AI Is Set to Transform How We Develop Software In 2019
With 80% of enterprises smartly investing in Artificial Intelligence (AI), the technology is transforming every possible business function, and software development is no exception.
It is projected that AI-enabled tools alone will generate $2.9 trillion in business value by 2021. Traditionally, software development required developers to specify, in advance, exactly what they wanted the system to do and then manually develop all the said features. However, in the AI age, all developers need to do is feed data into machine learning algorithms; the model will automatically deduce what features and patterns are important – without needing a human developer to explicitly carry out coding. In the coming year, AI is not only poised to accelerate the traditional software development lifecycle; rather, it is expected to present a completely new paradigm in software development.
Let’s see how AI is set to transform how we develop software in 2019:
- Improved time-to-market: Over time, software systems have become incredibly complex, requiring multiple dependencies and integration as well as layers upon layers of functionality and interfaces. All these components have, until now, been manually managed and updated by humans, leading to discrepancies and unresolvable bugs. In contrast, AI models can extrapolate important features and patterns in data and reduce the time taken to develop high-quality, complex software – thus improving time-to-market.
- Rapid prototyping: The process of turning business requirements into technology products has typically been long and cumbersome. Getting the idea to a prototype level has been another daunting step which needs massive budgets and resources. 2019 will see AI shortening this process to a few lines of code; by using pre-defined natural language or visual interfaces, AI will speed up the prototyping process and enable technical domain experts to quickly develop quality solutions of tomorrow.
- Intelligent programming assistants: In software development, a lot of time is spent on going through important documentation and debugging code. Enter intelligent programming assistants, and the debugging process can be accelerated. In 2019, smart AI assistants will become extremely popular; through deep learning, they will offer just-in-time support and provide recommendations including relevant documentation, best practices, and code examples to developers, and help them speed up the development process.
- Automatic error handling. AI algorithms can also learn from experience to identify common errors automatically during the development phase. AI’s deep learning algorithm can help flag known errors and learn how to fix each of them – with enhanced accuracy. It can do this by analyzing system logs and proactively identifying and rectifying errors even after the software solution has been deployed. In the coming year, it would also be possible for software to change dynamically in response to errors without human intervention.
- Accurate estimates: Software development projects are notoriously known to miss timelines and go over budget. Reliable estimation requires developers to learn from past situations regarding delivery times, and common pitfalls. AI models can train on data from past projects including data about features, bugs, average development time, resource allocation, testing times, user reviews etc. and predict effort and budget far more accurately. By learning about individual habits, team performance, and possible obstacles, AI can create personalized work schedules that take into account the work patterns of each member, for maximum efficiency.
- Automatic code refactoring. Clean code is critical in software development as it can make or break a project. Contrary to the belief that programmers spend a lot of time writing code, they actually spend a lot of time reading code, documenting it, debugging it and figuring out what to do next. AI can analyze code and automatically optimize it for interpretability and performance; by mutating a piece of software hundreds of times, it can determine which of those versions are better, and then mutate those, until the end result is the best possible version of the code.
- Quality development: A substantial portion of development time is often spent debating which features to prioritize and which to eliminate. An AI solution that is trained on past development projects can assess the actual performance of existing features and help both business leaders and development teams identify efforts that would maximize revenue and minimize risk. By analyzing customer reviews and product features, AI can create a list best features to have and improve the quality and success rate of the software under development.
- Automated testing: Another major impact AI will have on software development in 2019 is in the area of automated testing and bug detection. Traditional testing involved creating a comprehensive list of most probable test cases, as well as some extreme ones that could affect the performance of the program. AI can automate the testing process by looking at past logs and automatically generating a list of test cases. What’s more, it can also predict outcomes of testing without performing the actual tests and only focus on cases that have a higher likelihood.
Enhance software development accuracy
In the AI era, programming is no longer about developing code and wondering if the features will meet the said requirements. It is more about choosing the right data to train AI algorithms which will satisfy needs to the T – all without human intervention. The coming year will see the human-driven era of software development, which involved writing rule-based code to solve deterministic problems using logic, paving the way to AI that will forever change the way we develop software. With the ability to improve time-to-market, increase prototyping speed and efficiency, automatically handle error and refactor code, accurately estimate budget and time, and automate testing, AI has massive potential for speeding up and improving the accuracy of the software development process in 2019.