Open access peer-reviewed chapter

A Review of BIM-Based Automated Code Compliance Checking: A Meta-Analysis Research

Written By

Murat Aydın

Submitted: 16 August 2021 Reviewed: 19 November 2021 Published: 25 May 2022

DOI: 10.5772/intechopen.101690

From the Edited Volume

Automation and Control - Theories and Applications

Edited by Elmer P. Dadios

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This study aims to discuss the articles which are only available in electronic academic databases and only written in English in the subject of BIM and ACCC. Statistical results about the articles are obtained by the meta-analysis. In this study, meta-analysis method was selected as the method, and the general situation of the articles is presented based on statistical analysis data in the AEC industry. For meta-analysis, adapting from previous studies, a meta-analysis template consisting of four main categories is created and each category is subdivided into sub-categories. As a result of the study conducted in the electronic academic databases of the ITU (Istanbul Technical University) library website, there are 168 studies, including 131 articles and 37 proceedings until 31.12.2020. Only articles are analyzed in this study, and proceedings are not included. A literature review is carried out in the publications on the subject of ACCC through BIM by the ITU library website’s academic databases to determine in which research trend is, in which areas are concentrated, and which areas are available. The study gives detailed information about the articles on ACCC subject area in the AEC industry in sub-categories when making general evaluation in categories.


  • automated code compliance checking
  • building information modeling
  • common graphs
  • industry foundation classes
  • meta-analysis

1. Introduction

Building Information Modeling (BIM) is a simulation prototyping technology. The definition of the BIM according to the US National BIM Standard is “BIM is the digital representation of the physical and functional characteristics of a building project.” The concept of BIM emerged in the 1970s, is discussed by academicians in various publications. The importance of BIM technology was increased gradually since the 2000s. Various BIM software has been developed by computer-aided design application providers such as Autodesk®, Graphisoft®, Bentley®, etc. In 1997, a new data standard Industry Foundation Classes (IFC), was established by Industry Alliance for Interoperability (IAI) [1, 2]. IFC is independent of any software, and it is a standard object-based data standard developed in express modeling language [3, 4]. IFC is supported by leading BIM-based software. Thus, it is widely accepted that BIM and IFC data standard will significantly improve and facilitate cooperation in the design processes.

A high level of interoperability and cooperation is essential to enhance expertise and automation in the construction industry. The required data must be represented correctly according to the types, characteristics, and names to build a building. A validated IFC building model is a vital prerequisite for executing many automated tasks such as building performance analysis and Automated Code Compliance Checking (ACCC) [5]. ACCC, according to building regulations, is an important task that must be handled carefully during the whole design process. Manually building regulation checking, a traditional method is a repetitive, time-consuming, and error-prone process for architects, engineers, or public authorities [6, 7, 8]. That is why BIM’s effective automated code compliance checking is considered a promising domain in Architecture, Engineering, and Construction (AEC) industry.

ACCC studies are generally directed at standardizing and automating problems encountered in building regulation control [9]. Although ACCC studies were conducted in different countries, it is also understood that these countries show similarities to the problems set by the researchers. It is seen that most of the scientific studies aimed at local administration, which is in the most crucial position in the implementation and control of the building production process under the legislation, are limited to the subject area of process improvement and geographical information system [10, 11, 12, 13]. As a result of the literature research being studied on the subject area, it is seen that there are no general conclusions about the ACCC domain; and it is needed to combine the results of the research conducted in different countries. On the other hand, emerging BIM technology and ACCC have become critical issues to evaluate building performance in design and building permit processes automatically. It is also a fact that it is too late to start working on ACCC in a country where the construction sector is so active. Some local administrations are observed to investigate the problems and state of the art manual code checking, and the ACCC possibilities are examined; a BIM-based model has been designed and coded. In this article, the literature review results in the first stage of the research project are given. This study is addressing the interaction between BIM and ACCC.

Articles on the subject of BIM and ACCC, which are accessible in the electronic academic databases, are analyzed in the paper. In this study, where the findings are presented in pivot tables and graphs, meta-analysis method was preferred. Tables and graphs are developed with the help of Microsoft Excel® and Graph Commons website. A meta-analysis template is transformed by adapting some previous meta-analysis studies. The template consists of four main categories be about Data, Content, Form & input-output relationship, and Purpose & outcome relationship and each category is subdivided into sub-categories. Findings are expressed with the help of pivot tables and graphs as the results of the meta-analysis.


