Technostress in the Age of AI: A Preliminary Study with Software Professionals
研究通过调查26国121位软件专业人士,探讨了AI引发的技术压力问题及其对工作、职责和个人职业规划的影响。
研究通过调查26国121位软件专业人士,探讨了AI引发的技术压力问题及其对工作、职责和个人职业规划的影响。
本文讨论了生成式AI对软件开发的影响,指出虽然AI增加了代码生成的可访问性,但控制权可能更加集中。研究强调了意图规范、行为评估和系统集成方面的新需求。
本文通过多元文献综述法,探讨了量子软件测试在学术和实践中的特点及挑战,揭示了现有方法的碎片化及工具生态不成熟等问题。
This study addresses the limited flight endurance and adverse aerodynamic effects experienced by micro-rotorcraft during low-altitude indoor operations. To overcome these challenges, the authors propose a lightweight, custom-designed shroud that endows the Crazyflie 2.1 platform with dual-mode capability—efficient ground-effect (cushion) flight and conventional free-flight. Leveraging thin-wall thermoforming fabrication, parametric geometric evaluation, empirical force modeling, and automated data collection, the optimized shroud significantly enhances beneficial ground effect while mitigating the detrimental suction effect at intermediate heights. Experimental results demonstrate that the refined configuration achieves nearly a threefold increase in lift within ground effect, extends hover endurance by 60% on a single charge, and incurs only a 30% reduction in free-flight duration. Moreover, the system enables stable transitions between flight modes and accurate trajectory tracking.
This study systematically identifies and differentiates functional dependency, overreliance, and addiction-like behaviors in the use of large language models (LLMs) within software engineering. Through a survey of 119 software practitioners, complemented by descriptive statistics and thematic analysis of open-ended responses, the research reveals that LLMs have become deeply integrated into development workflows. Most developers exhibit functional dependency, leveraging LLMs as productive tools without impairment. Overreliance manifests as a preference for consulting LLMs over official documentation or colleagues, potentially compromising solution quality. Addiction-like behaviors are relatively rare but characterized by difficulties in usage moderation and emotional attachment. The findings provide an empirical foundation and a behavioral classification framework for understanding the nuanced impacts of LLM adoption in software development.
研究通过调查26国121位软件专业人士,探讨了AI引发的技术压力问题及其对工作、职责和个人职业规划的影响。
本文讨论了生成式AI对软件开发的影响,指出虽然AI增加了代码生成的可访问性,但控制权可能更加集中。研究强调了意图规范、行为评估和系统集成方面的新需求。
本文通过多元文献综述法,探讨了量子软件测试在学术和实践中的特点及挑战,揭示了现有方法的碎片化及工具生态不成熟等问题。
This study addresses the limited flight endurance and adverse aerodynamic effects experienced by micro-rotorcraft during low-altitude indoor operations. To overcome these challenges, the authors propose a lightweight, custom-designed shroud that endows the Crazyflie 2.1 platform with dual-mode capability—efficient ground-effect (cushion) flight and conventional free-flight. Leveraging thin-wall thermoforming fabrication, parametric geometric evaluation, empirical force modeling, and automated data collection, the optimized shroud significantly enhances beneficial ground effect while mitigating the detrimental suction effect at intermediate heights. Experimental results demonstrate that the refined configuration achieves nearly a threefold increase in lift within ground effect, extends hover endurance by 60% on a single charge, and incurs only a 30% reduction in free-flight duration. Moreover, the system enables stable transitions between flight modes and accurate trajectory tracking.
This study systematically identifies and differentiates functional dependency, overreliance, and addiction-like behaviors in the use of large language models (LLMs) within software engineering. Through a survey of 119 software practitioners, complemented by descriptive statistics and thematic analysis of open-ended responses, the research reveals that LLMs have become deeply integrated into development workflows. Most developers exhibit functional dependency, leveraging LLMs as productive tools without impairment. Overreliance manifests as a preference for consulting LLMs over official documentation or colleagues, potentially compromising solution quality. Addiction-like behaviors are relatively rare but characterized by difficulties in usage moderation and emotional attachment. The findings provide an empirical foundation and a behavioral classification framework for understanding the nuanced impacts of LLM adoption in software development.