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<p>Design Pattern Detection (DPD) tools are useful to support to the comprehension and maintenance of software systems. Although several DPD tools have been introduced over the years, they typically focus on a limited set of design patterns and programming languages. This paper aims to investigate (i) the reasons that motivate DPD tool designers to target specific design patterns and programming languages, and (ii) how potential users perceive the usefulness of DPD tools in practical software development scenarios. We conducted two online surveys. For the first survey, we reached out to designers of 42 DPD tools selected from a systematic literature review to obtain their perspectives on design decisions about pattern and language coverage, receiving 22% of such responses. For the second survey, we recruited 28 student and senior developers to help us understand their expectations, perceived benefits, and concerns related to the use of DPD tools. Within our sample, the findings suggest that participating tool designers often prioritize design patterns whose internal structure facilitates automated detection, while language support is frequently motivated by popularity and expected demand. From the perspective of tool users, DPD tools are expected to support development activities, such as program comprehension and software quality improvement. Unfortunately, usability difficulties, limited accuracy, and insufficient documentation often discourage them from adopting a tool. The responses suggest that some design decisions reported by participating DPD tool designers are aligned with practical and industrial considerations. However, the recurring lack of adequate documentation and usability support is a major barrier to wider usage. Taken as indicative evidence, these results suggest that future DPD tools should better balance detection capabilities and usability concerns, especially to meet the need of less experienced developers. Given the limited number of tool-designer respondents, conclusions about design rationale should be interpreted as indicative rather than representative of all DPD tool designers.</p>

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Understanding the developer and user perspectives of design pattern detection tools

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月22日

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  • Rodrigo Moreira,
  • Eduardo Fernandes,
  • Eduardo Figueiredo,
  • Filipe Fernandes

摘要

Design Pattern Detection (DPD) tools are useful to support to the comprehension and maintenance of software systems. Although several DPD tools have been introduced over the years, they typically focus on a limited set of design patterns and programming languages. This paper aims to investigate (i) the reasons that motivate DPD tool designers to target specific design patterns and programming languages, and (ii) how potential users perceive the usefulness of DPD tools in practical software development scenarios. We conducted two online surveys. For the first survey, we reached out to designers of 42 DPD tools selected from a systematic literature review to obtain their perspectives on design decisions about pattern and language coverage, receiving 22% of such responses. For the second survey, we recruited 28 student and senior developers to help us understand their expectations, perceived benefits, and concerns related to the use of DPD tools. Within our sample, the findings suggest that participating tool designers often prioritize design patterns whose internal structure facilitates automated detection, while language support is frequently motivated by popularity and expected demand. From the perspective of tool users, DPD tools are expected to support development activities, such as program comprehension and software quality improvement. Unfortunately, usability difficulties, limited accuracy, and insufficient documentation often discourage them from adopting a tool. The responses suggest that some design decisions reported by participating DPD tool designers are aligned with practical and industrial considerations. However, the recurring lack of adequate documentation and usability support is a major barrier to wider usage. Taken as indicative evidence, these results suggest that future DPD tools should better balance detection capabilities and usability concerns, especially to meet the need of less experienced developers. Given the limited number of tool-designer respondents, conclusions about design rationale should be interpreted as indicative rather than representative of all DPD tool designers.