need to make sure they’re producing good code that’s usable by catching errors and editing any machine-produced code.

And while artificial intelligence may lead to a statistical downward trend in how many new (programmer-specific) positions will be available over the next ten years, this has to be understood in the context of the explosion of tech positions that have been created in the last decade.

According to the US Bureau of Labor Statistics, the average growth rate of all occupations sits at 5%. Software developers knock this statistic out of the park with a 25% growth rate projected for 2021-2031! Keep in mind this statistic doesn’t take into account analysis, sys admin, QA testers, UI/UX designers, or even machine learning engineers.

Automating development (somewhat paradoxically) will increase the number of engineers and developers needed to help develop and train them. It could also lead to a trend of more developers in project manager positions.

About Geneca

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We want to provide your company with a step-by-step guide to developing your custom software, even if we only have human programmers for now. Contact Geneca today for a consultation with the right member of the Geneca family. Together, we’ll work to bring your idea to life!

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