Large language models such as Codex, have shown the capability to produce code for
many programming tasks. However, the success rate of existing models is low, especially for …

Large pre-trained language models such as GPT-3 [10], Codex [11], and Google's language
model [7] are now capable of generating code from natural language specifications of …

In this paper, we present a natural language code synthesis tool, GenLine, backed by 1) a
large generative language model and 2) a set of task-specific prompts that create or change …

Large language models (LLMs) have shown great potential in automating significant
aspects of coding by producing natural code from informal natural language (NL) intent …

Students often make mistakes on their introductory programming assignments as part of
their learning process. Unfortunately, providing custom repairs for these mistakes can …

Prior work has combined chain-of-thought prompting in large language models (LLMs) with
programmatic representations to perform effective and transparent reasoning. While such an …

Deep learning (DL) techniques have been used to support several code-related tasks such
as code summarization and bug-fixing. In particular, pre-trained transformer models are on …

Programming-by-Examples (PBE) involves synthesizing an" intended program" from a small
set of user-provided input-output examples. A key PBE strategy has been to restrict the …

Large languages models (LLMs) trained on datasets of publicly available source code have
established a new state-of-the-art in code completion. However, these models are mostly …

While large language models (LLMs) now excel at code generation, a key aspect of software
development is the art of refactoring: consolidating code into libraries of reusable and …