design the review protocol through five main stages, as shown in Fig. 2. Adopting the PRISMA framework ensures systematic review transparency and rigor [25]. Previous studies in urban research, like [26,27] have successfully employed PRISMA, demonstrating its effectiveness in guiding the review process and enhancing the quality of evidence synthesis. By adopting this methodology, this study aligns with best practices in the field and contributes to a more robust understanding of the integration of visual programming within computational BIM.
通过五个主要阶段设计审查方案，如图2所示。采用PRISMA框架可确保系统性审评的透明度和严谨性[25]。以前的城市研究中的研究，如[26，27]已经成功地使用了PRISMA，证明了它在指导审查过程和提高证据合成质量方面的有效性。通过采用这种方法，本研究与该领域的最佳实践保持一致，并有助于更好地理解计算BIM中的可视化编程集成。

Search keywords were selected based on the research objectives during the first and second stages (the scoping and identification). Previous review papers $[10,28]$$[10,28]$[10,28][10,28] with similar topics were used to identify specific keywords to make the search more effective. The final search keywords were then combined by Boolean operations as follows: (“BIM” OR “Building Information Model*” OR “Computational BIM” OR “Computational Building Information Model*”) AND (“visual programming language” OR “visual programming” OR “VP” OR “visual scripting” OR “grasshopper” OR “Dynamo” OR “Marionette” OR “GenerativeComponents”). The symbol “*” implies a fuzzy search. The selected search field was “Title/Abstract/Keyword”, and the initial search process was performed using Scopus and ISI Web of Science (WOS) databases because these databases provide peer-reviewed indexed publications well-regarded by researchers worldwide. The search publication date was not constrained to any period to cover as many papers as possible because the application of computational BIM is a relatively new topic that emerged last decade, according to the review paper of Liu et al. [20].
根据第一和第二阶段（范围界定和识别）的研究目标选择检索关键词。使用具有相似主题的既往综述论文 $[10,28]$$[10,28]$[10,28][10,28] 识别特定关键词，以使检索更有效。然后通过布尔运算将最终的搜索关键词组合如下：（“BIM”OR“Building Information Model*”OR“Computational BIM”OR“Computational Building Information Model*”）AND（“visual programming language”OR“visual programming”OR“VP”OR“visual scripting”OR“grasshopper”OR“Dynamo”OR“Marionette”OR“GenerativeComponents”）。符号“*”表示模糊搜索。选择的检索字段为“标题/摘要/关键词”，使用Scopus和ISI Web of Science（WOS）数据库进行初始检索，因为这些数据库提供了全球研究人员公认的同行评审索引出版物。 根据Liu等人的评论论文，检索出版日期不限于任何时期，以涵盖尽可能多的论文，因为计算BIM的应用是近十年出现的一个相对较新的主题。[20]。

The initial search results recorded 269 and 157 papers in Scopus and WOS, respectively. The first published document related to the search criteria was a conference paper published in 2012 and a journal article published in 2014. The total record from the previous step ( $n=426$$n=426$n=426n=426 ) was then screened and filtered using the functionalities of the search databases, and therefore 307 papers were excluded ( 74 duplicates, 14 papers not in English, 219 papers not original journal papers). Similarly, several previous systematic review papers [29,30] included only journal articles because they are thoroughly peer-reviewed and accepted as the highest quality of academic contribution.
最初的检索结果分别在Scopus和WOS中记录了269篇和157篇论文。与检索标准相关的第一篇发表文献是2012年发表的会议论文和2014年发表的期刊文章。然后使用检索数据库的功能筛选和过滤上一步骤（ $n=426$$n=426$n=426n=426 ）的总记录，因此排除了307篇论文（74篇重复论文，14篇非英文论文，219篇非原始期刊论文）。同样，之前的几篇系统性综述论文[29，30]只包括期刊文章，因为它们经过了彻底的同行评审，并被认为是最高质量的学术贡献。

