perceived diversity in software engineering a systematic literature review

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Perceived diversity in software engineering: a systematic literature review

Affiliations.

• 1 University of British Columbia, Kelowna, Canada.
• 2 University of Waterloo, Waterloo, Canada.
• PMID: 34305441
• PMCID: PMC8284041
• DOI: 10.1007/s10664-021-09992-2

We define perceived diversity as the diversity factors that individuals are born with. Perceived diversity in Software Engineering has been recognized as a high-value team property and companies are willing to increase their efforts to create more diverse work teams. The current diversity state-of-the-art shows that gender diversity studies have been growing during the past decade, and they have shown the benefits of including women in software teams. However, less is known about how other perceived diversity factors such as race, nationality, disability, and age of developers are related to Software Engineering. Through a systematic literature review, we aim to clarify the research area concerned with perceived diversity in Software Engineering. Our goal is to identify (1) what issues have been studied and what results have been reported; (2) what methods, tools, models, and processes have been proposed to help perceived diversity issues; and (3) what limitations have been reported when studying perceived diversity in Software Engineering. Furthermore, our ultimate goal is to identify gaps in the current literature and create a call for future action in perceived diversity in Software Engineering. Our results indicate that the individual studies have typically had a gender diversity perspective focusing on showing gender bias or gender differences instead of developing methods and tools to mitigate the gender diversity issues faced in SE. Moreover, perceived diversity aspects related to SE participants' race, age, and disability need to be further analyzed in Software Engineering research. From our systematic literature review, we conclude that researchers need to consider a wider set of perceived diversity aspects for future research.

Keywords: Perceived diversity; Software engineering; Systematic literature review.

© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.

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• Barnes T Lee K Tavares C Rodríguez-Pérez G Nagappan M (2024) Towards understanding barriers and mitigation strategies of software engineers with non-traditional educational and occupational backgrounds Empirical Software Engineering 10.1007/s10664-024-10493-1 29 :4 Online publication date: 4-Jun-2024 https://dl.acm.org/doi/10.1007/s10664-024-10493-1
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Women’s Participation in Open Source Software: A Survey of the Literature

Addressing the influence of end user human aspects on software engineering, post-pandemic resilience of hybrid software teams, diversity in software engineering: a survey about scientists from underrepresented groups, investigating the perceived impact of maternity on software engineering: a women’s perspective, the nature of prejudice, are emily and greg more employable than lakisha and jamal a field experiment on labor market discrimination, the difference: how the power of diversity creates better groups, firms, schools, and societies, gender violence: transgender experiences with violence and discrimination., managing cross-cultural issues in global software outsourcing, related papers (5), software engineering practice versus evidence-based software engineering research, are you sure you are happy, global and latin american female participation in evidence-based software engineering: a systematic mapping study, practical relevance of software engineering research: synthesizing the community's voice, critical elements for multigenerational teams: a systematic review, trending questions (1).

- Gender diversity studies have grown, showing benefits in software teams. - Other diversity factors like race, age, disability need further analysis.

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Observable Diversity in Software Engineering: A Systematic Literature Review

Authors: Gema Rodríguez-Pérez Reza Nadri Meiyappan Nagappan

Venue: EMSE   Empirical Software Engineering, Vol. 26, No. 5, pp. 102, 2021

Abstract: We define perceived diversity as the diversity factors that individuals are born with. Perceived diversity in Software Engineering has been recognized as a high-value team property and companies are willing to increase their efforts to create more diverse work teams. The current diversity state-of-the-art shows that gender diversity studies have been growing during the past decade, and they have shown the benefits of including women in software teams. However, less is known about how other perceived diversity factors such as race, nationality, disability, and age of developers are related to Software Engineering. Through a systematic literature review, we aim to clarify the research area concerned with perceived diversity in Software Engineering. Our goal is to identify (1) what issues have been studied and what results have been reported; (2) what methods, tools, models, and processes have been proposed to help perceived diversity issues; and (3) what limitations have been reported when studying perceived diversity in Software Engineering. Furthermore, our ultimate goal is to identify gaps in the current literature and create a call for future action in perceived diversity in Software Engineering. Our results indicate that the individual studies have typically had a gender diversity perspective focusing on showing gender bias or gender differences instead of developing methods and tools to mitigate the gender diversity issues faced in SE. Moreover, perceived diversity aspects related to SE participants’ race, age, and disability need to be further analyzed in Software Engineering research. From our systematic literature review, we conclude that researchers need to consider a wider set of perceived diversity aspects for future research.

