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Spin-off of HPI identifies optimization potential in software engineering based on real company data
Potsdam, December 3, 2019:
In a newly offered workshop, Seerene will demonstrate achievable optimization potentials through the use of AI-based methods in software engineering. The HPI spin-off will start directly in the company, namely with the development tools already used for software engineering. The information available in repositories and databases is merged and evaluated using the possibilities of artificial intelligence. The result is a "Digital Boardroom” for software management with meaningful key figures, dashboards, and software maps. This also allows for cross-company benchmarking of software development processes and risks and enables possible starting points for optimization.
"In addition to realizing efficiency potentials - often 30 percent and more - AI-based software analytics also succeeds in increasing the quality and robustness of software and minimizing the commercial risks associated with it," explains Seerene Founder and CPO Dr Johannes Bohnet. "Until now, however, this experience has been reserved for companies that already have a corresponding platform in use. With our workshop, we now want to lower the entry obstacles and clearly demonstrate to interested parties what results they can achieve in their very specific situation even before they decide on continuous real-time monitoring".
The workshop includes the analysis of one or more business-critical applications. After a kick-off meeting, which also serves to clarify fundamental questions, the Seerene software analytics platform will be connected to the software development tools used in the company in order to apply analytics procedures based on the data traces left behind by these tools. Seerene's analytics platform supports all common tools from all different areas of the development process: tools for source code management, static code analysis, task & issue tracking, bug/defect tracking, test automation and code coverage, and continuous integration systems (CI/CD). Seerene and the technical experts jointly set up the Digital Boardroom and adapt the KPI key figures to the specific requirements and concrete challenges of the company.
"For those responsible, this is the first time that the development process as a whole becomes visible to those in charge," summarizes Bohnet. "After an observation period of two to four weeks, concrete results are available that lead to clear recommendations for the management and control process." In a final presentation, these are discussed with the management and ideally the next steps are already agreed upon - but then based on hard facts and no longer just following a gut feeling. This approach is therefore particularly suitable for the financial sector and other compliance-sensitive industries.
Software Analytics is based on more than 15 years of academic research at the Hasso Plattner Institute for Digital Engineering (HPI) in Potsdam, Germany. It uses artificial intelligence and machine learning to analyze complex interrelationships in the development of software systems. "Repositories and all the other tools have long provided us with excellent, precise data on all the essential aspects of software development," explains Prof. Dr. Jürgen Döllner, head of the AI Laboratory for Software Engineering at HPI, "We only have to release them from their silos and look at them in their entirety to generate superordinate knowledge that helps all those responsible in the software development process. Seerene's workshop makes it possible for software management to experience this now: early on and in relation to their own situation".
Seerene builds on more than 15 years of academic research in software analytics. The spin-off of the Hasso Plattner Institute for Digital Engineering (HPI) relies on artificial intelligence and machine learning to analyze complex relationships in the development of software systems. The Seerene software analytics platform integrates the existing development infrastructure, the repositories and data already isolated in the various sub-disciplines of software development with its own analyses and makes the knowledge available in a “digital boardroom” to those responsible. Meaningful key metrics, dashboards and software maps make the development process visible as a whole and in real time for the first time and form a common basis for the end-to-end management of software processes across all expert fields. In this way, efficiency potentials of 30 percent and more can be realized, quality and robustness can be increased, and risks minimized.