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Case Study #85 — Top 100 Software Failures

Uber surge-pricing algorithm during the Sydney hostage crisis

Uber's automated dynamic-pricing algorithm quadrupled fares in Sydney as people tried to flee the area during an active hostage crisis, drawing widespread public criticism; Uber refunded affected riders.

2014-12-15
When it happened
Retail / Technology
Sector
#85 of 100
Ranked by documented impact
01 — What Happened

The damage was public. The root cause was preventable.

Uber's automated dynamic-pricing algorithm quadrupled fares in Sydney as people tried to flee the area during an active hostage crisis, drawing widespread public criticism; Uber refunded affected riders.

Retail
Sector affected
2014-12-15
Date of the event
#85
Rank in the Top 100 Software Failures
1
Distinct root-cause clause identified below
02 — The Root Cause

What the software actually got wrong

The surge-pricing algorithm automatically raised prices in response to a spike in ride requests and had no override or exception logic to detect and suspend surge pricing during a declared public emergency.

01Root Cause

The surge-pricing algorithm automatically raised prices in response to...

What Happened

The surge-pricing algorithm automatically raised prices in response to a spike in ride requests and had no override or exception logic to detect and suspend surge pricing during a declared public emergency.

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.

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.