The need for measuring the state of your code via qualitative analysis is huge in ensuring that your software and applications are at the highest of standards. Kiuwan takes on this task as a cloud solution to indicate risk, quality and technical debt for software development. We sat down with Javier Salado, Partner Development & Marketing Manager for Kiuwan, to discuss this further.
insideBIGDATA: Kiuwan–How is the name of the company pronounced and what does it do?
Javier Salado: It’s pronounced like “Q 1.”
Kiuwan does automatic code review based on static analysis in the cloud. It is SaaS model, as opposed to other software quality solutions based in code analysis that are on-premise and very expensive to implement, Kiuwan is an affordable solution in the cloud. We are the Salesforce.com of software quality.
Users can upload their code to be analyzed in the cloud or they can download the analyzers to analyze within their firewalls if they don’t want or are not allowed to share the code. The results are always consumed in the Kiuwan web application in the cloud in comprehensive screens, generated reports or can be consulted to be consumed elsewhere using the Kiuwan RESTful API. Kiuwan offers several extra features like remediation action plans based on available effort or quality targets, and much, much more.
insideBIGDATA: Which organizations would find code analysis most useful?
Javier Salado: In short, any organization that develops software would benefit greatly from code analysis. From big corporations like banks where software is critical for their business to small startups developing mobile applications. Most organizations today rely on software to run their business, and many of them develop the software they use using different technologies. All these companies can benefit with Kiuwan by measuring and analyzing their software with Kiuwan to know the risk they face in their development processes and assure the highest quality of the code even before testing the applications. Kiuwan will find defects to fix during development when it is cheaper, and will generate action plans to continuously improve the quality in a very affordable way.
insideBIGDATA: Can you tell me a little about the underlying technology behind this and how it came to be?
Javier Salado: The technology behind Kiuwan has been entirely developed by Optimyth Software, the owners of the Kiuwan brand. Kiuwan uses code parsers to understand the code of the different programming languages (15 supported today, and growing), then it executes different sets of rules to measure intrinsic metrics, the quality and find possible defects in the code affecting different software characteristics: Efficiency, Reliability, Maintainability, Portability and Security. With all this evidence Kiuwan calculates indicators like risk, global quality and technical debt in the form of efforts to solve the defects.
insideBIGDATA: What is Kiuwan’s play in the Big Data world?
Javier Salado: Kiuwan’s goal is to become a ‘de facto’ reference to measure and analyze software in the cloud. There are millions and millions of lines of code out there to analyze. We have modestly started analyzing open source projects available in GitHub for example. Along with the analyses from our users we are going to have an interesting and vast database about the quality of code around the world. The amount of data we can put together (with our users’ permission) enters in Big Data arena. We want to contribute to the big data technology and take advantage of it to exploit the huge amount of code quality data.
insideBIGDATA: As millions and millions of lines of code come into play day by day, how might Kiuwan handle this in 4-5 years?
Javier Salado: In 4-5 years we want to be a reference for anybody that is interested in application code quality. We are hoping to have code quality results for millions of applications. How are we going to handle this? Let’s see where the current Big Data technology available takes us, but I’m sure that even with today’s technology we can handle it and make some sense on the ocean of data we are going to be gathering during this time.