Introduced by Massimo Forno
Software Signal Engineering
A discipline for testing and reliability in complex dynamic systems.
Stop counting tests.
Start modeling signals.
Founder of Quantik Mind
Testing is not a coverage problem.
It is a signal problem.
Test outcomes are observations. Observations decay, correlate, and carry uncertainty.
The objective is not more execution. The objective is better system knowledge.
The problem
Deterministic testing does not scale.
Code changes.
Dependencies shift.
Traffic fluctuates.
Infrastructure adapts.
Yet testing still behaves as if software were static.
Coverage is a vanity metric.
Signals are knowledge.
Definition
What changes when testing is treated as signal engineering.
Software Signal Engineering does not optimize for execution volume. It optimizes for informational value.
In this model, a test is not important because it exists in a suite. It is important because of the knowledge it can still produce under current system conditions.
The goal is not to run more tests. The goal is to extract more relevant system knowledge.
Principles
Three foundations.
Test results lose relevance over time. A passing test yesterday is not a guarantee today.
Some tests reveal information about others. Knowledge is not isolated. It propagates.
Testing should concentrate where knowledge is weakest and uncertainty is highest.
Manifesto
The Signal Engineering Manifesto
Test outcomes are signals.
Signals decay.
Coverage is not knowledge.
Deterministic validation cannot scale.
Testing must become probabilistic.
System knowledge outweighs test volume.
Origin
Introduced in 2026 by Massimo Forno
Software Signal Engineering emerges from a widening gap. Distributed systems have become dynamic, context-sensitive, and increasingly probabilistic in behavior.
Yet testing language and testing strategy have largely remained deterministic. Suites still optimize for completion, repetition, and coverage, even when system reality is fluid, relational, and uncertain.
The discipline was introduced to describe that gap more precisely, and to offer a more adequate model for reasoning about validation in modern systems.
Quantik Mind is the current reference implementation of these principles.