Predictive Analytics key to great software quality? Intro to Grip.QA

logo gripInterview with founders Kamiel Wanrooij and Jan Princen
Date: 10 October 2014
Grip.QA profile

Last week I had the opportunity to meet up with two old friends, Jan and Kamiel, for some drinks and hear about their plans with Grip.QA

In a sentence, Grip applies predictive analytics to software development to improves software quality. I have interviewed quite a few predictive analytics companies in the IT infrastructure space and I was intrigued to learn about the application of predictive analytics to software development.

Predictive Analytics for Software Development
Grip provides predictive analytics for software development organizations to improve software quality. With Grip development teams get real time insight in the state of their software development and learn how far they are off from reaching goals, such as on time delivery, and what they actions they can take to hit targets.

They differ from other software analysis tools, such as those that provide source code analysis, in two ways. Firstly, Grip uses a broader data set for its analysis. Besides product data Grip also uses data about the people that create the software, and the processes by which the software is build. Secondly, instead of after the fact reporting of deficiencies in the source code, Grip provides predictions on the quality in use and the ability of the team to deliver on time and within budget, that can be used to implement changes before problems occur.

Data Driven Software Development
In his previous role in QA process consulting Jan learned how hard it is, even for the best teams, to develop good software and how much money was involved with damage from software that did not meet expectations. “I saw many organizations struggling to deliver their software and noticed that even in large companies decisions often are not based on data, but on the gut feeling and experience of the teams. With the world increasingly dependent on software this is a major risk. The interesting thing about software development organizations is that they already generate tons of data. Up until now it was just very hard to collect and analyze this data,” says Jan.

“This is where Grip comes in”, adds Kamiel, “we harvest historic and real time data from many different aspects of the development of a software product, and run this data through our machine learning algorithms to make predictions on user satisfaction goals for that product. We then tell our users in a simple to do list what issues have most impact on reaching those goals. User of Grip can for instance use our predictions to learn what to specific actions to take improve their time to market.”

Currently in Beta
Grip has released a beta version and is now running predictions for several software development organizations. Grip provides a level of insight for several levels within a software development organization; senior executives can see portfolio risks over several products or teams, while product managers and developers can delve deeper in the specific root causes that risk product goals to tackle them before they cause real problems.

Interesting Market
The space that Grip is in, is hot. In september of this year, Semmle received a series A round investment of $8 million. The respected venture capital firm Accel Partners joined the round.

Predictive analytics applied to Software development vs IT Infrastructure
My talk with Jan and Kamiel has been wrecking my brain. Predictive analytics, applied to software development and IT Infrastructure, offers many parallel advantages. I have not yet been able to define the common ground precisely though. I predict a few follow-up posts 🙂

Resources and related links
Grip’s website
Website of Semmle
CloudPhysics, Predictive Analytics applied to virtual datacenter
Interview with CEO John W. Thompson of VirtualInstruments

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