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Rubber duckies

Understanding Program Semantics

With symbolic execution

Thus far, we have established the need to represent code as vectors before feeding it into a machine learning classifier that will help us sort through a messy project. We have also discussed at...



Book in two languages

Can code be translated?

From code to words

Now that we have a better undestanding of how natural language and code embeddings work, let us take a look at a work by the same authors of code2vec, entitled code2seq: generating sequences from...



Arrows vector field

Embedding code into vectors

Vector representations of code

As we have stated over and over in the past, the most critical step in our ongoing project of building a machine learning (ML) based code classifier will be that of representing the code as...



Photo by Franck V. on Unsplash: https://unsplash.com/photos/_E1PQXKUkMw

The Vectors of Language

Distributed representations of natural language

Recall that in previous iterations we described the required steps for our code classifier to work, which can be roughly summarized as: Fetching data. Representing code as vectors. Training the...



Photo by camilo jimenez on Unsplash: https://unsplash.com/photos/vGu08RYjO-s

Triage for Hackers

Prioritize code auditing via ML

Based upon our last experiment, in this article, I will provide a global vision of how our ML for vulnerability discovery approach should work. First, what problem would this solve? I am repeating...



Git. Photo by Yancy Min on Unsplash: https://unsplash.com/photos/842ofHC6MaI/

Big Code

Learning from open source

In our Machine Learning (ML) for secure code series the mantra has always been the same: to figure out how to leverage the power of ML to detect security vulnerabilities in source code, regardless...




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