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Software is at the base of all the advancements we see in our lives. Software development technologies have witnessed a huge transformation over the last few years. Be it Amazon’s drone deliveries or Snapshot with augmented reality offerings, the software makes the world go round. Enterprises have adopted almost all the emerging technologies in their software development, and Artificial intelligence is no exception. Impact of artificial intelligence on software development changes how enterprises run business and make software smarter.
A survey by Forrester revealed that development and delivery teams are confident that AI in Software development will improve development, agile test automation, automation-testing software as well as the way RPA bots functions with the support of the software. AI tools aim to make software development more reliable, faster and easier.
What will happen as Artificial Intelligence works its way into your development cycle? How will software development change? How will you leverage AI to verify ever-enhancing code suites? Let us find answers for all these questions:
Role of AI in Software Development
AI will impact the way we develop the application and we can expect a better app developed under the existing environment. Understanding AI will shape the future of software development; most businesses today are showing interest in AI. 80% of companies smartly investing in AI. Nearly 47% of digitally mature enterprises have defined AI strategy. It is predicted that by 2021 AI tools alone will create $2.9 trillion in business value.
If you want to adopt this strategy, then you should understand the role of AI in software development and analyze what has changed. Here are the functionalities that AI can offer into software development to deliver extremely customized products or services for your customers.
Areas where AI impacts Software Development
AI plays a key role in the design, code generation and testing of software. Let us discuss each area in detail:
Requirement Gathering
Being a conceptual phase of SDLC, the requirement gathering requires maximum human intervention. Artificial intelligence offers a broad range of techniques/tools like Google ML Kit, and Infosys Nia to automate certain processes to minimize human intervention to some extent. This phase includes plenty of emphasis on detecting loopholes early before moving to design. A technique of AI called Natural language processing will make machines understand the user’s requirements in natural language and automatically derive high-level of software models. Of course, there are some issues with this approach including difficulties in balancing the developed systems. However, it remains as one of today’s hot research topics.
Software Design
Planning projects and designing it needs specialized learning and experience to propose a definitive solution. Settling on a correct design for each stage is an error-prone task for designers. Retracts and forward investigating plan forces dynamic changes to the design until the client reaches the desired solution. Automating some complex procedures with AI tools can enable the most capable methods to design the projects. For example, using AIDA (Artificial Intelligence Design Assistant), designers can understand the needs as well as the desires of the client and use that knowledge to design the appropriate project. AIDA is a website building platform that examines various combinations of software design and presents the appropriate customized design as per the client’s needs.
Automatic Code Generation
Taking a business idea and writing code for the huge project is still time-consuming and labor-intensive. To confront the time and money concerns, experts have approached a solution that writes code before starting development. However, the approach is not good with uncertainties like what target code aims at doing as collecting these details takes much time like writing code from scratch. An intelligence programming assistance with AI will reduce the load by a certain extent.
Imagine that if you explain the project idea in your natural language and your system would understand it and convert it into executable code. Though it seems like science fiction, software development artificial intelligence can flip the story! It will be possible through natural language processing and AI tools.
AI in Testing Services
Software testing is a crucial phase in software development, which ensures the quality of the product. If certain software testing is repeated whenever source code is changed and repeating the same tests can be time-consuming and costly. The capture here is AI in software testing comes to the rescue once again.
There is a wide range of tools that employ AI for creating test cases and performs regression testing. These AI tools can automate the testing for you and further ensure error-free testing. Appvance, Functionize, and Testim.io are a few examples of AI and machine learning-based testing platform.
Deployment Control
Machine learning AI technologies also had some impacts on software deployment, like an increase in the efficiency of deployment control activities. In the software development paradigm, the deployment phase is the stage where developers often upgrade the programs or apps to newer versions.
If developers fail to execute a process correctly during upgradation, there will be a high risk in executing the software. AI can prevent developers from such vulnerabilities during upgradation and reduce the risk of failure in deployment. Another impact of artificial intelligence is, it enables to analyze the deployment process with machine learning algorithms.
Benefits of AI in Software Development
By understanding the impact of artificial intelligence and its possibility of future enhancement in software development, you can realize the results of deploying AI technology. Here are the promising results due to the impact of artificial intelligence in software development:
Enhanced Data Security:
Software security is a crucial property that you can’t overlook during development. The system generally collects data from network sensors and software installed on the customer end. AI enables you to investigate the data using machine learning to distinguish irregularities from normal behaviors. Further Software Development Companies adopting AI in their development process can also avoid the delayed warning, false notifications, and alerts.
Bugs & error identification becomes easier:
By integrating with AI tools, coding becomes better and enhanced. Developers and testers don’t need to struggle with examining the executable files loaded with bugs & errors. It is easier for them to find bugs instantly and correct them.
Build better software with strategic decision-making:
Diego Lo Giudice, Forrester analyst says,
“Software developers will be able to build better software faster, using AI technologies such as advanced machine learning (ML), deep learning, natural language processing, and business rules”.
Machine learning solutions are empowered with the ability to learn from past development projects as well as analyzing the performance of existing projects. AI in software development not only makes development easy but also results in better applications.
Improvement in accuracy of estimates:
AI offers a solution to estimate software that involves analyzing historical data from earlier projects of the enterprise to find correlations and statistics. It employs predictive analytics as well as business rules to offer accurate estimates of cost, time and effort.
Overall, Artificial intelligence will have a significant impact on the design as well as the creation of software. The software development companies need to perceive the impact of artificial intelligence and the potential benefits it will bring, not only in the way of building software but also in the nature of the software itself. Undeniably, AI in software development will prove to be a game-changer!
