Esteban Sanchez

Session 6: Applying IFPUG Function Point Analysis to AI-Based Automotive Embedded Systems
Time: 1:40 pm – 2:10 pm

Session Abstract:
As Artificial Intelligence becomes increasingly integrated into automotive embedded software, organizations face new challenges in objectively sizing and estimating these systems. While Function Point Analysis (FPA) is widely used for business applications, its application to AI-enabled embedded systems remains a relatively unexplored area.

This presentation demonstrates how the IFPUG Function Point Method can be effectively applied to modern automotive embedded systems while remaining fully aligned with the IFPUG Counting Practices Manual (CPM). The session emphasizes that Function Points measure the functionality delivered to the functional user, regardless of the underlying technologies, including AI.

The presentation uses an **AI Driver Monitoring System (DMS)** as a practical case study. The system analyzes camera images and vehicle sensor data to detect driver fatigue, distraction, and drowsiness, generating alerts and interacting with other Electronic Control Units (ECUs). This example will be used to illustrate the identification of Application Boundaries, Functional Users, External Inputs (EIs), External Outputs (EOs), External Inquiries (EQs), Internal Logical Files (ILFs), and External Interface Files (EIFs).

Several practical Function Point counting examples based on the Driver Monitoring System will demonstrate how AI-enabled embedded functionality can be measured consistently using IFPUG standards. The session will conclude with lessons learned, practical recommendations, and an open discussion on applying Functional Size Measurement to next-generation embedded software.

Speaker Bio:
Esteban Sanchez is a well recognized expert on software measurement and estimation. He is the Chair of the FSSC at IFPUG and works with numerous organizations around the world to develop mature estimation processes for software and IT systems.