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Perceived diversity in software engineering: a systematic literature review

Abstract: we define perceived diversity as the diversity factors that individuals are born with. perceived diversity in software engineering has been recognized as a high-value team property and companies are willing to increase their efforts to create more diverse work teams. the current diversity state-of-the-art shows that gender diversity studies have been growing during the past decade, and they have shown the benefits of including women in software teams. however, less is known about how other perceived diversity … show more.

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Cited by 55 publication s

References 164 publication s, detecting latent topics and trends in software engineering research since 1980 using probabilistic topic modeling.

The landscape of software engineering research has changed significantly from one year to the next in line with industrial needs and trends. Therefore, today's research literature on software engineering has a rich and multidisciplinary content that includes a large number of studies; however, not many of them demonstrate a holistic view of the field. From this perspective, this study aimed to reveal a holistic view that reflects topics, trends, and trajectories in software engineering research by analyzing the majority of domain-specific articles published over the last 40 years. This study first presents an objective and systematic method for corpus creation through major publication sources in the field. A corpus was then created using this method, which includes 44 domain-specific conferences and journals and 57,174 articles published between 1980 and 2019. Next, this corpus was analyzed using an automated text-mining methodology based on a probabilistic topic-modeling approach. As a result of this analysis, 24 main topics were found. In addition, topical trends in the field were revealed. Finally, three main developmental stages of the field were identified as: the programming age, the software development age, and the software optimization age.

Towards Understanding Barriers and Mitigation Strategies of Software Engineers with Non-traditional Educational and Occupational Backgrounds

The traditional path to a software engineering career involves a post-secondary diploma in Software Engineering, Computer Science, or a related field. However, many software engineers take a non-traditional path to their career, starting from other industries or fields of study. This paper proposes a study on barriers faced by software engineers with non-traditional educational and occupational backgrounds, and possible mitigation strategies for those barriers. We propose a two-stage methodology, consisting of an exploratory study, followed by a validation study. The exploratory study will involve a grounded-theory-based qualitative analysis of relevant Reddit data to yield a framework around the barriers and possible mitigation strategies. These findings will then be validated using a survey in the validation study. Making software engineering more accessible to those with non-traditional backgrounds will not only bring about the benefits of functional diversity, but also serves as a method of filling in the labour shortages of the software engineering industry. CCS CONCEPTS• Social and professional topics → Computing profession.

Análise quali-quantitativa sobre a influência da diversidade na produtividade de equipes ágeis: um estudo na indústria

Este artigo investiga a influência da diversidade na produtividade de equipes que utilizam metodologias ágeis e também na qualidade dos artefatos produzidos. Para isso, foi realizada uma pesquisa quali-quantitativa, no contexto da indústria, envolvendo quatro times com diferentes perfis de diversidade. O estudo utilizou dois métodos de coleta de dados: um questionário organizado em três dimensões e métricas aplicadas a dados de uma ferramenta de apoio ao desenvolvimento. Os resultados mostraram que os times mais diversos apresentaram melhores indicadores de produtividade e qualidade em seus produtos.

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• DOI: 10.1109/CHASE.2019.00010
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Not Quite There Yet: Remaining Challenges in Systems and Software Product Line Engineering as Perceived by Industry Practitioners

DOI: https://doi.org/10.1145/3646548.3672587 SPLC '24: 28th ACM International Systems and Software Product Line Conference , Dommeldange, Luxembourg, September 2024

Research on system and software product line engineering (SPLE) and the community around it have been inspired by industrial applications. However, despite decades of research, industry is still struggling with adopting product line approaches and more generally with managing system variability. We argue that it is essential to better understand why this is the case. Particularly, we need to understand the current challenges industry is facing wrt. adopting SPLE practices, how far existing research helps industry practitioners to cope with their challenges, and where additional research would be required. We conducted a hybrid workshop at the 2023 Systems and Software Product Line Conference (SPLC) with over 30 participants from industry and academia. 9 companies from diverse domains and in different phases of SPLE adoption presented their context and perceived challenges. We grouped, discussed, and rated the relevance of the articulated challenges. We then formed clusters of relevant research topics to discuss existing literature as well as research opportunities. In this paper, we report the industry cases, the identified challenges and clusters of research topics, provide pointers to existing work, and discuss research opportunities. With this, we want to enable industry practitioners to become aware of typical challenges and find their way into the existing body of knowledge and to relevant fields of research.

