Communications of the ACM
Research Archive
The Research archive provides access to all Research articles published in past issues of Communications of the ACM.
November 2020
From Communications of the ACM
Technical Perspective: BLeak: Semantics-Aware Leak Detection in the Web
What is the right leak oracle that can precisely capture the behavior of leaks in Web applications? "BLeak: Automatically Debugging Memory Leaks in Web Applications," by John Vilk and Emery D. Berger, provides a simple and yet…
From Communications of the ACM
Generative Adversarial Networks
In this overview paper, we describe one particular approach to unsupervised learning via generative modeling called generative adversarial networks. We briefly review applications of GANs and identify core research problems related…
From Communications of the ACM
BLeak: Automatically Debugging Memory Leaks in Web Applications
This paper introduces BLeak (Browser Leak debugger), the first system for automatically debugging memory leaks in web applications.
From Communications of the ACM
Technical Perspective: When the Adversary Is Your Friend
The key insight of the "Generative Adversarial Networks," by Ian Goodfellow et al., is to learn a generative model's loss function at the same time as learning the model.