The included papers from the previous stage ( $n=119$$n=119$n=119n=119 ) were then screened for eligibility using the title and abstract of each article. As a result, 26 articles were excluded based on their titles $(\mathrm{n}=5)$$(\mathrm{n}=5)$(n=5)(\mathrm{n}=5) and abstract ( $\mathrm{n}=21$$\mathrm{n}=21$n=21\mathrm{n}=21 ) because they deal with research problems unrelated to building projects, such as infrastructure or computational BIM application in education. Accordingly, only 93 articles were selected for eligibility screening using the full text. This stage showed that the full text of 6 articles was not available; therefore, they were excluded. Additionally, the screening of the full text of 93 papers revealed that eight papers are out of the scope of this research. For instance, several papers focused on developing a new computational BIM platform rather than using computational BIM to propose a new method, tool, or workflow to solve a building-related problem. As a result, only 79 papers are included in the current systematic review paper.
然后使用每篇文章的标题和摘要筛选前一阶段（ $n=119$$n=119$n=119n=119 ）纳入的论文的合格性。因此，26篇文章因标题 $(\mathrm{n}=5)$$(\mathrm{n}=5)$(n=5)(\mathrm{n}=5) 和摘要（ $\mathrm{n}=21$$\mathrm{n}=21$n=21\mathrm{n}=21 ）而被排除，因为它们涉及与建筑项目无关的研究问题，例如基础设施或计算BIM在教育中的应用。因此，仅选择了93篇文章进行使用全文的合格性筛选。该阶段显示，6篇文章的全文不可用;因此，将其排除。此外，对93篇论文的全文进行筛选，发现8篇论文不在本研究范围内。例如，有几篇论文专注于开发新的计算BIM平台，而不是使用计算BIM提出新的方法，工具或工作流程来解决建筑相关问题。因此，只有79篇论文被纳入当前的系统综述论文。

Following the selection of the 79 papers for review, a descriptive statistical analysis was conducted, which included annual publication trends, country distributions, journal distributions and high-yielding authors. Next, the VOSviewer software was used for scientometrics analysis, including the keyword co-occurrence network and developing a cooperative network between authors. In addition to VOSviewer, other bibliometric analysis software used in research include Citespace [31] and Gephi [32]. However, VOSviewer is better suited for visualizing more extensive networks than other bibliometric software and includes special text mining capabilities [33]. Furthermore, VOSviewer is increasingly being used to aid in the review of literature in the field of AECO research, such as modular construction [34,35], construction progress monitoring [36] and BIM for LCA [37]. As a result, VOSviewer
在选择79篇论文进行综述后，进行了描述性统计分析，其中包括年度出版趋势、国家分布、期刊分布和高产作者。其次，使用VOSviewer软件进行科学计量学分析，包括关键词共现网络和开发作者之间的合作网络。除了VOSviewer，其他用于研究的文献计量分析软件包括Citespace [31]和Gephi [32]。然而，VOSviewer比其他文献计量软件更适合可视化更广泛的网络，并包括特殊的文本挖掘功能[33]。此外，VOSviewer越来越多地用于帮助AECO研究领域的文献综述，例如模块化建筑[34，35]，施工进度监控[36]和LCA BIM [37]。因此，VOSviewer
was used to analyze co-authorship (section 3.5.1) and keywords (section 3.5.2), as recommended by Park and Nagy [38]. Finally, content analysis summarised the current key research topics, and in-depth discussions were conducted. A research framework was then developed to identify gaps and future directions for computational BIM applications in building research.
根据Park和Nagy [38]的建议，用于分析共同作者（第3.5.1节）和关键词（第3.5.2节）。最后，内容分析总结了当前的重点研究课题，并进行了深入的讨论。然后开发了一个研究框架，以确定建筑研究中计算BIM应用的差距和未来方向。