2. Background of the ACCC studies

ACCC is a rule-based method that provides simultaneous control of building elements and building regulations, considering the building elements’ size and characteristics and their associated regulations and codes [14, 15, 16]. In ACCC, structural elements and components are checked for compliance with the relevant regulation’s rules and conditions, and checking reports are produced [9]. The domain of automated rules, code, and regulation compliance checking has been interested in many researchers and practitioners over the years. It started in 1960 as a subfield of Artificial Intelligence (AI) and linguistics to investigate human language’s automatic creation and comprehension. The first computable rule development study dates back to the 1960s in the AEC industry. The American Institute of Steel Construction (AISC) specifications had been made using a decision table, and it has been formalized in these years. The research conducted by Fenves in 1966, using the regulations’ decision tables, is shown as the first scientific study in this area in literature [17]. In his research, Fenves created different decision tables with regulation rules and conditions under which these rules may apply [18]. In 1973, a project was undertaken to restructure the AISC specification. In this project, a theoretical model was presented in which a four-layer structure can explain the knowledge of regulation. This regulation model was used as the SASE modeling methodology (Standard, Analysis, Synthesis, and Expression) software developed by Fenves and his team in 1987 [19]. This software was developed as a tool to provide the organization of regulation rules, decision tables, information networks, and classification systems. Towards the end of the 1980s, studies began about the development of building ACCC systems.

When it came to the 1990s, building models and rule checking methods have been developed, but effective computable code systems have more recently begun to emerge. The first study on ACCC has been CORENET in Singapore since 1995. As of 2000, researches and studies about building BIM-based design evaluation have increased. The latest and current ACCC Systems are Construction and Real Estate NETwork (CORENET), FORNAX, Solibri Model Checker (SMC), Jotne EDMmodelChecker & The Express Data Manager (EDM), Statsbygg, International Code Council (ICC) & SMARTcodes, General Services Administration (GSA) & Design Assessment Tool (DAT), Korean Research Studies, DesignCheck, LicA, ACCBEP, GTPPM, Natural Language Processing (NLP), and Artificial Intelligence (AI) [20]. The present studies have shown the possibility of various rule generation approaches and applicability to ACCC by many countries. The Republic of Korea, Norway, Portugal, The United States of America, Australia, The Republic of Singapore have given importance to BIM-based ACCC studies towards increasing the quality of design. Private or public institutions have financed most of these studies. Some of the studies deal with building regulation as a whole, and some only involve fire, elevator, water system, safety, building envelope, installation, circulation, parking, etc. regulations.


3. Background of meta-analysis

The literature review allows us to learn the state of the recent or current literature. Review articles can cover a wide range of subject matter at various levels of completeness and comprehensiveness. These are based on analyses of literature that may include research findings. There are various types of literature reviews, including meta-analysis/systematic review, scoping review, rapid review, umbrella review, and systematized review [21].

Quantitative methods of combining study results were first described in the early 1930s and grew in interest, especially in health, in the 1970s. Glass gave a “Meta-analysis” name for the kind of his research in 1976 [22]. Applications of meta-analysis to accumulated research literature showed that research findings were not nearly as conflicting as had been thought and that valuable and sound general conclusions could be drawn from existing research [23]. Meta-analysis began to evolve with Doll and Peto’s intensive work in Oxford in the 1980s [24]. Wasserman, Hedges, Olkin, and Petitti defined the meta-analysis’s statistical methods [25, 26]. Greenland described the statistical methods for meta-analysis of non-experimental studies [27]. At present, many discoveries and advances in cumulative knowledge are being made not by those who do primary research studies but by those who use meta-analysis to discover the latent meaning of existing research literature [28, 29].

The classification is of great importance to determine any domain’s analysis, how the research trend is focused, in which areas it is concentrated, and in which areas there are spaces [30]. By analyzing the studies carried out within the scope, it is expected to give information about ACCC studies. A detailed literature review is carried out for the studies within the subject’s scope [29]. Many articles, proceedings, papers, theses, book chapters, research reports, published or unpublished sources are accessed through scanning [28].

Meta-analysis is a method of combining the results of multiple studies independent of each other; and statistical analysis of research findings [28]. It combines the results of studies done in different places, times, and centers on the same subject, and it makes a general conclusion about the related topic [31].

