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/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

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

Zendy Tools

Zendy Open

Context: Learning-based automatic program repair techniques are showingpromise to provide quality fix suggestions for detected bugs in the source codeof the software. These tools mostly exploit historical data of buggy and fixedcode changes and are heavily dependent on bug localizers while applying to anew piece of code. With the increasing popularity of code review, dependency onbug localizers can be reduced. Besides, the code review-based bug localizationis more trustworthy since reviewers' expertise and experience are reflected inthese suggestions.  Objective: The natural language instructions scripted on the review commentsare enormous sources of information about the bug's nature and expectedsolutions. However, none of the learning-based tools has utilized the reviewcomments to fix programming bugs to the best of our knowledge. In this study,we investigate the performance improvement of repair techniques using codereview comments.  Method: We train a sequence-to-sequence model on 55,060 code reviews andassociated code changes. We also introduce new tokenization and preprocessingapproaches that help to achieve significant improvement over state-of-the-artlearning-based repair techniques.  Results: We boost the top-1 accuracy by 20.33% and top-10 accuracy by 34.82%.We could provide a suggestion for stylistics and non-code errors unaddressed byprior techniques.  Conclusion: We believe that the automatic fix suggestions along with codereview generated by our approach would help developers address the reviewcomment quickly and correctly and thus save their time and effort.

Review4Repair: Code Review Aided Automatic Program Repairing