Dual-Component Deep Domain Adaptation: A New Approach for Cross Project Software Vulnerability Detection.

Owing to the ubiquity of computer software, software vulnerability detection (SVD) has become an important problem in the software industry and computer security. One of the most crucial issues in SVD is coping with the scarcity of labeled vulnerabilities in projects that require the laborious manual labeling of code by software security experts. One possible solution is to employ deep domain adaptation (DA) which has recently witnessed enormous success in transferring learning from structural labeled to unlabeled data sources. Generative adversarial network (GAN) is a technique that attempts to bridge the gap between source and target data in the joint space and emerges as a building block to develop deep DA approaches with state-of-the-art performance. However, deep DA approaches using the GAN principle to close the gap are subject to the mode collapsing problem that negatively impacts the …