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Have these techniques been used to generate realistic looking test data for testing software? I have had ideas along these lines but people think I'm talking ab
by johnwatson11218 10y ago
Have these techniques been used to generate realistic looking test data for testing software? I have had ideas along these lines but people think I'm talking about fuzz testing when I try and describe it.
I'm imagining something where you take a corporate db and reduce it down to a model. Then that can be shared with third parties and used to generate unlimited amounts of test data that looks like real data w/o revealing any actual user info.
- hacker42 10y agoThat depends on the nature of the data, I think. If the data has a lot of sequential, sparse, hierarchical statistical dependencies (like source code, text or data streams), they might be better modeled by an LSTM. If you have high-dimensional dependencies (like images, where each pixel tends to spatially depends on many other pixels), then an autoencoder or some undirected model might be the right choice.