Fig. 3 depicts the trends in publishing papers on computational BIM in building research. A total of 79 journal articles have been published between 2014 and 2022 (retrieval date till May 2022). The first related journal article appeared in 2014, indicating that computational BIM application in the building research field is still in its infancy. In addition, the number of articles has begun to rise since 2019. Most articles were published in 2021 when there were 24 publications, more than twice as many as in 2019. However, Fig. 3 indicated that fewer papers were published in 2022 than in 2021; this may be the case because the 2022 data is only available up until the retrieval date of May 2022, which only covers five months out of the year. More papers will likely be published in 2022 than in prior years, as there has been significant interest in computational BIM in the AECO industry.
图3描述了建筑研究中有关计算BIM的论文发表趋势。2014年至2022年期间共发表了79篇期刊文章（检索日期至2022年5月）。第一篇相关期刊文章出现在2014年，表明计算BIM在建筑研究领域的应用仍处于起步阶段。此外，文章数量从2019年开始上升。大部分文章发表于2021年，当时有24篇发表，是2019年的两倍多。然而，图3显示，2022年发表的论文比2021年少;这可能是因为2022年的数据仅在2022年5月的检索日期之前可用，该日期仅涵盖全年的五个月。2022年发表的论文可能会比往年更多，因为AECO行业对计算BIM有着浓厚的兴趣。

A statistical analysis of journals can assist readers in obtaining the most up-to-date information and identifying journals that may be useful for future reference. The distribution of the 79 publications throughout the 39 journals is depicted in Fig. 4. Notably, Automation in Construction produced the most papers with a total number of 10; next up are Buildings (7), Sustainability (Switzerland) (6), and Journal of Information Technology Construction (5), indicating that these are the foremost journals in this field of study.
期刊的统计分析可以帮助读者获得最新的信息，并确定可能对未来参考有用的期刊。79篇出版物在39种期刊中的分布如图4所示。值得注意的是，建筑自动化产生了最多的论文，总数为10篇;其次是建筑（7篇），可持续性（瑞士）（6篇）和信息技术建筑杂志（5篇），这表明这些是该研究领域最重要的期刊。

Regarding the author institutions’ geographic distribution, 23 contributing countries/regions are identified. The top three most productive countries/regions presented in Table 1 are Italy, the United States, and Japan. Italy publishes the most articles (15), followed by the United States (9) and Japan (7). More than $40\mathrm{\%}$$40\mathrm{\%}$40%40 \% of all papers (31 of 79) were published in these three countries.
关于作者机构的地理分布，确定了23个贡献国家/地区。表1所列的生产率最高的前三个国家/地区是意大利、美国和日本。意大利发表的文章最多（15篇），其次是美国（9篇）和日本（7篇）。超过 $40\mathrm{\%}$$40\mathrm{\%}$40%40 \% 篇论文（79篇中的31篇）在这三个国家发表。

Fig. 3. Number and years of the reviewed published papers.
图3.发表论文的数量和年份。

Fig. 4. Journal publications and the number of papers published.
图4.期刊出版物和发表论文的数量。

Table 1  表1
The top 10 most productive countries/regions.
生产力最高的10个国家/地区。

The citations of the publications can indicate the trend and research impact of the reviewed topic [35] and better represent the eminent authors in this field. Table 2 displays the top 10 cited articles from the 79 publications. Among the highly cited articles are authors who applied computational BIM to develop new methods to study building performance; these articles were classified under the research theme of “Building Performance Analysis (BPA)”. In comparison, two publications were classified as research themes on “Design Optimization” and “Facility Management”, respectively. There is also a research theme on “project management”.
出版物的引用可以表明评论主题的趋势和研究影响[35]，并更好地代表该领域的杰出作者。表2显示了79篇出版物中引用次数最多的10篇文章。被引用次数较多的文章中，作者应用计算BIM开发了研究建筑性能的新方法;这些文章被归类为“建筑性能分析（BPA）”的研究主题。相比之下，两份出版物分别被归类为“设计优化”和“设施管理”的研究主题。还有一个关于“项目管理”的研究主题。