ACM Reference Format: Martin Becker, Rick Rabiser, and Goetz Botterweck. 2024. Not Quite There Yet: Remaining Challenges in Systems and Software Product Line Engineering as Perceived by Industry Practitioners. In 28th ACM International Systems and Software Product Line Conference (SPLC '24), September 02--06, 2024, Dommeldange, Luxembourg. ACM, New York, NY, USA 12 Pages. https://doi.org/10.1145/3646548.3672587

1 INTRODUCTION

System and Software Product Line Engineering (SPLE) has a long tradition, tracing back almost half a century to Parnas’ discussion of program families [ 59 ]. From the get-go frameworks for SPLE [ 17 ], the system and software product line community, and its flagship conference, SPLC 1 have been very much inspired by industry needs and challenges. The devised approaches have been applied successfully in a broad spectrum of industries [ 51 , 80 ].

However, despite all this research, when talking to industry practitioners, one gets the impression that they are still struggling when dealing with SPLE in practice. One common pattern is that a company with a successful product adds more similar products in an ad hoc approach (e.g., “clone-and-own”). Then, with more products, at some point the company hits a complexity barrier and requires a more systematic approach [ 10 , 24 , 69 ]. On the other hand, the combinatorial explosion resulting from developing highly-variable engineering artefacts leads to issues in other engineering practices, e.g., verification and validation/testing, if no systematic approach to manage variabilities is applied [ 55 ] and variability management across granularity levels is perceived as being difficult [ 26 ]. The evolution of variation-rich system without a systematic approach also becomes a nightmare [ 41 ] over time.

In this paper, we argue that, to provide directions for product line research, it is necessary to understand this phenomenon and reasons for it. In 2020, Berger et al. provided some updates on industry challenges in SPLE [ 10 ] elicited earlier, but overall there is only limited up-to-date data on industrial challenges in SPLE. Single case studies about companies adopting product line engineering are still added to the body of knowledge, see, for instance, the ESPLA catalog  [ 51 , 52 ], but multi-case studies or studies focusing on discussing industry challenges from a broader perspective often date 10 to almost 20 years back [ 9 , 80 ].

Furthermore, SPLC industry participation keeps eroding, e.g., Schmid et al. [ 73 ] concluded in 2021 that “today, SPLC is mostly regarded as an academic conference with little industry participation”. However, they also emphasised the interest of practitioners and researchers to exchange knowledge and learn from each other.

We argue that industry practitioners should (1) be aware of typical challenges in adopting SPLE practices and (2) understand the existing body of knowledge on SPLC practices and technology. Furthermore, the SPLC research community needs to (3) understand current and unsolved challenges that industry practitioners are (still) facing and (4) try to address the challenges in collaboration with industry practitioners. This, we hope, will also re-strengthen the link between the academic and industry subcommunities.

As a first step, two authors of this submission organised a workshop with industry practitioners from 9 companies with active systems and software product lines. The discussion and data emerging from that workshop provide the input for this paper. With our analysis here, we aim to answer the following research questions:

• Which challenges and barriers do industry practitioners experience in system and software product line practice?
• What are the reasons for these observed challenges and barriers? (a) Where do approaches exist but are not applied (indicating dissemination, communication, or management issues); (b) where are the available approaches insufficient (indicating opportunities for future work)?
• Where are opportunities and what are appropriate measures to (re-)strengthen the synergy between academic SPLE researchers and industrial practitioners?

In summary, this paper provides the following contributions :

• Recent and up-to-date empirical data elicited from practitioners working on 9 different industrial use cases, including 17 challenges organised into 7 themes.
• A rating of the relevancy (i.e., the relative importance as rated by practitioners) of these challenges.
• A discussion of existing research to address the challenges and open research opportunities for the SPLE community.

2 RESEARCH APPROACH

In this section, we summarise our research approach to obtain the presented results (see Figure  1 ). The workshop was communicated explicitly as an industry-focused and hybrid event (to reach a broad international audience, including those who might not travel to Tokyo). 33 participants took part – the vast majority joined online.

