Resist the Hype! Practical Recommendations to Cope With R\'esum\'e-Driven Development

• URL: http://arxiv.org/abs/2307.02850v1
• Date: Thu, 6 Jul 2023 08:32:38 GMT
• Title: Resist the Hype! Practical Recommendations to Cope With R\'esum\'e-Driven Development
• Authors: Jonas Fritzsch, Marvin Wyrich, Justus Bogner, Stefan Wagner
• Abstract summary: We find empirical support for a tendency to overemphasize technology trends in r'esum'es and the application process. Among the software professionals, 82% believed that using trending technologies in their daily work would make them more attractive for potential future employers.
• Score: 14.241792326365088
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Technology trends play an important role in the hiring process for software and IT professionals. In a recent study of 591 software professionals in both hiring (130) and technical (558) roles, we found empirical support for a tendency to overemphasize technology trends in r\'esum\'es and the application process. 60% of the hiring professionals agreed that such trends would influence their job advertisements. Among the software professionals, 82% believed that using trending technologies in their daily work would make them more attractive for potential future employers. This phenomenon has previously been reported anecdotally and somewhat humorously under the label R\'esum\'e-Driven Development (RDD). Our article seeks to initiate a more serious debate about the consequences of RDD on software development practice. We explain how the phenomenon may constitute a harmful self-sustaining dynamic, and provide practical recommendations for both the hiring and applicant perspectives to change the current situation for the better.

Related papers

• Identifying Factors Contributing to Bad Days for Software Developers: A Mixed Methods Study [1.1545092788508224]
  The presence of friction can significantly hinder productivity, increase frustration, and contribute to low morale among developers. This research employed a mixed-method approach, including interviews, surveys, diary studies, and analysis of developer telemetry data. Findings revealed factors that cause "bad days" for developers and significantly impact their work and well-being.
  arXiv  Detail & Related papers  (2024-10-24T02:43:33Z)
• Dear Diary: A randomized controlled trial of Generative AI coding tools in the workplace [2.5280615594444567]
  Generative AI coding tools are relatively new, and their impact on developers extends beyond traditional coding metrics. This study aims to illuminate developers' preexisting beliefs about generative AI tools, their self perceptions, and how regular use of these tools may alter these beliefs. Our findings reveal that the introduction and sustained use of generative AI coding tools significantly increases developers' perceptions of these tools as both useful and enjoyable.
  arXiv  Detail & Related papers  (2024-10-24T00:07:27Z)
• Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking [59.87055275344965]
  Job-SDF is a dataset designed to train and benchmark job-skill demand forecasting models. Based on 10.35 million public job advertisements collected from major online recruitment platforms in China between 2021 and 2023. Our dataset uniquely enables evaluating skill demand forecasting models at various granularities, including occupation, company, and regional levels.
  arXiv  Detail & Related papers  (2024-06-17T07:22:51Z)
• Beyond Trend Following: Deep Learning for Market Trend Prediction [49.89480853499917]
  We advocate for the use of Artificial Intelligence and Machine Learning techniques to predict future market trends. These predictions, when done properly, can improve the performance of asset managers by increasing returns and reducing drawdowns.
  arXiv  Detail & Related papers  (2024-06-10T11:42:30Z)
• Fairness in AI-Driven Recruitment: Challenges, Metrics, Methods, and Future Directions [0.0]
  Big data and machine learning has led to a rapid transformation in the traditional recruitment process. Given the prevalence of AI-based recruitment, there is growing concern that human biases may carry over to decisions made by these systems. This paper provides a comprehensive overview of this emerging field by discussing the types of biases encountered in AI-driven recruitment.
  arXiv  Detail & Related papers  (2024-05-30T05:25:14Z)
• LLM-based Interaction for Content Generation: A Case Study on the Perception of Employees in an IT department [85.1523466539595]
  This paper presents a questionnaire survey to identify the intention to use generative tools by employees of an IT company. Our results indicate a rather average acceptability of generative tools, although the more useful the tool is perceived to be, the higher the intention seems to be. Our analyses suggest that the frequency of use of generative tools is likely to be a key factor in understanding how employees perceive these tools in the context of their work.
  arXiv  Detail & Related papers  (2023-04-18T15:35:43Z)
• Policy Gradients Incorporating the Future [66.20567145291342]
  We introduce a method that allows an agent to "look into the future" without explicitly predicting it. We propose to allow an agent, during its training on past experience, to observe what emphactually happened in the future at that time. This gives our agent the opportunity to utilize rich and useful information about the future trajectory dynamics in addition to the present.
  arXiv  Detail & Related papers  (2021-08-04T14:57:11Z)
• R\'esum\'e-Driven Development: A Definition and Empirical Characterization [14.241792326365088]
  R'esum'e-Driven Development describes the overemphasis of trending technologies in both job offerings and resumes. We empirically investigated this phenomenon by surveying 591 software professionals in both hiring (130) and technical (558) roles.
  arXiv  Detail & Related papers  (2021-01-29T17:41:37Z)
• Optimizing Deep Learning Recommender Systems' Training On CPU Cluster Architectures [56.69373580921888]
  We focus on Recommender Systems which account for most of the AI cycles in cloud computing centers. By enabling it to run on latest CPU hardware and software tailored for HPC, we are able to achieve more than two-orders of magnitude improvement in performance.
  arXiv  Detail & Related papers  (2020-05-10T14:40:16Z)
• Is 40 the new 60? How popular media portrays the employability of older software developers [78.42660996736939]
  We analyzed popular online articles and related discussions on Hacker News through the lens of employability issues and potential mitigation strategies. We highlight the importance of keeping up-to-date, specializing in certain tasks or technologies, and present role transitions as a way forward for veteran developers.
  arXiv  Detail & Related papers  (2020-04-13T10:00:03Z)

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.