The Impact of Personality on Requirements Engineering Activities: A Mixed-Methods Study

• URL: http://arxiv.org/abs/2210.07807v3
• Date: Mon, 20 Nov 2023 09:12:43 GMT
• Title: The Impact of Personality on Requirements Engineering Activities: A Mixed-Methods Study
• Authors: Dulaji Hidellaarachchi, John Grundy, Rashina Hoda, Ingo Mueller
• Abstract summary: The objective of this study is to explore and identify the impact of personality on Requirements Engineering activities. We found a range of impacts related to the personality traits of software practitioners, their team members, and external stakeholders. We found a set of strategies that can be applied to mitigate the negative impact of personality on RE activities.
• Score: 10.850726111343064
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Context: Requirements engineering (RE) is an important part of Software Engineering (SE), consisting of various human-centric activities that require the frequent collaboration of a variety of roles. Prior research has shown that personality is one such human aspect that has a huge impact on the success of a software project. However, a limited number of empirical studies exist focusing on the impact of personality on RE activities. Objective: The objective of this study is to explore and identify the impact of personality on RE activities, provide a better understanding of these impacts, and provide guidance on how to better handle these impacts in RE. Method: We used a mixed-methods approach, including a personality test-based survey (50 participants) and an in-depth interview study (15 participants) with software practitioners from around the world involved in RE activities. Results: Through personality test analysis, we found a majority of the practitioners have a high score on agreeableness and conscientiousness traits and an average score on extraversion and neuroticism traits. Through analysis of the interviews, we found a range of impacts related to the personality traits of software practitioners, their team members, and external stakeholders. These impacts can be positive or negative, depending on the RE activities, the overall software development process, and the people involved in these activities. Moreover, we found a set of strategies that can be applied to mitigate the negative impact of personality on RE activities. Conclusion: Our identified impacts of personality on RE activities and mitigation strategies serve to provide guidance to software practitioners on handling such possible personality impacts on RE activities and for researchers to investigate these impacts in greater depth in future.

Related papers

• Active Learning for Derivative-Based Global Sensitivity Analysis with Gaussian Processes [70.66864668709677]
  We consider the problem of active learning for global sensitivity analysis of expensive black-box functions. Since function evaluations are expensive, we use active learning to prioritize experimental resources where they yield the most value. We propose novel active learning acquisition functions that directly target key quantities of derivative-based global sensitivity measures.
  arXiv  Detail & Related papers  (2024-07-13T01:41:12Z)
• The Impact of Human Aspects on the Interactions Between Software Developers and End-Users in Software Engineering: A Systematic Literature Review [10.307654003138401]
  We present a systematic review of studies on human aspects affecting developer-user interactions. We identified various human aspects affecting developer-user interactions in 46 studies. Our findings suggest the importance of leveraging positive effects and addressing negative effects in developer-user interactions.
  arXiv  Detail & Related papers  (2024-05-08T03:38:36Z)
• Exploring the Relationship Between Personality Traits and User Feedback [9.289846887298852]
  We present a preliminary study about the effect of personality traits on user feedback. 56 university students provided feedback on different software features of an e-learning tool used in the course. Results suggest that sensitivity to frustration and lower stress tolerance may negatively impact the feedback of users.
  arXiv  Detail & Related papers  (2023-07-22T10:10:27Z)
• Understanding Self-Efficacy in the Context of Software Engineering: A Qualitative Study in the Industry [2.268415020650315]
  Self-efficacy is a concept researched in various areas of knowledge that impacts various factors such as performance, satisfaction, and motivation. This study aims to understand the impact on the software development context with a focus on understanding the behavioral signs of self-efficacy.
  arXiv  Detail & Related papers  (2023-05-26T17:16:37Z)
• Expanding the Role of Affective Phenomena in Multimodal Interaction Research [57.069159905961214]
  We examined over 16,000 papers from selected conferences in multimodal interaction, affective computing, and natural language processing. We identify 910 affect-related papers and present our analysis of the role of affective phenomena in these papers. We find limited research on how affect and emotion predictions might be used by AI systems to enhance machine understanding of human social behaviors and cognitive states.
  arXiv  Detail & Related papers  (2023-05-18T09:08:39Z)
• Understanding the Influence of Motivation on Requirements Engineering-related Activities [9.932667889555193]
  Requirements Engineering (RE)-related activities are critical in developing quality software. This study explores the impact of one of the most influential human aspects, motivation on RE.
  arXiv  Detail & Related papers  (2023-04-17T08:40:03Z)
• Co-Located Human-Human Interaction Analysis using Nonverbal Cues: A Survey [71.43956423427397]
  We aim to identify the nonverbal cues and computational methodologies resulting in effective performance. This survey differs from its counterparts by involving the widest spectrum of social phenomena and interaction settings. Some major observations are: the most often used nonverbal cue, computational method, interaction environment, and sensing approach are speaking activity, support vector machines, and meetings composed of 3-4 persons equipped with microphones and cameras, respectively.
  arXiv  Detail & Related papers  (2022-07-20T13:37:57Z)
• Evaluating and Inducing Personality in Pre-trained Language Models [78.19379997967191]
  We draw inspiration from psychometric studies by leveraging human personality theory as a tool for studying machine behaviors. To answer these questions, we introduce the Machine Personality Inventory (MPI) tool for studying machine behaviors. MPI follows standardized personality tests, built upon the Big Five Personality Factors (Big Five) theory and personality assessment inventories. We devise a Personality Prompting (P2) method to induce LLMs with specific personalities in a controllable way.
  arXiv  Detail & Related papers  (2022-05-20T07:32:57Z)
• Enhancing operations management through smart sensors: measuring and improving well-being, interaction and performance of logistics workers [0.0]
  The purpose of the research is to conduct an exploratory investigation of the material handling activities of an Italian logistics hub. Wearable sensors and other smart tools were used for collecting human and environmental features during working activities. Results suggest that human attitudes, interactions, emotions and environmental conditions remarkably influence workers' performance and well-being.
  arXiv  Detail & Related papers  (2021-12-15T15:40:06Z)
• The Impact of Algorithmic Risk Assessments on Human Predictions and its Analysis via Crowdsourcing Studies [79.66833203975729]
  We conduct a vignette study in which laypersons are tasked with predicting future re-arrests. Our key findings are as follows: Participants often predict that an offender will be rearrested even when they deem the likelihood of re-arrest to be well below 50%. Judicial decisions, unlike participants' predictions, depend in part on factors that are to the likelihood of re-arrest.
  arXiv  Detail & Related papers  (2021-09-03T11:09:10Z)
• Two-Faced Humans on Twitter and Facebook: Harvesting Social Multimedia for Human Personality Profiling [74.83957286553924]
  We infer the Myers-Briggs Personality Type indicators by applying a novel multi-view fusion framework, called "PERS" Our experimental results demonstrate the PERS's ability to learn from multi-view data for personality profiling by efficiently leveraging on the significantly different data arriving from diverse social multimedia sources.
  arXiv  Detail & Related papers  (2021-06-20T10:48:49Z)

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.