Overview of the research approach, organised into three phases workshop, online discussion with participants, and review by researchers

• Extract data – Achieve immersion to be familiar with the evidence; update the research protocol; extract data.
• Code data – Identify and code interesting concepts, categories, and findings across the entire dataset.
• Translate codes into themes – Translate codes into themes, identify subthemes and higher-order themes where necessary.
• Create a model of higher-order themes – Explore relationships between themes and create a model of higher-order themes.
• Assess the trustworthiness of the synthesis – Assess the trustworthiness of the interpretations leading up to the synthesis.

Note that thematic analysis/synthesis originally was invented for the analysis of a body of literature. Still, some of the provided ideas were useful to guide our research. As an output, we produced a mindmap with the identified themes and discuss research opportunities. More details later in Sections  4 and 5 .

3 INDUSTRY CASES

In this section, we introduce the 9 industry cases presented at the workshop. For a condensed summary see Table  1 .

The cases reported a diverse spectrum of types of product lines (Software PL, Hardware PL, System PL, System-of-Systems PL). 8 cases identified their project as “ongoing”, one as “future”.

3.1 Industry Case 1

Company . The first industry case, an automotive mechatronics expert, is adopting SPLE at both the software and system levels for several years now to cater to a diverse range of customers and a broad product portfolio.

Approaches . The company utilises a “docs as code” methodology, enabling streamlined updates and maintenance of documentation akin to software code. The configuration of features within the PL is managed through KConfig, that raises questions regarding its efficacy and usability for complex feature configurations in a system PL environment, including difficulties in maintaining an overview of features and configuring them.

Challenges . They have to adhere to the Automotive SPICE standard, necessitating robust management of variability across all work products. Furthermore, in the realm of Continuous Integration and Delivery (CI/CD), they are compelled to provide quick feedback cycles, implement rigorous quality gates, and satisfy the varying acceptance criteria of developers, customers, and projects. A crucial challenge is formulating a viable test strategy compatible with PL characteristics and efficiently addressing stakeholder needs. Additionally, there is a pressing need to restructure the organisation to facilitate a smooth transition from traditional project-based workflows to a more scalable product line engineering framework.

3.2 Industry Case 2

Company . The second case is an international company with subsidiaries in 7 countries plus 60 countries with distributors. They develop and manufacture sensing elements, sensing modules and sensors for air velocity, CO2, humidity, moisture in oil, pressure, temperature, etc. They are maintaining a product line of measurement technology solutions such as (hand-held) measuring devices, humidity calibrators or wireless sensor systems. Their products are highly customisable and there is a massive amount of possible combinations of the components of the product line.

Approaches . The company has developed their own variant management and configuration tool, including description of features and their characteristics, as well as constraints on possible selections of features and characteristics.

Challenges . One of the core challenges they reported was the difficulty in performing verification, which is important in their domain, given the combinatorial explosion of possible products and also to automatically check the validity of created configurations. They have tried approaches such as equivalence class partitioning, but found no vectors since every single characteristic behaves (can behave) different in combination with others.

3.3 Industry Case 3

Company . The third case, an established OEM and supplier in various application domains, is advancing its mission to improve smart living solutions at home by implementing a System of Systems (SoS) PLE approach based upon its existing PLs, including electric solutions, climate & well-being etc. Their SPLE strategy focuses on managing resources effectively, supporting the definition of core products and assets that are foundational to multiple applications. The modularisation of products into manageable units is a key strategy, enabling them to tackle complex systems.

Approaches . Clarifying what constitutes a “module” in the context of SoS and establishing clear guidelines for modular development and integration are essential steps. This ensures that modular components are effectively designed and that they contribute to the overall objectives of the SoS architecture, facilitating smoother transitions and more robust system integrations.

Challenges . They are facing several challenges in this transformation described along the BAPO framework [ 80 ]. Business: transitioning from offering single interconnected systems to an integrated ecosystem. Architecture: managing a diverse portfolio and engineering processes distributed across locations while concurrently handling multiple domains (software, electronics, mechanics). Process: reducing the V&V effort required for variants across different product lines. Organisation: coordinating portfolio and engineering management across distributed locations. To evolve from System to SoS PLE, they consider strategic personnel transfers between different application domains to foster cross-functional expertise and collaboration.