Meta analysis using quantitative methods to synthesize and summarize results is a systematic review. It can be completely objective in evaluating research findings. This advantage makes it different and preferable from other reviews. Hence, in this paper, the meta-analysis method analyzes ACCC studies in the BIM domain.

  • The research questions for each article are as follows:

  • What is the basic info (keywords, authors, year, institution, country, etc.)?

  • What is the content?

  • What are the form, input, and output?

  • What are the purpose and outcome?

3.1 The objective and limitations of the meta-analysis study

It is necessary to examine previous research results to develop a conceptual model for ACCC. This study aims to find the research gap and organize the existing information to form the conceptual model’s basis to be developed. Articles published between 01.01.1988 and 31.12.2020 are included in the review. Only leading international electronic academic databases are used within the scope of the meta-analysis study (e.g., Emerald, John Wiley & Sons, ICONDA CIB Library, Science Direct, ASCE, Taylor & Francis, Web of Science, ITcon, Scopus, Engineering Village, and Google Scholar) [32]. “Building Information Modeling,” “BIM,” “IFC,” “Industry Foundation Classes,” “Code Checking,” “Automated Code Compliance Checking,” “Code Compliance Checking,” “Building Code” keywords are used in Title, Abstract and Keywords sections of advanced search screen of the databases. The search areas are limited to:

  • Architectural design,

  • Automation,

  • Building codes,

  • Engineering,

  • Environmental science,

  • Construction industry, and

  • Construction building technology.

As a result of the search in the academic databases in ITU Library, 168 studies, including 131 articles and 37 proceedings, are found (Figure 1). To achieve a confident academic standard, 131 articles that are peer-reviewed are included in the analysis. The only peer-reviewed articles are analyzed in the meta-analysis study. Papers in proceedings that generally include the progress of preliminary research are not included in the scope.

Figure 1.

Numerical distribution of document type.

3.2 Template of meta-analysis study

Meta-analysis template allows the articles analyzed within the scope to be categorized under the headings and subheadings discussed. The meta-analysis template, which consists of four main categories be about Data, Content, Form & input-output relationship, and Purpose & outcome relationship, shown in Table 1, was prepared with the help of the frameworks of similar studies, and each category was subdivided into subcategories to provide detailed information [28, 33].

1. Data1.1. Article type
1.2. Keyword
1.3. Author
1.4. Institution
1.5. Country
1.6. Source
1.7. Publisher
1.8. Year
1.9. Database
1.10. Area
2. Content2.1. Subject
2.2. Study level
2.3. Process
3. Form & input-output relationship3.1. Method
3.2. Data type
3.3. Contribution
4. Purpose & outcome relationship4.1. Problem
4.2. Tool
4.3. Result

Table 1.

The meta-analysis template.

The Data Category consists of 10 sub-categories: e.g., Title, Keyword, Author, Institution, Country, Source, Publisher, Year, Database, and Area. The content category consists of three sub-categories: e.g., Subject, Study level, and process. The form & input-output relationship category consists of three sub-categories: e.g., Method, Data Type, and Contribution. The purpose & outcome relationship category consists of three sub-categories: e.g., Problem, Tool, and Result.


4. Methodology and analysis

131 articles were transformed into a comprehensive table with Microsoft Excel®, which shows the findings on the pivot tables and graphs. Bar charts were used for the “Data” category. In other categories, interactive map network graphs via the Graph Commons website were used to express sub-categories’ relationships [34]. Graph Commons is a collaborative platform for mapping, analyzing, and publishing data-networks. It empowers researchers, people, and organizations to transform their data into interactive maps and untangle complex relations. In Graph Common, it needs at least two fundamental values for a map networks graph. It establishes the results with a Name typed in From Type, Edge To, and Type To columns in an Excel format file. In an interactive map networks graph, the ones with high weight (the arrow and the text) become more dominant than the others, which shows their importance.

4.1 Data

“Data” category consists of 10 sub-categories be about Title, Keyword, Author, Institution, Country, Source, Publisher, Year, Database, and Area of an article. The results of the analysis are given under the related headings. Since the results are more remarkable in number in sub-categories, the results less than three are grouped under the “Others.”