The results of the scientometric analysis are presented in this section. In addition, bibliometric analysis was performed on all 79 articles collected to understand the current state and evolution of knowledge around computational BIM topics in the AECO industry.
本节介绍了科学计量分析的结果。此外，对收集的所有79篇文章进行了文献计量分析，以了解AECO行业中计算BIM主题的知识现状和演变。

A co-authorship network is defined as a graph in which the nodes are the authors, and there is an edge between two authors (nodes) if they have published a paper together. Fig. 5 displays the findings of the coauthor analysis performed on the 79 chosen articles using the VOSviewer toolkit. The size of the circles corresponds to the number of
合著网络被定义为一个图，其中的节点是作者，如果两个作者（节点）一起发表论文，则他们之间存在边。图5显示了使用VOSviewer工具包对79篇选定文章进行的合著者分析的结果。圆圈的大小对应于
papers published on the target topic by each author. The year is symbolized by the colour of a circle. As shown in Fig. 5, some research teams are more productive in this field than others. For instance, the research teams led by Cheng, Wang, and Gan developed a strong network of collaboration. It is also worth noting that several collaboration networks began to emerge in 2020. Overall, the computational BIM application in building research showed a pattern of constant expansion and diversification. However, there is still room for improvement and strengthening in the collaboration between authors from various countries/ regions.
每个作者发表的关于目标主题的论文。一年是由一个圆圈的颜色来象征的。如图5所示，一些研究团队在这一领域比其他团队更富有成效。例如，由Cheng，Wang和Gan领导的研究团队开发了一个强大的合作网络。同样值得注意的是，2020年开始出现多个协作网络。总体而言，计算BIM在建筑研究中的应用呈现出不断扩展和多样化的模式。然而，在不同国家/地区的作者之间的合作方面仍有改进和加强的余地。

Keywords help to summarize the content of literature studies. It represents the key findings of existing research and related topics in a specific domain. The minimum number of occurrences was set to two when mapping a co-occurrence network in the VOSviewer toolkit using author keywords. Keywords with the same or similar meanings and singular or plural forms, such as “bim”, “building information model,” “building information model - bim”, “building information modelling”, "building information modelling (bim) and “building information modelling (bim)” were replaced by “building information modelling” through thesaurus file. In addition, “visual languages”, “visual programming”, “visual programming interface”, “visual programming language (VP)”, “visual programming languages”, “visual scripting” and “VP” were replaced by “visual programming language”. Other similar types of replacement are not listed. As a result, 106 main keywords were shortlisted and visualized, as shown in Fig. 6. The colour-coded circular nodes in the visual keyword co-occurrence network represent different clusters. Each keyword’s frequency is represented by the node’s size, the co-occurrence relationships between keywords by the arcs and the strength of each link by the line thickness. In addition, one can observe that “building information modelling” is the most commonly used keyword, followed by “architectural design” and “visual programming language”. Furthermore, dynamo, decision-making, environment management, building performance and energy utilization are also research hotspots in this field.
关键词有助于总结文献研究的内容。它代表了特定领域现有研究和相关主题的主要结果。当使用作者关键字在VOSviewer工具包中映射共现网络时，最小出现次数设置为2。透过同义词库档案，“建筑信息模型”取代了涵义相同或相近及单数或复数形式的关键词，例如“建筑信息模型”、“建筑信息模型”及“建筑信息模型”。此外，“可视化语言”、“可视化程序设计”、“可视化程序设计接口”、“可视化程序设计语言”、“可视化程序设计语言”、“可视化脚本”和“可视化程序设计语言”被“可视化程序设计语言”取代。没有列出其他类似的替换类型。结果，106个主要关键词入围并可视化，如图6所示。 视觉关键词共现网络中的颜色编码的圆形节点表示不同的聚类。每个关键词的频率由节点的大小表示，关键词之间的同现关系由弧表示，每个链接的强度由线的粗细表示。此外，可以观察到“建筑信息模型”是最常用的关键词，其次是“建筑设计”和“可视化编程语言”。此外，发电机、决策、环境管理、建筑性能和能源利用也是该领域的研究热点。

