Project description
Machines to help software developers write code
Software development and testing teams work together to write and review code. This lengthy process hinges on the interaction between the two sides, which may lag due to availability issues. The EU-funded DEVINTA project will give this process a high-tech boost with an artificial intelligence (AI) assistant to speed up the process. It is developing a machine that can assist software developers by helping them comprehend unfamiliar code, natural language translation as well as in writing code faster through predictive feature implementation. The AI assistant would help improve code quality, performing online code review while the developer types the code, catching bugs and suboptimal implementation choices and providing timely solutions.
Objective
Software development, also due to the complexity of software systems, is tackled by collaborating teams of people. For example, in pair programming two developers share a single workstation: One writes code, while the other reviews it and proposes ideas for improvement. While interacting with teammates is the preferred means to obtain help, their availability may fall short and they might not always have a solution at hand. To address this problem, recommender systems for developers have been proposed in the form of applications providing information items considered valuable for a given task and context (e.g. recommending documentation useful to understand a code component). However, these recommenders can hardly be considered as a valid alternative to teammates since they are not proactive, do not support the developer in a wide variety of tasks, do not adapt their recommendations to the developer’s profile, and fall short in having meaningful interactions with the developer (e.g. they are not able to answer developers’ questions). Given the advances in artificial intelligence, the vision that one day a developer's teammate is a machine does not seem far-fetched anymore. The DEVINTA project aims at making this future a reality, introducing models and techniques serving as the basis for the first artificial assistant supporting developers in their everyday activities. The assistant helps in (i) comprehending unfamiliar code via source code to natural language translation; (ii) writing code faster, providing predictive feature implementation, meaning the ability to infer the feature the developer is implementing and automatically complete it; and (iii) improve code quality, performing online code review while the developer types the code, timely catching bugs and suboptimal implementation choices and providing solutions for them. The assistant uses advanced conversational interfaces to interact with the developer, answer her questions, and disambiguate her needs.
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Funding Scheme
ERC-STG - Starting GrantHost institution
6900 Lugano
Switzerland