Software is fundamentally changing the world we live in, yet mundane, routine tasks continue to bog down IT departments and developer teams. Combining Software Intelligence – insight into complex software structure – with machine learning and artificial intelligence in application development can automate these impediments to innovation and reduce the time it takes to achieve a company’s digital transformation goals.
At the end of last year, DevOps.com noted that 40% of digital transformation initiatives will be supported by cognitive/AI capabilities by 2019. This shift will help to automate many of the routine tasks that can impede software development at speed, but this is not possible without first establishing a platform for Software Intelligence that can feed data about the structural quality of software into the AI tool.
“While AI/machine learning will be able to help with these problems, you can’t just snap your fingers and make it so. Harnessing AI successfully requires specialized engineering talent, quality data, objective planning and some trial and error,” writes Scot Finnie. “One of the key points to remember is that the decision-making abilities of a machine learning tool can’t overcome a lack of quality data.”
Naresh Choudhary, associate vice president of Infosys, recently spoke with CAST to give a CIO-level perspective about how his organization incorporated machine leaning and AI on top of Software Intelligence to improve software quality and team productivity by 10 to 15 percent.
“Software intelligence is really about acquiring knowledge about the software you’re working with and applying it in meaningful and relevant ways,” said Choudhary.
“Where we are taking this forward is by ensuring that with Software Intelligence, using AI and machine learning on top of this information, and driving insights right into where developers spend most of their time,” said Choudhary. “That’s where we see the power of putting AI and machine learning onto this…we are able to use our DevOps platform to really drive insights that get better productivity.”
Choudhary says Infosys is using a suite of automation and software quality solutions, including CAST’s Application Intelligence Platform, to make their development process more transparent and efficient. This allows developers to gain insight into the ‘health’ of applications they are developing, while also generating reports and analytics dashboards about production for company stakeholders and front-end leaders.
In one particular instance, Naresh’s team ran into issues in their software development life cycle. With the help of CAST AIP, “the team was able to analyze the issues very rapidly, identify the root causes, fix them, and we were actually able to cut down our release time from a couple of months to a few weeks,” says Naresh. “And that was a drastic improvement to start with.”
You can watch the full video of Choudhary’s feedback on Software Intelligence as the foundation for AI and machine learning here.
Erik Oltmans, an Associate Partner from EY, Netherlands, spoke at the Software Intelligence Forum on how the consulting behemoth uses Software Intelligence in its Transaction Advisory services.
Erik describes the changing landscape of M & A. Besides the financial and commercial aspects, PE firms now equally value technical assessments, especially for targets with significant software assets. He goes on to detail how CAST Highlight makes these assessments possible with limited access to the targetâ€™s systems, customized quality metrics, and liability implications of open source components - all three that are critical for an M&A due diligence.