3.4 Industry Case 4

Company . Case 4 is an international company providing metallurgical plant solutions. They maintain several SPLs (automation, control) for machines in the metallurgical process, e.g., ironmaking, steelmaking, continuous casting, hot rolling, cold rolling, and strip processing. Their motivation for systematic variability management stems from the need to consider different kinds of plants and customer requirements for those plants; the fact that every plant has several setups; that there are diverse protocols and diverse suppliers, e.g., of sensors; that there are many interfaces between systems (their own and of other vendors) and software on different levels of the automation pyramid. The company has developed diverse solutions to deal with variability including templates (typicals), standard technological packages, and parameterisation tools.

Approaches . The company has a long-term research project with multiple university partners to work on these challenges and adopt an SPL approach. Specifically, they are working on a multi-disciplinary variability modeling approach allowing to represent variability knowledge from different engineering disciplines in different variability models and relate them via cross-discipline constraints.

Challenges . The core challenges the company reported are the issues resulting from clone-and-own (e.g., code duplication, maintenance issues), the huge system scope, the need to adapt software to diverse hardware platforms (and the need to maintain legacy software for many years), the versioning of variants (customer configuration vs. platform), and the required (re-)modularisation to ease systematic variability management.

3.5 Industry Case 5

Company . The fifth case is an OEM of farming systems who manages diverse product families and maintains long-living systems, often exceeding 30 years in operation. Cybersecurity is a critical concern as it necessitates ongoing software updates to address emerging threats over the lifespan of the hardware.

Approaches . Addressing this concern involves integrating advanced tools for modelling and simulation, fostering a modular architecture that allows for component reuse, and continuously updating cybersecurity measures to protect against evolving threats. The reuse of components across different PLs is a strategic approach to maximise resource efficiency and reduce development costs.

Challenges . Small volumes complicate standardisation and economies of scale. A significant challenge arises when hardware required for testing new software versions is no longer available. This scenario demands innovative solutions such as virtualisation or emulation technologies, ensuring new software can still operate on legacy systems. Tool support for modeling and analysing variability across both space (hardware and system configurations) and time (across system versions and over time) is crucial. These tools have to manage complexity and ensure consistency and reliability across PLs. Moreover, the maintenance of long-living products requires robust strategies to ensure their functional safety and security against cyber threats throughout their extended lifespan.

3.6 Industry Case 6

Company . Our sixth case, an OEM for railway systems, is aiming to enhance its reuse rate through the adoption of modular architectures and building kits tailored for different market segments. The company operates in a market characterised by a relatively small number of customers, where evaluation criteria can vary significantly, even with the same customer. This variability affects bid types, which range from system-only proposals to comprehensive turnkey solutions.

Approaches . Their strategic shift is designed to improve economies of scope, accelerate the bid process, and expedite project execution while providing value-adding flexibility. The modular approach integrates components from various engineering disciplines (electrical, mechanical, networking, software).

Challenges . Even with the broad experience with reuse on all levels of the product structure there are several challenges and strategic questions: how can the company characterise demand variability and adapt product definitions to accommodate such changes? What criteria should be used to delineate a product family, especially when focusing on module-based families? What are the optimal criteria for defining modules and the next level of standardisation related to these modules? How can modularity be assessed efficiently to ensure it meets the desired outcomes and contributes to overall business objectives? How to effectively document a product family architecture that integrates functional, electrical, mechanical, network, and software components while balancing market/customer needs with technical and business objectives? How to develop subsystem variability models that effectively connect with train-level variability models? What strategies should be employed to optimise module development and maintenance? What is the most effective organisational and governance setup to manage modularity?

3.7 Industry Case 7

Company . Our seventh case is a tier-1 supplier in industrial automation, specialising in control systems for electrical motors in high-performance applications. They are transitioning to a new generation of automation products for a diverse range of motor sizes. With a strong foundation in PLE, the company seeks to overcome the sluggishness perceived in the previous product generation's PLE process, which was criticised for being “dead by roadmap.”

Approaches . To speed up delivery of new features, the company has integrated agile methodologies within a CI/CD framework. Each product team manages its own backlog, which is overseen by a Product Owner. Coordination among these backlogs, especially for common features requiring platform team collaboration, is managed through a product owner forum. Additionally, a Governance Board is responsible for setting targets for software platform development, prioritising mid-to-long-term and complex platform cross-cutting development items, and ensuring that resources are adequately allocated. Product teams are permitted to modify shared assets, raising questions about the long-term impact of these changes on system stability.

