How AI Impact on Software Development?

The AI industry is never ending industry for the developers who think out of the box. The technology helps the developers to create safer software unlike the software created in a traditional environment.

It’s been fascinating to see how artificial intelligence (AI) has re-emerged after long periods of failing to meet expectations. AI is creating a revolution faster than we could ever imagine, Helped by the power of cloud computing and big data. But how will AI impact the development of the software that underlies many of these new services? How will the job of a developer or tester change?

Will we see the transition in Google’s software becoming system that “automatically writes itself”?

The chances are 50% that the machines will surpass the human jobs in near 45 years, according to a survey of more than 350 artificial intelligence researchers. New Scientist also estimates that machines will be better than us at :

·      Translating languages (by 2024)

·      Writing essays (by 2026)

·      Driving trucks (by 2027)

·      Writing a bestseller book (by 2049)

·      Automating all human jobs (next 120 years)

For many businesses "AI's Bot" is a reality just then a method. Robotics and Artificial Intelligence are getting evolved more and more and will be taking over the world in upcoming years and to make this true, the experts are striving days and nights.

Mobile Apps have been already successful in changing the lives of people leaving a mark on technological changes. Internet of things has made their place in the homes. However, the next technology will be AI making a mark on the people's lives and developer’s jobs.

Al is already started making its impression by clashing with all the aspects of the software development lifecycles, from the readiness of the software to develop, test, deploy and maintain. Currently, we can see two main impacts of AI on software development:

·      AI helping developers and testers create better software

·      Developers using AI to create better functionality that is more responsive to users

AI Helping developers:

Quality Assurance(QA) is the main key point for helping developers through Artificial Intelligence(AI). The first footprint AI made in Developers job is due to improved tools to help them code better. They are also making an impression on experts to test and make the quality assurance more effective. The software quality has been already improved through this, as using machine learning to test software is the natural next step after automation testing. Testers using bots too to find bugs.

To help testers find flaws and bugs in their software, AI has an emerging area which includes testing tools that can also help them fix code automatically after finding the bug. As an example, last year the Defense Advanced Research Projects Agency (DARPA) held a major event to develop systems that can automatically and autonomously "detect, evaluate and patch software vulnerabilities" to improve cyber security. AI can also solve bugs by having expert systems suggest possible changes in code and how to apply them to a software development life cycle (SDLC). Involving AI in any of the software models can enable stronger text recognition. Developers will be able to get the stronger code out of this sharp recognition.

Becoming the better programmers faster, the developers will also be able to learn different languages if they want to move their center of attention to different language. Just as we’re seeing AI entering into firms via the tools that we all use every day (think of Sales force embedding AI into its CRM platform or AI now appearing in Microsoft Word’s Editor), similar tools will impact the developer community.

One-trick AI

“There is accumulating evidence that machines can overpower human intelligence in complex, though specific tasks,” says Eleni Vasilaki at the University of Sheffield in the UK. But there is little evidence that AI with human-like versatility will appear any time soon, she says.

The predictions are to use machine learning in assuming the failure rates for the agile sprints. Deciding, what the developers should build or develop is difficult and so we can expect the emergence of AI helping the developers to decide. For example, what parts of an application should the development team focus on?

Developers Using AI To Build Effective Applications :

Our technological devices have experienced the new generation of application who can hear, sense, talk and think on behalf of us. To generate more revenue the businesses would take in this type of applications so vendors can grow. Point solutions and platforms are going to be a big hit in the next upcoming years. We have already experienced this technology to some extent through Siri and Alexa. Upgradation of these steps is going to make these technologies even smarter for customers.

The need to provide highly customized and personalized services for customers has also increased the need of functionality to feed AI into an enterprise's software. There are already countless examples of AI improving applications and creating new functionalities, whether it is the predictive text on your smart phone or the bots used to write simple news articles.

The weaker version of AI has been in the industry for quite some time, but it requires developer interference to come to reality. AI is the terminology to enable applications to learn autonomously and react to scenarios.

Well, the weak AI was weak because it used programming. The newer version of it would be totally different. The stronger version would be taking learning and smarter implementations into consideration. The deep learning and the smarter implementation through this diverse technology is being more excited for the developers.

Conclusion:

New Outlook:

Machine Learning and AI are going to teach the developers the new technologies about the field they have been most passionate about. Developing this mindset is a challenge and a gift. Traditional development model expects us to move in a linear way because of the algorithms we know. Machine learning algorithms don’t allow you to think in traditional ways. AI makes the technological change mark by making the developers job easy.