4.1.1 Article type

The “Type” of articles used for the meta-analysis is examined in the Article Type sub-category (Figure 2), which shows articles’ distribution by article types. 98 of the 131 articles are published directly in journals, while the remaining 33 are published as selected papers at congresses.

Figure 2.

Distribution of article type, keyword, and author (data) according to the number of articles.

4.1.2 Keywords

The keywords are listed in the “Keyword” sub-category. The distribution of the keywords is shown in Figure 2. Articles with less than three keywords are categorized into the “Others” sub-category to limit the number of keywords. The most frequently used keywords are “Building information modeling (BIM)” (58 pcs), “Industry foundation classes (IFC)” (21 pcs), “Building information model” (13 pcs), and “Building codes” (13 pcs). Subsequently; Rule checking, Interoperability, Code checking, Computer-aided design, Automated code compliance checking, Semantic systems, Natural Language Processing, Model checking, Building design, Automated compliance checking, Prevention through design, Open BIM, Governance, Compliance checking, Code compliance checking, Building regulations, Automation, Automated information extraction, Automated code checking, and AEC industry are the most common keywords.

4.1.3 Author

The “Author” sub-category includes the authors’ names and numbers. The distribution of authors is shown in Figure 2. It is seen that the number of articles in which 2 authors are the highest, 7 and 8 authors is the lowest. In general, the articles are prepared by large groups. This preparation shows the subject’s multidisciplinary face, and the research studies should be supported by all the disciplines involved in the construction activities.

4.1.4 Institution

The authors’ institutions are grouped in the “Institution” sub-category. Figure 3 shows the distribution of articles by institution type. Most of the articles prepared in Universities (111 pcs) as the findings of the research projects. Then University-Private Sector (8 pcs), Private Sector (4 pcs), University-Research Center-Private Sector (4 pcs) follows the universities. When University-Research Center-Private Sector-Public Sector associations collaboratively work, the first authors of the articles are mostly academicians. Accordingly, it can be seen that the construction sector and university cooperation is currently limited in the subject area of BIM and ACCC, even though cooperation is a very urgent need. Collaborative research should be supported to reduce public institutions’ workload, increase efficiency, and minimize possible human errors.

Figure 3.

Distribution of institution, country, source, and publisher (data) according to the number of articles.

4.1.5 Country

The countries of the institutions are grouped in the “Country” sub-category (Figure 3). Countries with fewer than three are grouped under “Others.” Most of the articles are prepared in the USA (57 pcs). China (13 pcs), Australia (10 pcs), and Germany (9 pcs) follow the USA.

4.1.6 Source

The Source sub-category shows the source of the article. The distribution of articles by sources can be seen in Figure 3. Most of the articles are published in the Journal of Information Technology in Construction (18 pcs), Journal of Computing in Civil Engineering (12 pcs), and Automation in Construction (10 pcs). Subsequently, Workshop on Computing in Civil Engineering (6 pcs), Building Research & Information (5 pcs), Computing in Civil and Building Engineering (4 pcs), Computer-Aided Civil and Infrastructure Engineering (4 pcs), Journal of Civil Engineering and Management (3 pcs), Journal of Architectural Engineering (3 pcs) and Congress on Computing in Civil Engineering (3 pcs) sources are available.

4.1.7 Publisher

The “Publisher” sub-category shows the publishers of the articles. The distribution of articles by publishers can be seen in Figure 4. Most of the articles are published by the American Society of Civil Engineers (ASCE) (47 pcs). The others are respectively Journal of Information Technology in Construction (ITcon) (19 pcs), Taylor & Francis (19 pcs), Elsevier (16 pcs), Institute of Electrical and Electronics Engineers (IEEE) (5 pcs), International Council for Research and Innovation in Building and Construction (CIB) (4 pcs), Emerald (3 pcs), John Wiley & Sons (3 pcs) and Trans Tech Publications (3 pcs).

Figure 4.

Distribution of year, database, and area (data) according to the number of articles.

4.1.8 Year

The year in which the articles were published is grouped in the “Year” sub-category. The distribution of articles by years can be seen in Figure 4. The earliest study on BIM, IFC, and ACCC was published in 1988, and the number of articles has increased steadily between 1995 and 2011 [35]. There has been an increase in the number of articles as of 2012. It peeks in 2014 (26 pcs) and 2016 (22 pcs). BIM and ACCC have gained importance after 2011.

