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Case Study #251 — 300 Software Failure Case Studies

Kenya 2017 presidential election IT result-transmission failure

Kenya's Supreme Court annulled the 2017 presidential election result and ordered a re-run, citing irregularities in the electronic transmission of results.

2017-08
When it happened
Government
Sector
#251 of 300
Ranked by documented impact
01 — What Happened

The damage was public. The root cause was preventable.

Kenya's Supreme Court annulled the 2017 presidential election result and ordered a re-run, citing irregularities in the electronic transmission of results.

Government
Sector affected
2017-08
Date of the event
#251
Rank in the 300 Software Failure Case Studies
1
Distinct root-cause clause identified below
02 — The Root Cause

What the software actually got wrong

The court found the electoral commission's IT system for transmitting and verifying polling-station results did not meet the legal requirements for a secure, verifiable count, with gaps in the system's audit trail that could not rule out manipulation of the transmitted results.

01Root Cause

The court found the electoral commission's IT system for...

What Happened

The court found the electoral commission's IT system for transmitting and verifying polling-station results did not meet the legal requirements for a secure, verifiable count, with gaps in the system's audit trail that could not rule out manipulation of the transmitted results.

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.