Ever since software development progressed from compiler code, there have existed a range of tools to help make developing easier and more effective.  A number of projects point in an interesting direction for the sector however.

For instance, Amazon recently announced the launch of Cloud 9, an integrated development environment that directly connects to the cloud computing platform provided by the company.  It’s a strong sign that machine learning is becoming a strong presence in software development on the cloud.

Developers using the platform can easily tap into the cloud-based AI baked into the software to create the next generation of apps.  Amazon hope that it will allow more of the software we use every day to have intelligence built in as standard.

It’s part of a broader movement to make it easier to utilize AI in the development of applications.  Whilst the big tech players are investing heavily in this space, there are also a number of interesting startups making waves as well.

Intelligent coding

For instance, Paperspace aims to make it easier to start using deep learning via their cloud-based virtual machine, whilst Carnegie Mellon spinout Petuum aim to provide a complete software infrastructure for the development of AI for the enterprise.

One of the more interesting is Oxford University spinout Diffblue, who have developed an AI-based solution to help improve the way code is tested.  The company, which raised $22 million in Series A funding earlier this year, has developed the platform in partnership with Goldman Sachs, who have a stake in the startup.

The AI engine aims to understand precisely what the code is trying to achieve, and then tests the code to examine just how well it’s performing.  The testing engine is currently available for Java and C and the company are working with a number of major banks and financial institutions, although there are plans to expand not only into new industries but also into new languages, including Python, Javascript and C#.

“We believe that the suite of tools we are developing at Diffblue has immense potential to help address these issues. Studies show that coders spend up to 30% of their time writing tests. Automation will provide great returns both in terms of achieving much broader test coverage, and also freeing up significant developer time. Furthermore, many legacy codebases suffer from very deficient test coverage, which removes any chance of lifting them out of legacy and into nimbleness – again, we believe automation in this space will have powerful beneficial effects,” the company say.

Suffice to say, with the company still at an early stage in its development, the long-term strategy is still being forged.  For instance, it’s not clear yet whether they will pursue life as a standalone product or license the technology to a larger software development suite.  There is also the potential to work more closely with systems integrators such as Wipro.

Software is undoubtedly becoming more complex, so it’s pleasing to see a number of tools emerging to help developers, and indeed managers, handle that growing complexity and ensure that applications are not only effective but secure and efficient too.