Challenges . The company maintains solid internal and external interfaces to enhance platform stability, but faces cost pressures that could compromise critical components, threatening the controlled flexibility essential for its PL success. The balance between rapid development and high-quality, stable releases continues to be a pivotal concern in the competitive field of industrial automation. Also, product teams have limited awareness of other products and their software/hardware configurations. There are ongoing concerns about maintaining system consistency during CI/CD, including decisions on test selection (for each pull request) and test duration. Decisions on which hardware configurations and power sizes to test and appropriate configurations for each pull request remain complex. Platform development is perceived as slow due to long lead times for some changes due to backlog prioritisation.

3.8 Industry Case 8

Company . Our eighth case is a tier-1 defense supplier specialising in networked, pre-integrated sensor solutions with applications across ground, air, sea, cyber, and space platforms. The company, which operates on a global scale, manages several product families and variants, maintaining core assets across these groups. Driven by the need for efficient resource utilisation, timely delivery, and cost reductions, the company initiated a strategy focused on increasing modularisation and reuse across its divisions and business units. The primary motivation for this was the management of numerous contracted products under limited resources. The goal was to facilitate modularisation and implement a reuse potential analysis (RPA) to standardise solutions across different product families.

Approaches . Effective PLE implementation requires robust governance from top-level management. For instance, management needs to clearly define the reuse scope, which should extend from product families across business units and international entities. Reuse potentials are identified in a proactive manner, as starting the search for reuse opportunities strategically before developing new products can save significant effort. Regular reviews of product evolution are conducted to spot early reuse opportunities, especially concerning new requirements, technologies, and obsolescence. The RPAs are conducted collaboratively across business units and engineering departments, with regular updates and information sharing through a unified platform. This approach helps in making informed, timely decisions, thus avoiding protracted analyses. Additionally, appointing technical counterparts to product architects is essential for evaluating solutions that are applicable across product families. Finally, the consolidation and effective communication of information regarding target products, variants, features, and solution architectures are critical for maintaining alignment across the organisation.

Challenges . They are facing several challenges: as RPAs initially just were seen as an engineering effort, it required expanded governance to include management and business units to foster strategic reuse. Establishing a design authority is crucial for balancing product evolution with the objectives of modularisation and reuse. RPA revealed that information was often out of sync and varied in granularity, leading to the need for a standardised collaboration platform to ensure consistency in understanding.

3.9 Industry Case 9

Company . Our last case is a supplier of electronic controls for automotive powertrain solutions, with extensive experience with PLE. They manage over 3000 software deliveries annually, utilising a software platform governed by a central variability model.

Approaches . The model incorporates five distinct parts: market variants, context variants (including components and topologies), feature variants, technology variants (pertaining to hardware), and implementation variants (related to software). The process to derive specific project functions (100%) from the platform involves extending the platform functions (150%) with project-specific elements, followed by automatic removal of unselected parts. This is facilitated by a seamless management of system, hardware, and software variants, which includes more than 20,000 software variation points and more than 800,000 calibration parameters.

Challenges . Several challenges arise in managing such a complex hierarchical PL: achieving consistent and efficient variant management across multiple engineering disciplines is crucial. This includes maintaining artefact consistency across the variant management process. Managing variants effectively during V&V and continuous development stages presents logistical and technical difficulties. The evolution of variant models, especially concerning updates and cloud functionality integration, requires ongoing adaptation and flexibility. Managing “PLs of PLs” introduces complexity, requiring scalable and robust variant management solutions. Efficient handling of variants at the pre- and post-compilation stages is necessary to optimise performance and resource allocation. Enhancing the usability of variant management tooling, including tailoring for specific scopes, is essential for effective operation. Collaboration with OEMs, particularly concerning standardisation efforts, is vital for the harmonisation of practices and enhancing mutual benefits.

4 IDENTIFIED CHALLENGES AND THEMES

We first discuss challenges and their relevancy as perceived by practitioners and then identify theme clusters to structure our further discussion. Note that this is based both on material presented at the workshop and discussion after the workshop among participants and researchers to interpret and evolve the information.

4.1 Challenges

During the workshop we identified 17 challenges. We discuss them below, ordered by rating by the industry participants, highest average relevancy rating first (see Figure  2 ).

Topics identified in the workshop and their average relevancy rating defined by the industry case companies.

