  Code summarization and code search have been widely adopted in
sofwaredevelopmentandmaintenance. However, fewstudieshave explored the efcacy
of unifying them. In this paper, we propose TranS^3 , a transformer-based
framework to integrate code summarization with code search. Specifcally, for
code summarization,TranS^3 enables an actor-critic network, where in the actor
network, we encode the collected code snippets via transformer- and
tree-transformer-based encoder and decode the given code snippet to generate
its comment. Meanwhile, we iteratively tune the actor network via the feedback
from the critic network for enhancing the quality of the generated comments.
Furthermore, we import the generated comments to code search for enhancing its
accuracy. To evaluatetheefectivenessof TranS^3 , we conduct a set of
experimental studies and case studies where the experimental results suggest
that TranS^3 can signifcantly outperform multiple state-of-the-art approaches
in both code summarization and code search and the study results further
strengthen the efcacy of TranS^3 from the developers' points of view.
