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Case Study #185 — 300 Software Failure Case Studies

T-Mobile nationwide voice and data outage

T-Mobile customers across the US experienced widespread voice call, text, and data outages for most of a day, including thousands of failed 911 calls, prompting an FCC investigation.

2020-06-15
When it happened
Telecommunications
Sector
#185 of 300
Ranked by documented impact
01 — What Happened

The damage was public. The root cause was preventable.

T-Mobile customers across the US experienced widespread voice call, text, and data outages for most of a day, including thousands of failed 911 calls, prompting an FCC investigation.

Telecommunications
Sector affected
2020-06-15
Date of the event
#185
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

An FCC investigation found that a leased fiber circuit failure triggered a flood of diagnostic messages across T-Mobile's IP-based voice network; the network's software was not adequately designed to handle that volume of signaling traffic, causing a cascading overload across the network.

01Root Cause

An FCC investigation found that a leased fiber circuit...

What Happened

An FCC investigation found that a leased fiber circuit failure triggered a flood of diagnostic messages across T-Mobile's IP-based voice network

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 network's software was not adequately designed to handle...

What Happened

the network's software was not adequately designed to handle that volume of signaling traffic, causing a cascading overload across the network

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.