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Case Study #100 — Top 100 Software Failures

Black Monday portfolio-insurance algorithmic crash

The Dow Jones Industrial Average fell 22.6% in a single day, the largest one-day percentage drop in its history, wiping out roughly $500 billion in US stock market value.

1987-10-19
When it happened
Finance
Sector
#100 of 100
Ranked by documented impact
01 — What Happened

The damage was public. The root cause was preventable.

The Dow Jones Industrial Average fell 22.6% in a single day, the largest one-day percentage drop in its history, wiping out roughly $500 billion in US stock market value.

Finance
Sector affected
1987-10-19
Date of the event
#100
Rank in the Top 100 Software Failures
2
Distinct root-cause clauses identified below
02 — The Root Cause

What the software actually got wrong

Automated 'portfolio insurance' trading programs, widely adopted by institutional investors, were all programmed to sell index futures as prices fell; because so many funds ran functionally identical software strategies, their simultaneous automated selling formed a self-reinforcing feedback loop that available market liquidity could not absorb.

01Root Cause

Automated 'portfolio insurance' trading programs, widely adopted by institutional...

What Happened

Automated 'portfolio insurance' trading programs, widely adopted by institutional investors, were all programmed to sell index futures as prices fell

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

Because so many funds ran functionally identical software strategies,...

What Happened

because so many funds ran functionally identical software strategies, their simultaneous automated selling formed a self-reinforcing feedback loop that available market liquidity could not absorb

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.