Product: ADAS Software Quality & Performance Analytics Platform

Client Challenge:
The project focused on maintaining software quality and performance visibility across the development lifecycle of advanced driver assistance systems (ADAS). The objective was to improve software quality governance, automate compliance monitoring, and establish KPI-driven performance tracking for autonomous driving functions.

RSB Solution:

• Supported Product Lifecycle (PLC) quality processes, including static code analysis, code coverage monitoring, technical documentation, and code inspections using Coverity, coverage analysis tools, Doxygen, Gerrit, and Jenkins.
• Performed software quality assessments and supported compliance monitoring through automated reporting and verification workflows.
• Designed and implemented new KPI frameworks to measure system performance and identify regressions in autonomous driving scenarios.
• Developed data analysis, reporting, and visualization solutions using Python, SQL, Redash, GitLab, and related analytics tools.
• Worked within CI/CD, source control, and build environments utilizing GitLab, Gerrit, Jenkins, and Bazel.
• Collaborated with cross-functional software development and quality assurance teams using Jira, Slack, Microsoft Teams, Codex, and Cursor to improve transparency and decision-making.

Delivered Results:
The project delivered enhanced software quality monitoring through automated code compliance and coverage tracking, improved inspection workflows, and comprehensive KPI dashboards. The newly developed performance metrics provided increased visibility into system behavior, enabling faster detection of regressions and supporting continuous improvement of autonomous driving software.

Client Value:
The client gained improved software quality governance, data-driven performance monitoring, greater transparency of development KPIs, and faster identification of software regressions, supporting the delivery of reliable ADAS functionality.