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Case Study #190 — 300 Software Failure Case Studies

NORAD 1980 false missile-attack alarms

US strategic nuclear forces were briefly placed on alert after early-warning computers twice indicated a large-scale Soviet missile attack was underway, false alarms serious enough to prompt an emergency review of US nuclear command-and-control systems.

1979-11 and 1980-06
When it happened
Military / Defense
Sector
#190 of 300
Ranked by documented impact
01 — What Happened

The damage was public. The root cause was preventable.

US strategic nuclear forces were briefly placed on alert after early-warning computers twice indicated a large-scale Soviet missile attack was underway, false alarms serious enough to prompt an emergency review of US nuclear command-and-control systems.

Military
Sector affected
1979-11 and 1980-06
Date of the event
#190
Rank in the 300 Software Failure Case Studies
2
Distinct root-cause clauses identified below
02 — The Root Cause

What the software actually got wrong

A hardware chip fault in a communications component caused test data used to simulate missile-attack scenarios for training to be intermittently substituted into the live data feed monitored by warning-system operators, and the systems' design did not clearly and reliably distinguish test data from real, live attack data.

01Root Cause

A hardware chip fault in a communications component caused...

What Happened

A hardware chip fault in a communications component caused test data used to simulate missile-attack scenarios for training to be intermittently substituted into the live data feed monitored by warning-system operators

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

The systems' design did not clearly and reliably distinguish...

What Happened

the systems' design did not clearly and reliably distinguish test data from real, live attack data

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.

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.