Efficient Product Line Verification & Validation , (especially in a CI/CD context) received the highest average rating and was a recurring topic at the workshop. While all the companies develop and maintain highly variable systems successfully, they struggle when it comes to dealing with validating and particularly verifying the plethora of possible variants. Often, some standard configurations are tested and then a particular configuration for a customer, which is often inefficient manual work. Several companies reported their own custom-developed solutions to help them automate this. Yet, testing all possible configurations (or at least the most relevant ones) remains a big challenge.

Modularisation (granularity, reuse potential analysis) was also discussed by all companies as very important yet challenging. Specifically, companies agree that to properly adopt SPLE, one needs to properly modularise the (architecture of) systems. Due to the need to deal with long-living legacy systems and a lack of resources, refactoring everything systematically is just not feasible. Also, even if enough resources would be available, it remains challenging to hit the right level of granularity of modularisation (e.g., from feature-level or component-level down to #ifdef and statement level). For several companies, support to analyse the reuse potential of (parts of) their systems would be useful.

Process standardisation (e.g., company-wide, ASPICE [ 82 ]) and PLE was mentioned as both important and challenging. Customers and regulations require process standardisation. With adopting SPLE processes, this also requires standardisation of processes such as domain engineering and creating reusable components.

Product Lines of Product Lines was mentioned by companies as both a fact (it is what they do) and as a challenge. Most approaches companies have found focus on a single product line, and that mostly only in one particular discipline.

Transition from clone-and-own to strategic PLE is what has attracted companies to PLE in the first place. Companies not only naturally start with clone-and-own approaches to reuse, even after adopting a product line approach, they still (have to) follow some clone-and-own approaches, e.g., deriving a first version of a product from the product line for a customer and then cloning and adapting it for several similar customers. Both is challenging: adopting PLE in the first place and, after having adopted it, still living with customers having very specific requirements not allowing for a very high degree of standardisation. High enough to make PLE useful, but not high enough to get rid of clone-and-own completely.

PL Evolution / system lifecycle management of long-living systems (legacy systems, changing hardware platforms). Companies have very long living systems, e.g., company 4 reported their deployments live up to 30 years. Also, companies have to integrate their systems with systems developed by others, even competitors, frequently. Hardware platforms are provided by different vendors and change frequently resulting in significant adaptation efforts. Changing customer requirements, together with the very long lifecycle and changing hardware platforms make PL evolution a big challenge in practice.

Certifications (e.g., safety and security) and PLE are just a necessity for several of our case companies. Certification authorities, however, do not make it particularly easy to certify reusable components that cannot directly be run and tested until a product has been derived. This makes certification challenging in PLE scenarios.

Variability management tool support (integrated, holistic (requirements, architecture, code, V&V), usage of open-source tools). Companies require tools that help them manage variability throughout all development phases, from requirements over architecture, to code, to V&V, and back, integrated with their (application) lifecycle management tools. They are open to adopt open-source tools, yet often made the experience that the lifecycle support is even more limited than in commercial tools. Overall, they find it challenging to use existing variant management tools, because it is difficult to integrate them into their processes. Some of the companies, however, are actively using variant management tools such as the commercial pure::variants  [ 63 ] and the open-source FeatureIDE  [ 28 ]. Yet, “full” process integration is a different, challenging story. Hence, several of the companies have also developed their own solutions.

Involving business into PLE (from an engineering perspective). PLE is often perceived as an engineering effort. However, without involving business, it is impossible to maximise the benefit of systematic reuse. Companies often struggle with that because adopting a PLE approach is motivated and triggered by technical challenges in engineering such as maintenance and evolution effort when following clone-and-own approaches.

MBSE & PLE & long-living systems . Adopting model-driven software engineering approaches, as some of our case companies are doing, leads to the challenge that now models and meta-models become part of long-living systems in a PLE context. Dealing with these additional artefacts, and especially also their consistency, thus becomes challenging.

Diversity of customers / supporting unforeseen variability . Several of our case companies have a very diverse customer base, which in turn often leads to unforeseen (as in cannot be proactively planned) variability in their systems.

System of Systems PLs . The companies deal with systems of systems, i.e., their product line consists of multiple systems on different layers, e.g., of the automation pyramid, developed by different departments/companies, from different disciplines, without a strong SE background. This makes systematic approaches to variability management, across systems and disciplines, even more important.