Table 2  表2
The top 10 cited documents.
前10名引用的文件。

This section discusses the status of computational BIM applications and the key research areas within building research. The first subsection provides an overview of computational BIM application status across project lifecycles, which involves 79 papers. The subsequent subsections then highlight six key research themes, namely building performance analysis ( 24 papers), heritage BIM (13 papers), material take-off (7 papers), design optimization ( 9 papers), project management ( 6 papers), facility management ( 10 papers) and others ( 12 papers) as shown in
本节讨论了计算BIM应用的现状以及建筑研究中的关键研究领域。第一部分概述了计算BIM在项目生命周期中的应用现状，共涉及79篇论文。随后的小节重点介绍了六个主要研究主题，即建筑性能分析（24篇论文），文物BIM（13篇论文），材料起飞（7篇论文），设计优化（9篇论文），项目管理（6篇论文），设施管理（10篇论文）和其他（12篇论文），如

Table 3. It is worth noting that the six research themes were identified through an in-depth review of the 79 articles’ content.
表3.值得注意的是，这六个研究主题是通过对79篇文章内容的深入审查确定的。

Table 3 shows the themes identified by VOSviewer. However, the limitation of VOSviewer in bibliometric analysis is the inability to provide in-depth insights into qualitative aspects of the studies reviewed [25]. Recognizing this limitation, this study provided a critical perspective and emphasizes to enrich the understanding of visual programming’s impact on computational BIM.
表3显示了VOSviewer确定的主题。然而，VOSviewer在文献计量分析中的局限性是无法深入了解所审查研究的定性方面[25]。认识到这一局限性，这项研究提供了一个关键的角度，并强调丰富的理解可视化编程的影响计算BIM。

Computational BIM application in building research is mainly performed during the design ( $39\mathrm{\%}$$39\mathrm{\%}$39%39 \% of the papers) and operation ( $34\mathrm{\%}$$34\mathrm{\%}$34%34 \% of the papers) stages of the project lifecycle, as shown in Fig. 7. During the design stage, computational BIM is often used to automate repetitive tasks, manage data, optimize design, and perform performance analyses. For example, Hamidavi et al. [84] developed a structural design optimization prototype using computational BIM to enhance the structural design of tall buildings at the early stages of design. Bueno et al. [51] and Carvalho et al. [58] developed life cycle assessment LCA tools using Dynamo and Autodesk Revit, which are then used to support decisionmaking in the early design phase. All authors pointed out that computational BIM can help create more efficient workflows to support design decision-making in the early stages.
计算BIM在建筑研究中的应用主要在项目生命周期的设计（论文的 $39\mathrm{\%}$$39\mathrm{\%}$39%39 \% ）和运营（论文的 $34\mathrm{\%}$$34\mathrm{\%}$34%34 \% ）阶段进行，如图7所示。在设计阶段，计算BIM通常用于自动执行重复性任务、管理数据、优化设计和执行性能分析。例如，Hamidavi等人[84]使用计算BIM开发了结构设计优化原型，以在设计的早期阶段增强高层建筑的结构设计。[51]和Carvalho等人[58]使用Dynamo和Autodesk Revit开发了生命周期评估LCA工具，然后用于支持早期设计阶段的决策。所有作者都指出，计算BIM可以帮助创建更高效的工作流程，以支持早期阶段的设计决策。

