NLP2Code: Code Snippet Content Assist via Natural Language Tasks

@article{Campbell2017NLP2CodeCS,
  title={NLP2Code: Code Snippet Content Assist via Natural Language Tasks},
  author={Brock Angus Campbell and Christoph Treude},
  journal={2017 IEEE International Conference on Software Maintenance and Evolution (ICSME)},
  year={2017},
  pages={628-632}
}
Developers increasingly take to the Internet for code snippets to integrate into their programs. To save developers the time required to switch from their development environments to a web browser in the quest for a suitable code snippet, we introduce NLP2Code, a content assist for code snippets. Unlike related tools, NLP2Code integrates directly into the source code editor and provides developers with a content assist feature to close the vocabulary gap between developers' needs and code… 

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References

SHOWING 1-10 OF 22 REFERENCES

Bing developer assistant: improving developer productivity by recommending sample code

A tool called Bing Developer Assistant (BDA), which improves developer productivity by recommending sample code mined from public software repositories and web pages (such as Stack Overflow), which can automatically mine code snippets that implement an API or answer a code search query.

Prompter: A Self-Confident Recommender System

Prompter is presented, a plug-in for the Eclipse IDE which automatically searches and identifies relevant Stack Overflow discussions, evaluates their relevance given the code context in the IDE, and notifies the developer if and only if a user-defined confidence threshold is surpassed.

Making sense of online code snippets

This analysis is able to identify 253,137 method calls and type references from 21,250 Stack Overflow code snippets and shows how identifying structural relationships from snippets could perform better than lexical search over code blocks in practice.

SWIM: Synthesizing What I Mean - Code Search and Idiomatic Snippet Synthesis

SWIM, a tool which suggests code snippets given API-related natural language queries such as "generate md5 hash code" is described, which translates user queries into the APIs of interest using clickthrough data from the Bing search engine.

T2API: synthesizing API code usage templates from English texts with statistical translation

A statistical machine translation-based tool that takes a given English description of a programming task as a query, and synthesizes the API usage template for the task by learning from training data, and is capable of generating new API usages from smaller, previously-seen usages.

Understanding Stack Overflow Code Fragments

It is found that less than half of the Stack Overflow code fragments in this sample are considered to be self-explanatory by the 321 participants who answered the survey, and that the main issues that negatively affect code fragment understandability include incomplete fragments, code quality, missing rationale, code organization, clutter, naming issues, and missing domain information.

Seahawk: Stack Overflow in the IDE

Seahawk is an Eclipse plugin that supports an integrated and largely automated approach to assist programmers using Stack Overflow, and formulates queries automatically from the active context in the IDE, presents a ranked and interactive list of results, and lets users import code samples in discussions through drag & drop.

Jigsaw: a tool for the small-scale reuse of source code

This paper presents a tool, called Jigsaw, that uses thedeveloper's context to help integrate the reused source code into the developer's own source code.

Example Overflow: Using social media for code recommendation

Examples Overflow is presented, a code search and recommendation tool which brings together social media and code recommendation systems and enables crowd-sourced software development by utilizing both textual and social information, which accompany source code on the Web.

Learning from examples to improve code completion systems

Evidence is given that intelligent code completion systems which learn from examples significantly outperform mainstream codepletion systems in terms of the relevance of their suggestions and thus have the potential to enhance developers' productivity.