What rationales drive architectural decisions? An empirical inquiry

• URL: http://arxiv.org/abs/2309.14164v1
• Date: Mon, 25 Sep 2023 14:18:51 GMT
• Title: What rationales drive architectural decisions? An empirical inquiry
• Authors: Klara Borowa, Rafa{\l} Lewanczyk, Klaudia Stpiczy\'nska, Patryk Stradomski, Andrzej Zalewski
• Abstract summary: There is a rationale behind every architectural decision that motivates an architect to choose one architectural solution out of a set of options. This study aims to identify which categories of rationale most frequently impact architectural decisions and investigates why these are important to practitioners.
• Score: 0.7499722271664147
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Architectural decision-making is a crucial concern for researchers and practitioners alike. There is a rationale behind every architectural decision that motivates an architect to choose one architectural solution out of a set of options. This study aims to identify which categories of rationale most frequently impact architectural decisions and investigates why these are important to practitioners. Our research comprises two steps of empirical inquiry: a questionnaire (63 participants) and 13 interviews. As a result, we obtained a set of rationales that motivated architects' decisions in practice. Out of them, we extracted a list of software quality attributes that practitioners were the most concerned about. We found that, overall, architects prefer to choose solutions which are familiar to them or that guarantee fast software implementation. Mid-career architects (5 to 15 years of experience) are more open to new solutions than senior and junior practitioners. Additionally, we found that most practitioners are not concerned about the quality attributes of compatibility and portability due to modern software development practices, such as the prevalence of using specific standards and virtualisation/containerization.

Related papers

• How Do OSS Developers Utilize Architectural Solutions from Q&A Sites: An Empirical Study [5.568316292260523]
  Developers utilize programming-related knowledge (e.g., code snippets) on Q&A sites (e.g., Stack Overflow) architectural solutions (e.g., architecture tactics) and their utilization are rarely explored. For the mining study, we mined 984 commits and issues (i.e., 821 commits and 163 issues) from 893 Open-Source Software (OSS) projects on GitHub. For the survey study, we surveyed 227 of them to further understand how practitioners utilize architectural solutions from Q&A sites in their OSS development.
  arXiv  Detail & Related papers  (2024-04-07T18:53:30Z)
• The Presence and the State-of-Practice of Software Architects in the Brazilian Industry - A Survey [1.3392307634669538]
  The aim of this work is to understand the characteristics of the companies regarding the presence or absence of software architects in Brazil. The study collected data from 105 professionals distributed in 24 Brazilian states.
  arXiv  Detail & Related papers  (2024-03-01T20:10:37Z)
• Towards Assessing Spread in Sets of Software Architecture Designs [2.2120851074630177]
  We propose a quality indicator for the spread that assesses the diversity of alternatives by taking into account architectural features. We demonstrate how our architectural quality indicator can be applied to a dataset from the literature.
  arXiv  Detail & Related papers  (2024-02-29T13:52:39Z)
• Architecture Knowledge Representation and Communication Industry Survey [0.0]
  We aim to understand the current practice in architecture knowledge, and to explore where sustainability can be applied to address sustainability in software architecture in the future. We used a survey, which utilized a questionnaire containing 34 questions and collected responses from 45 architects working at a prominent bank in the Netherlands.
  arXiv  Detail & Related papers  (2023-09-20T18:17:16Z)
• Risk-reducing design and operations toolkit: 90 strategies for managing risk and uncertainty in decision problems [65.268245109828]
  This paper develops a catalog of such strategies and develops a framework for them. It argues that they provide an efficient response to decision problems that are seemingly intractable due to high uncertainty. It then proposes a framework to incorporate them into decision theory using multi-objective optimization.
  arXiv  Detail & Related papers  (2023-09-06T16:14:32Z)
• Learning From Each Other: How Are Architectural Mistakes Communicated in Industry? [1.5839621757142597]
  This study investigates the handling and particularly communication of mistakes by software architects. We identified software architects' definitions of architectural mistakes, their handling of these mistakes, and their preferred communication strategies regarding these mistakes. We found that architects communicate mistakes mainly within their project teams and seldom within or across companies.
  arXiv  Detail & Related papers  (2023-07-10T11:37:15Z)
• PyRCA: A Library for Metric-based Root Cause Analysis [66.72542200701807]
  PyRCA is an open-source machine learning library of Root Cause Analysis (RCA) for Artificial Intelligence for IT Operations (AIOps) It provides a holistic framework to uncover the complicated metric causal dependencies and automatically locate root causes of incidents.
  arXiv  Detail & Related papers  (2023-06-20T09:55:10Z)
• On solving decision and risk management problems subject to uncertainty [91.3755431537592]
  Uncertainty is a pervasive challenge in decision and risk management. This paper develops a systematic understanding of such strategies, determine their range of application, and develop a framework to better employ them.
  arXiv  Detail & Related papers  (2023-01-18T19:16:23Z)
• Investigating Positive and Negative Qualities of Human-in-the-Loop Optimization for Designing Interaction Techniques [55.492211642128446]
  Designers reportedly struggle with design optimization tasks where they are asked to find a combination of design parameters that maximizes a given set of objectives. Model-based computational design algorithms assist designers by generating design examples during design. Black box methods for assistance, on the other hand, can work with any design problem.
  arXiv  Detail & Related papers  (2022-04-15T20:40:43Z)
• Leveraging Expert Consistency to Improve Algorithmic Decision Support [62.61153549123407]
  We explore the use of historical expert decisions as a rich source of information that can be combined with observed outcomes to narrow the construct gap. We propose an influence function-based methodology to estimate expert consistency indirectly when each case in the data is assessed by a single expert. Our empirical evaluation, using simulations in a clinical setting and real-world data from the child welfare domain, indicates that the proposed approach successfully narrows the construct gap.
  arXiv  Detail & Related papers  (2021-01-24T05:40:29Z)
• RC-DARTS: Resource Constrained Differentiable Architecture Search [162.7199952019152]
  We propose the resource constrained differentiable architecture search (RC-DARTS) method to learn architectures that are significantly smaller and faster. We show that the RC-DARTS method learns lightweight neural architectures which have smaller model size and lower computational complexity.
  arXiv  Detail & Related papers  (2019-12-30T05:02:38Z)

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.