Big Data for Safety: Unleashing the Power of Your Software Project Data
A software project accumulates vast data along its life-cycle: Requirements, designs, code, tests and tickets. In this talk we illustrate how this big data can be leveraged to achieve safety in a more efficient and cost-effective way.
Reporting safety compliance of industrial software projects can become a complex task, as safety standards, their variations, additional internal and external customer safety requirements have to be considered.
Introducing Quality Gates monitoring project's compliance evolution is a way of ensuring that expectations are met. But, reaching perfection (all tests must pass, 100% compliance and no Technical Debt) is both time consuming and virtually unrealistic. A more efficient approach is to automatically leverage the project data to identify gaps between actual project indicators and specified target values and then to systematically reduce this gap.
This strategy can be implemented in a four-step process:
Measure: Project data is gathered and aggregated into meaningful high-level indicators, gaps are calculated.
Analyze: With product delivery and project-context in mind, risks are assessed, and potential actions derived.
Decide: Based on analytics informed decisions are taken.
Automate: Automatic iteration of steps 1-3 for repeatable, reliable and actionable results.
After this talk, attendees should know more about the use of high-level indicators in safety projects and how these indicators can be automatically calculated from development artifacts.
Safety & Security