title: SoTaNa: The Open-Source Software Development Assistant
summary: Software development plays a crucial role in driving innovation and
  efficiency across modern societies. To meet the demands of this dynamic field,
  there is a growing need for an effective software development assistant.
  However, existing large language models represented by ChatGPT suffer from
  limited accessibility, including training data and model weights. Although
  other large open-source models like LLaMA have shown promise, they still
  struggle with understanding human intent. In this paper, we present SoTaNa, an
  open-source software development assistant. SoTaNa utilizes ChatGPT to generate
  high-quality instruction-based data for the domain of software engineering and
  employs a parameter-efficient fine-tuning approach to enhance the open-source
  foundation model, LLaMA. We evaluate the effectiveness of  in answering
  Stack Overflow questions and demonstrate its capabilities. Additionally, we
  discuss its capabilities in code summarization and generation, as well as the
  impact of varying the volume of generated data on model performance. Notably,
  SoTaNa can run on a single GPU, making it accessible to a broader range of
  researchers. Our code, model weights, and data are public at
  https://github.com/DeepSoftwareAnalytics/SoTaNa.
paper_authors._id: 64ec46d5171e6c9862e3125a
paper_authors.name: Ensheng Shi
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-08-28T07:22:03.089Z
paper_authors._id: 622573983b9427436c09fe26
paper_authors.avatarUrl: https://cdn-avatars.huggingface.co/v1/production/uploads/1646653372528-622573983b9427436c09fe26.jpeg
paper_authors.fullname: Ensheng Shi
paper_authors.type: user
paper_authors.user: Ensheng
paper_authors._id: 64ec46d5171e6c9862e3125b
paper_authors.name: Fengji Zhang
paper_authors.status: admin_assigned
paper_authors.statusLastChangedAt: 2023-08-28T07:22:31.806Z
paper_authors._id: 64c8d4ac120a85440bfad55d
paper_authors.avatarUrl: /avatars/d65334288d69700250de51d0df344d9b.svg
paper_authors.fullname: Fengji Zhang
paper_authors.type: user
paper_authors.user: zfj1998
paper_authors._id: 64ec46d5171e6c9862e3125c
paper_authors.name: Yanlin Wang
paper_authors._id: 64ec46d5171e6c9862e3125d
paper_authors.name: Bei Chen
paper_authors.status: claimed_verified
paper_authors.statusLastChangedAt: 2024-01-23T13:49:33.830Z
paper_authors._id: 64cc65d786d8dc0caa6ab3cd
paper_authors.avatarUrl: /avatars/23dc126f7332825e713807fb1c000ab6.svg
paper_authors.fullname: Bei Chen
paper_authors.type: user
paper_authors.user: BellaBei
paper_authors._id: 64ec46d5171e6c9862e3125e
paper_authors.name: Lun Du
paper_authors._id: 64ec46d5171e6c9862e3125f
paper_authors.name: Hongyu Zhang
paper_authors._id: 64ec46d5171e6c9862e31260
paper_authors.name: Shi Han
paper_authors._id: 64ec46d5171e6c9862e31261
paper_authors.name: Dongmei Zhang
paper_authors._id: 64ec46d5171e6c9862e31262
paper_authors.name: Hongbin Sun
paper_title: SoTaNa: The Open-Source Software Development Assistant
paper_summary: Software development plays a crucial role in driving innovation and
  efficiency across modern societies. To meet the demands of this dynamic field,
  there is a growing need for an effective software development assistant.
  However, existing large language models represented by ChatGPT suffer from
  limited accessibility, including training data and model weights. Although
  other large open-source models like LLaMA have shown promise, they still
  struggle with understanding human intent. In this paper, we present SoTaNa, an
  open-source software development assistant. SoTaNa utilizes ChatGPT to generate
  high-quality instruction-based data for the domain of software engineering and
  employs a parameter-efficient fine-tuning approach to enhance the open-source
  foundation model, LLaMA. We evaluate the effectiveness of  in answering
  Stack Overflow questions and demonstrate its capabilities. Additionally, we
  discuss its capabilities in code summarization and generation, as well as the
  impact of varying the volume of generated data on model performance. Notably,
  SoTaNa can run on a single GPU, making it accessible to a broader range of
  researchers. Our code, model weights, and data are public at
  https://github.com/DeepSoftwareAnalytics/SoTaNa.