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Related Articles from SNS
Tokenomics: Quantifying Where Tokens Are Used in Agentic Software Engineering
Computer Science > Software Engineering [Submitted on 20 Jan 2026] Title:Tokenomics: Quantifying Where Tokens Are Used in Agentic Software Engineering View PDF HTML (experimental)Abstract:LLM-based Multi-Agent (LLM-MA) systems are increasingly applied to automate complex software engineering tasks such as requirements engineering, code generation, and testing.
TeleSWEBench: A Commit-Driven Benchmark for Evaluating LLM-Powered Software Engineering in Telecommunications
Announce Type: new Abstract: With the telecommunications field embracing zero touch management alongside novel O-RAN and AI-RAN frameworks, contemporary telecom networks now function as immensely intricate and heavily softwareized codebases. While automated software engineering (ASE) tools and Software Engineering (SWE) Agents hold the potential to alleviate the critical code generation bottleneck in this domain, their ability to navigate and modify specialized, mathematically rigorous...
Debugging the Debuggers: Failure-Anchored Structured Recovery for Software Engineering Agents
arXiv:2605.08717v2 Announce Type: replace Abstract: Software engineering agents are increasingly deployed in evaluable engineering environments, yet post-failure recovery remains costly, manual, and ad hoc. Existing systems expose traces or generate follow-up feedback, but they do not convert heterogeneous runtime evidence into grounded, bounded recovery guidance for a subsequent attempt. We present PROBE, a failure-anchored framework for structured recovery in software engineering agents.
How Software Engineering Students Use LLMs to Write Research Papers: An Experience Report
arXiv:2606.05114v2 Announce Type: replace Abstract: Large language models are increasingly becoming part of software engineering education, including activities involving empirical software engineering and evidence synthesis. This paper reports an educational experience involving the integration of reflective LLM use into an empirical methods assignment in a third-year software architecture course. Students were asked to develop a short research paper using either a rapid review or a gray...
How Software Engineering Students Use LLMs to Write Research Papers: An Experience Report
arXiv:2606.05114v1 Announce Type: new Abstract: Large language models are increasingly becoming part of software engineering education, including activities involving empirical software engineering and evidence synthesis. This paper reports an educational experience involving the integration of reflective LLM use into an empirical methods assignment in a third-year software architecture course. Students were asked to develop a short research paper using either a rapid review or a gray...
The End of Software Engineering: How AI Agents Are Fundamentally Restructuring the Software Paradigm
arXiv:2606.05608v1 Announce Type: new Abstract: For over half a century, software engineering has operated on a foundational premise: human engineers decompose problems, encode decision logic into static code, and manually adapt that code as requirements evolve. This paper argues that the emergence of AI agents -- systems where large language models serve as the primary reasoning engine, dynamically generating and discarding code as an instrumental resource -- constitutes not an incremental...
Trustworthy AI Software Engineers
arXiv:2602.06310v2 Announce Type: replace Abstract: With the rapid rise of AI coding agents, the fundamental premise of what it means to be a software engineer is in question. In this vision paper, we examine what it means for an AI agent to be considered a software engineer and then critically think about what makes such an agent trustworthy. Grounded in established definitions of SE (SE) and informed by recent research on agentic AI systems, we conceptualise AI software engineers as...
Human Oversight and Overload: Two Hidden and Costly Burdens of AI-Assisted Software Engineering
arXiv:2606.05770v1 Announce Type: new Abstract: AI is changing how software engineers work, but it often comes with hidden burdens and costs. In this paper, we characterize two such often-overlooked burdens: (1) the constant need for human oversight and inspection of AI-generated artifacts; and (2) the growing cognitive overload on software engineers from receiving large amounts of suggestions from AI tools. The need for human oversight is not optional-engineers must review, validate, and...
Piramidal (YC W24) – Software Engineers – NYC Onsite
We're looking for senior software engineers - frontend, backend, and infra - who are excited about solving difficult problems at the boundary of Foundational AI and Neuroscience. Our core backend and infra stack is Python, Go, and Terraform deployed to various cloud and on-prem, while our frontend stack is React and TypeScript. Bonus points for either: standing up and maintaining reliable streaming systems with a production/ops mindset; or building smooth, data-intensive React UIs with...
Human-AI Collaboration and the Transformation of Software Engineering Work
Announce Type: new Abstract: The integration of Generative AI (GenAI) and Agentic AI into software development is reconfiguring software engineering from an activity centered on human authorship of code into a discipline centered on directing, verifying, and governing autonomous and semi-autonomous systems. Drawing on a curated, multi-source evidence base of recent peer-reviewed and archival studies -- including large-scale empirical observations of autonomous coding agents contributing...