English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Question answering platforms, such as Stack Overflow, have impactedsubstantially how developers search for solutions for their programmingproblems. The crowd knowledge content available from such platforms has alsobeen used to leverage software development tools. The recent advances onNatural Language Processing, specifically on more powerful language models,have demonstrated ability to enhance text understanding and generation. In thiscontext, we aim at investigating the factors that can influence on theapplication of such models for understanding source code related data andproduce more interactive and intelligent assistants for software development.In this preliminary study, we particularly investigate if a how-to questionfilter and the level of context in the question may impact the results of aquestion answering transformer-based model. We suggest that fine-tuning modelswith corpus based on how-to questions can impact positively in the model andmore contextualized questions also induce more objective answers.

Towards a question answering assistant for software development using a transformer-based language model