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Testing and Fault Localization Part 4

Necessity is not Sufficiency Theorem 1 from the last post works due to the fact that simpler models are usually sufficient to explain causal relationships as opposed to more complicated models. Judea Pearl uses the term minimal causal structures for such simpler models. Further, such simpler models directly represent the use of the problem-solving principle called […]


Testing and Fault Localization Part 2

The Underlying Problem of Fault Localization The underlying problem for fault localization is a phenomenon called confounding (also called confounding bias). Therefore, we must first understand what confounding bias means. In simplest terms, confounding is an unknown causal quantity that is not directly measurable from observed data[1] In other words, an effect is confounded when its cause […]


Testing and Fault Localization

Testing and Fault Localization One of the goals of software testing is to produce evidence that a piece of software works as intended. That evidence might be in the form of hard, deterministic data or even stochastic results that statistically show the correctness of the software system to some degree, among others. However, with modern software […]