During the operation stage, computational BIM has been employed mainly for facility management and historical building conservation purposes. In this stage, computational BIM was used to develop workflows and models to connect the BIM data with 3D scanning, sensors, and Internet of Things (IoT) technologies for data collection. For instance, Valinejadshoubi et al. [98] developed a fault detection and alert generation system for malfunctioning FM sensors during the operational phase. The system integrates sensor information with BIM and a cloud-based system to ensure efficient communication between the building facility manager and IoT company for effective system maintenance. Computational BIM was applied in $19\mathrm{\%}$$19\mathrm{\%}$19%19 \% and $8\mathrm{\%}$$8\mathrm{\%}$8%8 \% of the papers in building projects during the construction and fabrication stages, respectively. The authors pointed out that VP plays a crucial role in developing algorithms for data extraction in the BIM environment.
在运营阶段，计算BIM主要用于设施管理和历史建筑保护。在此阶段，计算BIM用于开发工作流程和模型，将BIM数据与3D扫描，传感器和物联网（IoT）技术连接起来，以进行数据收集。例如，Valinejadshoubi等人[98]开发了一种故障检测和警报生成系统，用于在操作阶段故障FM传感器。该系统将传感器信息与BIM和基于云的系统集成，以确保建筑设施管理员和物联网公司之间的高效通信，以实现有效的系统维护。计算BIM分别在建筑项目的施工和制造阶段的 $19\mathrm{\%}$$19\mathrm{\%}$19%19 \% 和 $8\mathrm{\%}$$8\mathrm{\%}$8%8 \% 论文中应用。作者指出，VP在BIM环境中开发数据提取算法方面发挥着至关重要的作用。

The application of computational BIM for various building performance analyses has increased drastically in recent years. This is because of the continuous development of BIM and VP tools, as well as the advancements in data interoperability between design software and VP and building performance analysis tools [114]. As a result, various building performance criteria have been considered, including energy performance [115], daylighting simulation [9], PV optimization [47], LCA [48,51,58,60,63], acoustic [62], and more.
近年来，计算BIM在各种建筑性能分析中的应用急剧增加。这是因为BIM和VP工具的不断发展，以及设计软件和VP之间的数据互操作性和建筑性能分析工具的进步[114]。因此，考虑了各种建筑性能标准，包括能源性能[115]，采光模拟[9]，PV优化[47]，LCA [48，51，58，60，63]，声学[62]等。

Computational BIM has been employed intensely in different studies on the analysis and optimization of building envelopes. For instance, a BIM-based envelope insulation design tool has been developed to find the optimum trade-off between the insulation system’s total embodied energy and the envelope’s thermal performance by considering the material type and thickness [64]. Using the proposed framework, it was found that a slight improvement in the thermal performance (1.3399 to $1.2112\mathrm{GJ}/\mathrm{m}2$$1.2112\mathrm{GJ}/\mathrm{m}2$1.2112GJ//m21.2112 \mathrm{GJ} / \mathrm{m} 2 ) would cause the embodied energy to increase by more than 50 times. The same researchers developed a numerical-based window design optimization tool using computational BIM focusing on non-tropical regions of Australia. The tool achieved up to $8.57\mathrm{\%}$$8.57\mathrm{\%}$8.57%8.57 \% energy savings [64]. Both studies implemented Optimo [116], a Nondominated Sorting Genetic Algorithm (NSGA-II) optimisation package available in the VP tool Dynamo to conduct the optimisation task. Three systems for building thermal envelope performance automation and optimisation based on the overall thermal transfer value concept have
计算BIM已被广泛应用于建筑围护结构分析和优化的各种研究中。例如，已经开发了一种基于BIM的围护结构隔热设计工具，通过考虑材料类型和厚度，找到隔热系统总内含能量和围护结构热性能之间的最佳权衡[64]。使用所提出的框架，发现热性能（1.3399到 $1.2112\mathrm{GJ}/\mathrm{m}2$$1.2112\mathrm{GJ}/\mathrm{m}2$1.2112GJ//m21.2112 \mathrm{GJ} / \mathrm{m} 2 ）的轻微改善将导致体现能量增加超过50倍。同样的研究人员开发了一个基于数值的窗户设计优化工具，使用计算BIM，专注于澳大利亚的非热带地区。该工具实现了高达 $8.57\mathrm{\%}$$8.57\mathrm{\%}$8.57%8.57 \% 的节能[64]。两项研究均实施了Optimo [116]，这是VP工具Dynamo中可用的非支配排序遗传算法（NSGA-II）优化包，用于执行优化任务。 三种基于整体热传递值概念的建筑围护结构性能自动化和优化系统，