Related papers: Personalized First Issue Recommender for Newcomers…
Open-source software (OSS) projects rely on effective newcomer onboarding to sustain their communities. OSS projects widely adopt "good first issue" (GFI) labels to highlight beginner-friendly tasks. As development practices continue to…
Newcomers are critical for the success and continuity of open source software (OSS) projects. To attract newcomers and facilitate their onboarding, many OSS projects recommend tasks for newcomers, such as good first issues (GFIs). Previous…
Sustaining newcomer participation is critical for the long-term health of open-source communities. Although prior research has explored various task recommendation approaches to help newcomers resolve their first-issue, these methods…
Attracting and retaining a steady stream of new contributors is crucial to ensuring the long-term survival of open-source software (OSS) projects. However, there are two key research gaps regarding recommendations for onboarding new…
Developers often struggle to navigate an Open Source Software (OSS) project's issue-tracking system and find a suitable task. Proper issue labeling can aid task selection, but current tools are limited to classifying the issues according to…
Selecting an appropriate task is challenging for contributors to Open Source Software (OSS), mainly for those who are contributing for the first time. Therefore, researchers and OSS projects have proposed various strategies to aid…
Successful open source communities are constantly looking for new members and helping them become active developers. A common approach for developer onboarding in open source projects is to let newcomers focus on relevant yet easy-to-solve…
Context: To attract, onboard, and retain any new-comer in Open Source Software (OSS) projects is vital to their livelihood. Recent studies conclude that OSS projects risk failure due to abandonment and poor participation of newcomers.…
Newcomers to a software project must overcome many barriers before they can successfully place their first code contribution, and they often struggle to find information that is relevant to them. In this work, we argue that much of the…
Federated recommendation system usually trains a global model on the server without direct access to users' private data on their own devices. However, this separation of the recommendation model and users' private data poses a challenge in…
Sequential recommendation systems often struggle to make predictions or take action when dealing with cold-start items that have limited amount of interactions. In this work, we propose SimRec - a new approach to mitigate the cold-start…
New contributors often struggle to find tasks that they can tackle when onboarding onto a new Open Source Software (OSS) project. One reason for this difficulty is that issue trackers lack explanations about the knowledge or skills needed…
The ability of an Open Source Software (OSS) project to attract, onboard, and retain any newcomer is vital to its livelihood. Although, evidence suggests an upsurge in novice developers joining social coding platforms (such as GitHub), the…
Effective prioritization of issue reports is crucial in software engineering to optimize resource allocation and address critical problems promptly. However, the manual classification of issue reports for prioritization is laborious and…
Recommender systems suffer from the cold-start problem whenever a new user joins the platform or a new item is added to the catalog. To address item cold-start, we propose to replace the embedding layer in sequential recommenders with a…
Recommendation systems help users find matched items based on their previous behaviors. Personalized recommendation becomes challenging in the absence of historical user-item interactions, a practical problem for startups known as the…
Open Source Software (OSS) projects rely on a continuous stream of new contributors for their livelihood. Recent studies reported that new contributors experience many barriers in their first contribution, with the social barrier being…
Application programming interfaces (APIs) offer a plethora of functionalities for developers to reuse without reinventing the wheel. Identifying the appropriate APIs given a project requirement is critical for the success of a project, as…
The federated recommendation system is an emerging AI service architecture that provides recommendation services in a privacy-preserving manner. Using user-relation graphs to enhance federated recommendations is a promising topic. However,…
In modern recommender systems, especially in e-commerce, predicting multiple targets such as click-through rate (CTR) and post-view conversion rate (CTCVR) is common. Multi-task recommender systems are increasingly popular in both research…