Artificial Intelligence is increasingly prominent in business strategies, including software development.
An IDC survey of more than 2,000 IT and line of business (LoB) decision-makers confirms that the adoption of artificial intelligence (AI) is growing worldwide.
Ever since artificial intelligence has started to dominate the market, the software development industry is at the forefront of huge change. It will not only change the way programmers code but also change how they have to think about each aspect they put on the web or mobile apps. Artificial Intelligence can ease the programmers’ life to a large extent, but that does not mean programmers won’t need to code at all. This technology will make programming more powerful and natural. Developers will be able to think and act out of the box with the help of AI.
According to software development experts, the software development life cycle(SDLC) has enormous benefits with AI. It will change the practices involving software delivery estimations, coding assistance, testing, bring DevOps, and converting work culture into agility and more. Artificial intelligence will change custom software development into a slightly different experience than the current situation. It helps developers automate and assist coding to some extent where they need not think ground-level technicalities and focus more on developing custom requirements.
Today we are discussing a more detailed version of how custom software development can be affected by artificial intelligence.
AI: Programming & Code Assistance
Programming is an evolving skill. Companies have to excel at what they do and yet be learning new technologies every other day. It may become difficult to remember and write intricate lines of code for different projects and various programming languages. Artificial intelligence will aid in empowering their skills and enhance their speed to provide application development services to the clients. With the use of AI, many development efforts will be reduced to an IntelliCode (just like we had in Microsoft word IntelliSense).
It will complete the code lines from the collection of intelligence. This auto-completion of coding will not only save time but also save developers from single issues since these suggestions will be quite insightful. Developers will come to know better and proper ideas from the suggestions and won’t go into the troubles at the time of short deadlines. These intelligent tools learn from the code developer types; they predict the code compilation based on the basic intent without specific knowledge of the domain. There are also developments in a process that learn from the GitHub repositories. Intelligence will be driven from statistical patterns of coding and programming intricacies that will help in faster software development.
One of the most critical phases of software development is testing. Whether it is a manual or automated testing, it has to be done right to avoid last-minute failures. Though we know that automated testing is doing rounds over the years in software companies and experts believe that automated testing has had success over the past years, there is still a scope of improvement in that direction.
Artificial intelligence can generate test cases of its own without help from the software quality analysts. It saves most of the time that analysts spend on writing test cases for automated testing tools. These AI-powered testing can bring a noticeable improvement and change in software quality as well as delivery speed. Intelligence identifies the root cause of defects, proves to be more robust in identifying the elements of the user interface.
Deployment & Project Management (Artificial Intelligence speeds up the delivery)
Successful delivery is not possible without proper project management and precise prediction of a workflow. Artificial intelligence can help in both reinventing the deployment process and project management. It uses advanced analytics to extract the data and calculate future risks, technical tasks, resource allocations, and more. Based on this, predictive analytics of setting timelines become effortless and accurate. This advanced information about the project workflow also helps in taking precautionary measures for final deployment.
Though deployment is the last phase for software development, it has to be performed with most care because it can ruin the impression of an organization or a developer if something goes wrong. The final version of the software has to work as specified with thorough testing and trials under different environments and use cases. Artificial intelligence has started showing its influence in delivering the right software builds by implementing a successful deployment. There are AI-powered tools to predict the failures ahead of time. These tools are capable of knowing the exact root cause and performing analysis based on the previous performances of a software.
It saves a lot of money and time when it comes to big-budget real-time deployments like eCommerce applications since these apps have to be restored and recovered. There are also chances of rolling back the functionalities for the time being. All these things are taken care of by AI-based tools using their machine learning algorithms.
AI Tools for Improving Software Development Process
Artificial intelligence has domain wise tools to offer for improving software development. There are multiple AI-based tools used for different purposes, such as code assistance, bug fixing, testing, deployment, and other SDLC related activities.
Google ML Kit, Tensorflow, MxNet, H2O are the famous examples of AI-powered software tools for developing mobile apps and development in AI-based technologies like Python and other development facilitations.
For example, code assistance tools can help in auto-correcting the syntax errors and semantic errors based on the code intent the tool might have learned. It helps in detecting errors in the first place before the testing phase. Also, for large scale projects, bug fixing tools are the most proved to be most useful. For example, a large-scale application like Netflix gets hundreds of updates on a day-to-day basis. In such cases, AI-based bug fixes help a lot, detecting thousands of lines of code so that the prompt rectification can take place.
Artificial intelligence can help software companies in estimating project deliveries and bringing agility to the environment. Despite software companies having years of experience evaluating a mobile /web app project, AI-based tools are believed to be a more robust solution. They use years of data to predict the precise complexities, client requirements, and possible setbacks in progress to calculate the delivery estimation and needed precautionary measures. All these aspects help software companies better predict the milestones, resulting in better client communication and satisfaction.
Testing tools like Eggplant, TestComplete tools, Saucelabs have already started to integrate AI features. After all, automating the testing process speeds up the software’s overall time to be delivered ready and provides more detailed and quick insights to developers about the technical issues and fixing them.
How Artificial Intelligence can Improve the Software Development Process
Artificial Intelligence can ease the programmers’ life to a large extent, but that does not mean programmers won’t need to code at all. This technology will make programming more powerful and natural. Developers will be able to think and act out of the box with the help of AI. WArtificial Intelligence can ease the programmers’ life to a large extent, but that does not mean programmers won’t need to code at all. This technology will make programming more powerful and natural. Developers will be able to think and act out of the box with the help of AI. Artificial Intelligence can ease the programmers’ life to a large extent, but that does not mean programmers won’t need to code at all. This technology will make programming more powerful and natural. Developers will be able to think and act out of the box with the help of AI. Successful delivery is not possible without proper project management and precise prediction of a workflow. Artificial intelligence can help in both reinventing the deployment process and project management.