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software engineering

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AI4SE and SE4AI Exploration: A Decade Review Identifies Research Gaps for Enterprise Tech Leaders Technology
Artificial Intelligence #ai#software engineering

AI4SE and SE4AI Exploration: A Decade Review Identifies Research Gaps for Enterprise Tech Leaders

A new paper on arXiv traces a decade of progress in AI for systems engineering (AI4SE) and SE for AI (SE4AI). Using human and AI raters, it reviewed 1,712 INCOSE INSIGHT articles and 889 SERC publications, identifying five critical research gaps. The authors also launched an interactive web application for practitioners.

Jul 8, 2026 1 source
Meta's RADAR Automates Low-Risk Code Review, Cutting Review Time by 330% Technology
Software #automation#code review

Meta's RADAR Automates Low-Risk Code Review, Cutting Review Time by 330%

Meta has deployed RADAR, a multi-funnel automated system that risk-stratifies code diffs to accelerate low-risk reviews. The system has reviewed over 535,000 diffs and landed 331,000+, reducing median time to close by over 330% and median review wall time by 35%, while achieving a production incident rate 1/50 that of non-RADAR diffs.

Jun 16, 2026 1 source
Open-SWE-Traces: 207K Multilingual Trajectories Set New Standard for Autonomous Software Engineering Agents Technology
Artificial Intelligence #ai#artificial intelligence

Open-SWE-Traces: 207K Multilingual Trajectories Set New Standard for Autonomous Software Engineering Agents

Researchers have released Open-SWE-Traces, a dataset of 207,489 software engineering agent trajectories spanning nine programming languages, sourced from 20,000 real-world pull requests. Fine-tuning on this data yields models that achieve state-of-the-art resolve rates on multiple SWE-bench benchmarks, advancing autonomous software engineering.

Jun 16, 2026 1 source
LLMs Are Eroding a Senior Software Engineer’s Career — What Enterprise Leaders Need to Know Technology
Artificial Intelligence #llms#software engineering

LLMs Are Eroding a Senior Software Engineer’s Career — What Enterprise Leaders Need to Know

A senior software engineer with a decade of experience in finance and payments describes how large language models (LLMs) have made his hard-won domain knowledge and debugging skills feel obsolete. The blog post, published June 2026, details how even distributed systems debugging — once considered a safe haven — is now performed competently by AI agents. For enterprise technology leaders, the account signals a need to rethink talent retention, career progression, and the future value of deep specialization in software engineering.

Jun 14, 2026 1 source