Studying Developer Perceptions on the Potential of CI Recommendation Systems
- URL: http://arxiv.org/abs/2608.02682v1
- Date: Mon, 03 Aug 2026 01:42:17 GMT
- Title: Studying Developer Perceptions on the Potential of CI Recommendation Systems
- Abstract summary: We aim to contact about 5,000 active GitHub developers, including both CI users and non-users.<n>The study investigates what drives CI adoption and service selection, distinguishing need-driven from socially influenced motivations.<n>Our findings will inform researchers developing CI recommendation systems and practitioners aiming to streamline CI adoption in open-source projects.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Continuous Integration (CI) is central to modern software development, yet developers often struggle to choose the most suitable CI service. Prior work has identified barriers to CI adoption but offers little empirical evidence on how developers select CI services or whether adoption decisions are driven by genuine project needs versus social influence. This paper presents an exploratory survey study addressing that gap. We aim to contact about 5,000 active GitHub developers, including both CI users and non-users. The study investigates: (1) what drives CI adoption and service selection, distinguishing need-driven from socially influenced motivations; (2) whether developers consider CI universally necessary or context-dependent and what barriers hinder adoption; and (3) developers' perceptions of automated CI recommendation systems. Our findings will inform researchers developing CI recommendation systems and practitioners aiming to streamline CI adoption in open-source projects.
Related papers
- Evolutionary Intelligence for Scientific Discovery: From Evolutionary Computation to Cumulative Discovery Systems [52.75919264158643]
Evolutionary computation (EC) provides a computational basis for feedback-driven discovery.<n>This review introduces evolutionary intelligence (EI) for scientific discovery.<n>EI characterizes scientific AI systems that sustain exploration by linking candidate refinement with experience retention.
arXiv Detail & Related papers (2026-07-10T01:09:38Z) - A Vision for Context-Aware CI Adoption Decisions [0.0]
Continuous Integration (CI) is widely adopted in modern software development, yet adoption decisions are often made without systematic consideration of project context.<n> GitHub Actions lower the barrier to CI adoption but provide limited support for grounding adoption decisions in project characteristics.<n>This paper envisions a shift from default CI adoption to deliberate, context-aware decision-making.
arXiv Detail & Related papers (2026-04-03T22:19:11Z) - Role of CI Adoption in Mobile App Success: An Empirical Study of Open-Source Android Projects [0.0]
Continuous Integration (CI) helps automate builds, tests, and releases, but its impact on mobile development remains underexplored.<n> Existing studies mostly focus on CI adoption in general-purpose software.<n>We analyze open-source Android apps to compare CI adopters and non-adopters.
arXiv Detail & Related papers (2026-02-02T11:03:38Z) - Let the Barbarians In: How AI Can Accelerate Systems Performance Research [80.43506848683633]
We term this iterative cycle of generation, evaluation, and refinement AI-Driven Research for Systems.<n>We demonstrate that ADRS-generated solutions can match or even outperform human state-of-the-art designs.
arXiv Detail & Related papers (2025-12-16T18:51:23Z) - Barbarians at the Gate: How AI is Upending Systems Research [58.95406995634148]
We argue that systems research, long focused on designing and evaluating new performance-oriented algorithms, is particularly well-suited for AI-driven solution discovery.<n>We term this approach as AI-Driven Research for Systems ( ADRS), which iteratively generates, evaluates, and refines solutions.<n>Our results highlight both the disruptive potential and the urgent need to adapt systems research practices in the age of AI.
arXiv Detail & Related papers (2025-10-07T17:49:24Z) - Agentic Services Computing [51.50424046053763]
We propose Agentic Services Computing, a paradigm that reimagines services as autonomous, adaptive, and collaborative agents.<n>We organize ASC around a four-phase lifecycle: Design, Deployment, Operation, and Evolution.
arXiv Detail & Related papers (2025-09-29T07:29:18Z) - Cognitive Kernel-Pro: A Framework for Deep Research Agents and Agent Foundation Models Training [67.895981259683]
General AI Agents are increasingly recognized as foundational frameworks for the next generation of artificial intelligence.<n>Current agent systems are either closed-source or heavily reliant on a variety of paid APIs and proprietary tools.<n>We present Cognitive Kernel-Pro, a fully open-source and (to the maximum extent) free multi-module agent framework.
arXiv Detail & Related papers (2025-08-01T08:11:31Z) - From First Use to Final Commit: Studying the Evolution of Multi-CI Service Adoption [0.0]
We analyze the historical CI adoption of 18,924 Java projects hosted on GitHub between January 2008 and December 2024.<n>Our analysis shows that the use of multiple CI services within the same project is a recurring pattern observed in nearly one in five projects.
arXiv Detail & Related papers (2025-07-27T01:32:22Z) - On the Need to Monitor Continuous Integration Practices -- An Empirical Study [4.407128462695972]
Continuous Integration (CI) encompasses a set of widely adopted practices that enhance software development.<n>This paper explores developers' perceptions regarding the monitoring CI practices.
arXiv Detail & Related papers (2024-09-08T14:08:07Z) - The Impact of a Continuous Integration Service on the Delivery Time of
Merged Pull Requests [8.108605385023939]
We study whether adopting a CI service (TravisCI) can quicken the time to deliver merged PRs.
Our results reveal that adopting a CI service may not necessarily quicken the delivery of merge PRs.
The automation provided by CI and the boost in developers' confidence are key advantages of adopting a CI service.
arXiv Detail & Related papers (2023-05-25T10:59:35Z) - Advances and Challenges in Conversational Recommender Systems: A Survey [133.93908165922804]
We provide a systematic review of the techniques used in current conversational recommender systems (CRSs)
We summarize the key challenges of developing CRSs into five directions.
These research directions involve multiple research fields like information retrieval (IR), natural language processing (NLP), and human-computer interaction (HCI)
arXiv Detail & Related papers (2021-01-23T08:53:15Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.