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Case Study #15 — Top 100 Software Failures

Uber self-driving car pedestrian fatality

Pedestrian Elaine Herzberg was killed, the first pedestrian death caused by an autonomous vehicle; Uber suspended its entire self-driving test programme.

2018-03-18
When it happened
Automotive
Sector
#15 of 100
Ranked by documented impact
01 — What Happened

The damage was public. The root cause was preventable.

Pedestrian Elaine Herzberg was killed, the first pedestrian death caused by an autonomous vehicle; Uber suspended its entire self-driving test programme.

Automotive
Sector affected
2018-03-18
Date of the event
#15
Rank in the Top 100 Software Failures
3
Distinct root-cause clauses identified below
02 — The Root Cause

What the software actually got wrong

The self-driving software detected the pedestrian but repeatedly misclassified her, and emergency braking had been disabled in testing mode; the human safety driver was not attentive.

01Root Cause

The self-driving software detected the pedestrian but repeatedly misclassified...

What Happened

The self-driving software detected the pedestrian but repeatedly misclassified her

How Requs AI Catches This

Requs AI Edge Case flags this exact pattern at the requirements and architecture stage — before a single line of code implementing it exists — so the assumption behind it gets challenged while it is still cheap to fix.

02Root Cause

Emergency braking had been disabled in testing mode

What Happened

emergency braking had been disabled in testing mode

How Requs AI Catches This

Requs AI Software FMEA traces this failure mode back to the system-level hazard it feeds, tagging it against the Common Defect Enumeration so it surfaces in review instead of in the field.

03Root Cause

The human safety driver was not attentive

What Happened

the human safety driver was not attentive

How Requs AI Catches This

Requs AI Edge Case and Software FMEA together treat this as a known, catalogued defect pattern — not a novel surprise — so it gets tested for deliberately rather than discovered after deployment.

03 — How This Gets Caught Before It Happens

Beyond code coverage and "shall" testing

Root causes like this one rarely show up in code coverage or requirements-compliance testing, because nobody wrote a requirement anticipating the specific edge case that broke. Requs AI Edge Case and Requs AI Software FMEA are built to surface exactly this class of overlooked failure mode — before the software is written.

Requs AI Edge Case

Surfaces this before code exists

Identifies edge cases like this one at requirements and architecture time, using the Common Defect Enumeration to catalog failure patterns seen across hundreds of real-world software failures — including this one.

Requs AI Software FMEA

Connects the failure mode to the hazard

Traces this class of root cause directly to the system-level hazard it can produce, so a defect pattern like this one gets flagged during design review instead of after it ships.

Find the overlooked root causes before they ship.

Schedule a demonstration, or explore how Requs AI Edge Case and Software FMEA use the Common Defect Enumeration.