4.1.9 Database

The electronic academic databases are analyzed in the “Database” sub-category. The distribution of the databases used in the research is shown in Figure 4. Apart from these, Google Scholar, ICONDA CIB Library, and ITcon academic databases are included in the meta-analysis study. Most of the articles are obtained from Engineering Village (76 pcs), and the most minor articles are accessed from Emerald (3 pcs). American Society of Civil Engineers (34 pcs), Taylor & Francis (19 pcs), ITcon (17 pcs), Science Direct (14 pcs) follows them respectively.

4.1.10 Area

The “Area” sub-category identifies the professional areas in which the articles are relevant in the construction sector. Although some of the articles are evaluated for a specific area such as Architecture, Civil Engineering, Education, there are also some articles in the AEC Industry and AECO Industry, including many professional areas. As seen in Figure 4, most of the articles are performed in Architecture, Engineering and Construction Industry (AEC Industry) (57 pcs). Architecture, Engineering, Construction and Operation Industry (AECO Industry) (18 pcs), Civil Engineering (17 pcs), Building-Construction (16 pcs), Architecture (15 pcs), Construction Management (4 pcs), Education (3 pcs) follows it respectively.

4.2 Content

“Content” category, which is the second category of meta-analysis’ framework, consists of 3 sub-categories be about Subject, Study Level, and Process. The relationship between these sub-categories is shown in Figure 5, a map networks graph prepared by Common Graph. The Starting Point (Red Dots) shows the “Subject” sub-category, the Edge (Colorful Arrows) shows the “Study Level” sub-category, and the End Point (Blue Dots) shows the “Process” sub-category. As a result of the analysis, the distribution of the number of articles obtained in each sub-category is given in brackets in the map networks graph, and bar charts are automatically prepared according to this graph. The results of the analysis are given in detail under the related sub-category. According to the map networks graph in Figure 5, the articles are few, and they are not dominant, which are done in the same Subject, Study, and Process levels.

Figure 5.

Distribution of subject, process, and study level (content) according to the number of articles.

4.2.1 Subject

The topics of the articles are grouped under the “Subject” sub-category. In the Subject sub-category, the perspective of BIM, IFC, and ACCC concepts is analyzed. As shown in Figure 5, most articles are based on Automated Code Compliance Control (35 pcs). Then the articles on BIM Application (19 pcs), Building Code (17 pcs), BIM-based Rule Checking (10 pcs), BIM-based Model Checking (10 pcs), and Interoperability (9 pcs) subjects are prominent. As a result of this grouping, some articles have specific topics such as BIM-based Automatic Programming (6 pcs), Computer-Aided Design (5 pcs), Architectural Design (5 pcs), Structural Design (4 pcs), Construction Project Management (4 pcs), Visualization (2 pcs), Process Control (2 pcs), BIM Education (2 pcs) and Construction Contracts (1 pcs).

4.2.2 Study level

Articles are grouped at four basic levels in the “Study Level” sub-category. These levels are namely Project, Sector, Firm, and Product. Most of the articles are dealt with the Project level. Therefore, Project-Product, Project-Sector, Project-Firm, Project-Product-Firm levels are also created. As seen in Figure 5, most articles are discussed at the Project level (52 pcs). Project-Product (28 pcs), Sector (21 pcs), Product (16 pcs), Project-Sector (7 pcs), Project-Firm (3 pcs), Project-Product-Firm (2 pcs), and Firm (2 pcs) levels follow it respectively.

4.2.3 Process

The “Process” sub-category determines the relevant phase of the articles in the building production process. Planning, design, bid, construction, operation, and usage phases are grouped under Whole Life Cycle’s title. As shown in Figure 5, the articles are primarily directed to the Whole Life Cycle (49 pcs). Other articles, respectively, are prepared for Design (34 pcs), Construction (33 pcs), and Design-Construction (15 pcs) processes.

4.3 Form & input-output relationship

Form & input-output relationship category consists of 3 sub-categories be about Method, Data Type, and Contribution. Form & input-output relationship is shown in Figure 6. The Starting Point (Red Dots) shows the “Method” sub-category, the Edge (Colorful Arrows) shows the “Data Type” sub-category, and the End Point (Blue Dots) shows the “Contribution” sub-category. The distribution of the number of articles obtained in each sub-category is given in brackets in the map networks graph, and bar charts are automatically created according to this graph. The results of the analysis are given in detail under the related sub-category. When we look at the map networks chart in general, it is seen that many articles (34 pcs) prefer the Case Study method, use Quantitative data type, and present Model Creation contribution.

