Artificial Intelligence and Machine Learning have disrupted every industry including retail, manufacturing, transportation and even customer support. Software development is no exception where machine learning and AI can enhance the process of traditional software development cycle.
Research report as of September 2017 by MarketandMarkets predicts the Machine Learning market will grow to $8.81 billion by 2022.
To give you a brief overview of Machine Learning, it is an application of Artificial Intelligence that provides systems the ability to automatically improve and learn from the experiences without being programmed. The core purpose of machine learning is to allow computers learn automatically without the interference of humans.
As a software developer or computer programmer, you have to specify every detail to let the system know what to do. Thereafter, you customize the features of your technology accordingly. Developing an app or software integrated with machine learning would make a significant difference and help you to make a unique name as a software development company.
In this article, we will look into how machine learning in software development can benefit developers to write flawless code, deploy the upgradation and identify bugs
Let’s get started.
Data Security becomes Easier
The amount of data being transferred from different networks makes it difficult for cybersecurity experts to monitor every activity. The consequences are far more dangerous than ever because threats and breaches go unnoticed, but the time has passed out to take specific actions. In fact, the solution is in the machine learning in order to avoid false notifications, delayed warning, and alerts.
For example, Finnish Security vendor F-secure has already adopted this model with its rapid detection service. The main objective is to lessen the time it takes any organization to notice a breach. The system collects data from the combination of software installed in customer terminals and network sensors. The data is then investigated through machine learning to differentiate normal behaviors and irregularities.
Strategic Decision Making and Rapid Prototyping
Normally, developers have to go through a long and hefty process of what features to include in a product and which ones to cut. However, machine learning AI solution trained on business factors and past development projects can analyze the performance of existing applications. It will help both teams of engineers and business leaders to find solutions in order to maximize the impact and cut the risk.
Normally, the transformation of business requirements into technology requires months or years of planning. However, the process can be lessened with the help of machine learning by allowing fewer technical domain experts to develop technologies using visual interfaces or natural language. This will help software development companies to speed up the process, deliver the product in lesser time, and increase revenue within a short span.
Help in Identifying Bugs and Errors
Coding gets better and improved with the advancement in Artificial Intelligence. It allows developers to spot bugs instantly and fix them. They don’t need to put their brains out on executable files filled with bugs and errors. Developers can also incorporate Machine Learning algorithms in testing the software, resulting in improving the quality of the tested program.
With the evolution and advancement in AI, testers and developers are looking forward to integrating AI-powered tools to identify flaws and fix the code errors automatically. Now imagine how much time you can save as a developer in delivering the project without spending much of your time in fixing and identifying bugs and errors in your code.
Help Fresh Programmers to Nurture their Skills
The community of developers without young and fresh developers is incomplete. Artificial Intelligence allows these programmers to get better insights on how to write great code and develop awesome software programs.
The AI-powered tools help developers to collaborate on projects and offer the convenience of sharing acumens with experienced as well as fresh programmers. In fact, it helps both experienced and fresh programmers to learn from one another. These tools can be utilized to help fresh programmers to strengthen their skills and advance in their careers.
Deployment Control
Machine Learning AI technologies facilitate in increasing the efficiency when it comes to deployment control activities related to software development. In the Software development empire, deployment mechanism involves the development phase where developer upgrade applications or programs to new versions.
In case, the developer fails to execute the process correctly, there are high risks involved including ruining of application or software. However, AI can prevent software developers from such vulnerabilities of upgradation and prevent risks of failed deployment. Developers can also examine related to deployment process using Machine Learning algorithms.
The potential of Machine Learning in software development will not only help developers but will also prove to be the game changer for businesses looking out for software solutions. A wrong code or deployment failure will not affect the software agency, but a huge loss to the company as well.