Figure 6.

Distribution of method, data type, and contribution (form & input-output relationship) according to the number of articles.

4.3.1 Method

As shown in Figure 6, the Case Study (59 pcs) is the most common method used in the articles. Practical (34 pcs), Theoretical (20 pcs), Survey (11 pcs), and Interview (7 pcs) methods are also the other methods used in articles. The Case Study method is generally used in studies related to BIM-based residences or office buildings and unique case studies such as the validity of BIM and GIS integration, IFC construction models, the envelope design of the outer wall of a BIM-based building, and so on. Studies such as the development of BIM-based computable regulation rules and control, open-source IFC verification tool, and BIM-model control in building design are evaluated as Practical.

The other studies, such as literature review and BIM-based automated code compliance checking classification, are treated as Theoretical. The questionnaires conducted with the real estate sector participants, cost consultants, contractors, students, etc., on the adoption of BIM technology are evaluated as Surveys. The interview method is used in some studies with stakeholders of the construction sector such as expert project participants, designers, construction site staff and workers, project stakeholders, etc.

4.3.2 Data type

The type of data used in the articles is grouped in the “Data Type” sub-category. As seen in Figure 6, Most of the studies are based on Quantitative (81 pcs) data. The Quantitative data type is mainly seen in the studies which are utilized the case study method. It is used in the case studies for general and specific problems, such as implementation limitations of building code compliance checking, lack of interoperability in BIM applications, development of the automatic control and evaluation process for BIM data, results of BIM information acquisition difficulties, and control of green building design. Qualitative data obtained from the results of theoretical studies such as the failure to adopt BIM technology, the limitations of BIM in the construction sector, deficiencies of automated code compliance checking in the design process, and the limitations of existing building regulatory compliance control problems grouped. Quantitative-Qualitative data types are primarily obtained from articles where practical, theoretical, and case analysis methods are applied.

4.3.3 Contribution

The contribution of the article to the subject area is discussed in the “Contribution” sub-category. As shown in Figure 6, Model Creation (53 pcs), General Evaluation (34 pcs), System Development (29 pcs), and Statistical Findings (15 pcs) are the most known contributions of the studies, respectively. Model Creation is generally directed to the design of a BIM model. According to the BIM model, general evaluation is related to automated code compliance checking software, applications, and new trends. System Development focuses on the development of a BIM-based automated code compliance checking system. Statistical Result is based on the statistical results of the BIM-based model and code compliance checking application.

4.4 Purpose & outcome relationship

Purpose & Outcome Relationship category, the last category, consists of 3 sub-categories: Problem, Tool, and Result. The relationship between these sub-categories is shown in Figure 7. Starting Point (Red Dots) shows the Problem sub-category, the Edge (Colorful Arrows) shows the Tool sub-category, and the End Point (Blue Dots) shows the Result sub-category. As a result of the analysis, the distribution of the number of articles obtained in each sub-category is given in brackets in the map networks graph; and bar charts are automatically created according to this graph. The results of the analysis are given in detail under the related sub-category. In Figure 7, it is seen that the articles which are resulted from a Development for Requirement problem with the Software Development tool are dominant (20 pcs). The articles that resulted as a Proposal for Requirement problem with the Software Usage tool are also noteworthy (14 pcs).

Figure 7.

Distribution of problem, tool, and result (purpose & outcome relationship) according to the number of articles.

4.4.1 Problem

The “Problem” sub-category evaluates the factors that led to the emergence of articles. As shown in Figure 7, Requirement is reached in most articles (60 pcs). The others are Lack (26 pcs), Result (12 pcs), Limitation (10 pcs), Insufficiency (7 pcs), Examination (6 pcs), Identification (5 pcs), and Divergence (5 pcs) problems. When we check the articles’ reasons, the necessity of a BIM-based automated code compliance checking and national automated code compliance checking software problem comes to the fore. Furthermore, the importance of interoperability with practical BIM for computable building regulation rules is emphasized in many articles. Other problems result from BIM implementation difficulties in automated code compliance checking and the limitation of BIM implementation in the construction sector.

4.4.2 Tool

“Tool” sub-category discusses the tools used to reach the goal in articles. As shown in Figure 7, Software Usage (52 pcs) is reached in most of the articles. The other tools are Software Development (31 pcs), Infographic Usage (28 pcs), Common File Usage (9 pcs), and Module Addition (8 pcs).

There are three articles in which tool information is not available. National (Lica, ACCBEP, GTPPM) software and International (SMC, Statsbygg, Fornax, Corenet, ePlanCheck, DesignCheck, SmartCodes, Jotne EDMmodelChecker) software are preferred as a Software Usage tool in the articles. Software Development tool concludes as a development for a requirement problem in most articles. Common File Usage tool transfers standard data files between software such as an IFC-BIM data exchange, a BIM and GIS integration, and a BIM and QR-code. Information (data sources, statistical information, contents, etc.) and visual expression (visual elements, graphics, images, etc.) are combined in a meaningful way with an Infographic Usage tool to create a graphical and visual representation. Module Addition tool gives additional features to existing software or systems.

4.4.3 Result

The results of each article are determined in the Result sub-category. As shown in Figure 7, a Proposal (58 pcs) is reached in most of the articles. Also; Development (34 pcs), Analysis (26 pcs), Impact (10 pcs), Classification (2 pcs), and Identification (1 pcs) results are obtained from the articles. The results of the articles emphasize the importance of automated code compliance checking. Several articles propose a new automated code compliance checking system. Except for proposals, the other results are the development of BIM-based automated code compliance checking system and software, the impact of interoperability analysis and automated code compliance checking system, the impact the classification of building regulation rules, and the identification of trends in BIM teaching.


5. Conclusions

This study carries out a literature review by analyzing the articles on ACCC through BIM by the ITU library website. It eliminates the preliminary study of BIM and ACCC. It gave the previous studies’ general situation, research trends, and developed or proposed software features. Also, it creates a substructure for developing a BIM-based automated code compliance checking software in Turkey. The studies are investigated within the scope of BIM and ACCC subjects. The literature review covers the period between 1988 and 2020. As a result of the literature review, there are 168 publications, including 131 articles and 37 proceedings. This study only analyzes English articles except for proceedings. It evaluates the results by the meta-analysis method. The meta-analysis analyzes 131 articles by four main categories (Data, Content, Form & Input Relationship, Purpose & Outcome Relationship) and sub-categories within each category.

Of the 131 articles, 98 are journal articles, and 33 are conference articles. BIM, IFC, ACCC, and Building Codes are the keywords commonly used in articles. According to the keywords, articles include many professional areas such as architecture, construction, operation, computer science, etc. So, this situation shows that ACCC is related to different disciplines. It should be supported by all the disciplines involved in the construction sector. Most of the articles are written by academicians in universities. Most of the articles are carried out in the USA and published mainly by the American Society of Civil Engineers (ASCE) publisher by obtaining from the Engineering Village database.

The first ACCC article was published in 1988, and the number of articles has increased steadily between 1995 and 2011. After 2011, the increased number of articles shows the importance of BIM and ACCC. Although most articles are carried out in many professional fields, such as the AEC Industry and AECO Industry, some work in a specific area such as Architecture, Civil Engineering, Education. The articles impact the interoperability between ACCC and BIM Application. Most of them are dealt with the project level, associated with sector, firm, and product. They are primarily directed to the whole life cycle process. They generally apply to BIM-based housing or office buildings by using the case study method.

If we generally look at the articles’ problems, the requirement of BIM-based automated code compliance checking software comes to the fore. They emphasize the importance of ACCC, and they often propose a new ACCC system. Lica, Statsbygg, SMC, Fornax, Corenet, ePlanCheck, DesignCheck, etc., have been developed for solving different problems. These systems help to standardize and automate the problems of building regulation compliance checking. The emerging problems are similar in other countries such as Turkey by analyzing them. As a result, this study creates a substructure for developing a BIM-based automated code compliance checking software for solving the problems in building regulation compliance checking faced by Turkish municipalities.


Conflict of interest

The author declares no conflict of interest.


Notes/thanks/other declarations

The author received no specific funding for this study.


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Written By

Murat Aydın

Submitted: 16 August 2021 Reviewed: 19 November 2021 Published: 25 May 2022