PL Evaluation (KPIs, maturity, business case). All companies saw it as essential to not “just” adopt a PL approach, but also be able to assess it, e.g., from viewpoints of efficiency, performance, costs, etc. Measuring PL KPIs and, more generally, assessing the maturity of company when it comes to SPLE and its business cases, is both interesting and challenging in practice.

Integrated VM across disciplines . Integrating the different perspectives on variability the different disciplines have is challenging, especially when considering the different backgrounds, notations, and tools used by mechanics, electronics and electrics, software engineering, hydraulics, and many more.

Sharing PL architectural knowledge remains challenging in practice. Companies report that such knowledge about their highly variable systems is often concentrated in few people and that no single person has a complete overview.

PL organisations / governance . Companies struggle with the urge to centralise domain and platform engineering (development for reuse) vs. engineering departments being internationally distributed and involved in multiple projects.

Agile and PLE . All of our case companies to some extent have adopted agile development approaches. Naturally, they also aim for agile approaches to product line engineering. Looking at most, especially early works on SPLE, however, makes it appear not “lightweight” enough to stay agile at the same time.

Identified Themes

4.2 Theme Clusters

Through discussion we (the researchers and practitioners together) then identified 7 clusters of topics (Figure  3 ).

• Modularity / Modularisation refers to the process of structuring work items in distinct modules that encapsulate specific functionalities or features.
• PL Scoping deals with the integrated planning of member products of a PL, involved engineering domains and reusable assets to decide where invest in reuse is economically reasonable and align plans of the different planning levels.
• Variability Management aims for systematic handling of differences and commonalities among PL members. It involves modelling, realising, and maintaining the variations in features that allow each product within the PL to be customised or adapted for a particular customer or market segment.
• Process approaches organise the lifecycle of PLs and involved activities, e.g. alignment in larger organisations, adherence with process standards, or adoption of new process models.
• Verification and Validation (V&V) ensures that the PL meets specified requirements and fulfils its intended purpose, through systematic testing and or systematic analyses.
• Evolution and Maintenance deals with the ongoing processes of updating and refining a product line to accommodate new market demands, technological advancements, and changes in customer requirements.
• Key Performance Indicators (KPI) measure the effectiveness and efficiency of the PLE efforts. They help assess areas like cost reduction, time to market, product quality, and customer satisfaction, providing crucial data to guide decision-making and improvements.

5 DISCUSSION AND IMPLICATIONS

We will now discuss the identified themes (clusters) in more detail – from the viewpoint of a reader who is involved in or interested in industrial application of academic research.

When collecting material and discussing research opportunities for the different clusters, we decided to merge the clusters modularity and variability management as the discussions were overlapping frequently. We discuss literature and research opportunities for the theme clusters modularity and variability management, product line scoping, verification and validation and evolution and maintenance. We kept the theme clusters process and KPI for future work. For all team clusters, we defined one responsible researcher who is an expert in the respective area and will drive further initiatives.

5.1 Modularity and Variability Management

Literature . A plethora of approaches to variability management, variability modelling as well as implementing variable systems, including approaches to modularise systems, have been proposed since the early 1990s [ 64 ]. The most prominent variability modeling approaches are feature modelling and decision modelling [ 19 ]. However, there are also many other approaches, such as OVM [ 62 ], UML-based approaches [ 31 ], and diverse textual variability languages [ 7 ]. Many variability management tools have been proposed [ 6 ], mostly, however, as academic prototypes and only few commercial 2 or well-maintained open-source tools 3 . There were several initiatives to define a standard, e.g., CVL [ 32 ] and UVL [ 76 ], the latter initiative is still ongoing and very active 4 .

Diverse programming paradigms have been proposed to realise modular, highly-variable systems, e.g., feature-oriented software development [ 2 ] and delta-oriented programming [ 70 ], to name but a few. Diverse industry case studies have been published [ 80 ] and collected [ 51 ]. There are also many textbooks [ 2 , 17 , 62 , 80 ].

There have been attempts to capture the variability modelling body of knowledge 5 as well as many surveys [ 6 , 19 , 64 ]. There are several online courses 6 and teaching material collections 7 available, for variability and modularisation specifically, and the overarching topic SPLE in general. Common topics related to variability management and modularisation that are taught at universities are object-oriented programming and design patterns for variability, clone-and-own with version control and build systems, feature-oriented programming, services and microservices, and frameworks and plugins.

Besides SPLC 8 , there is a dedicated international (working) conference on variability modelling 9 .

Research Opportunities . Rabiser et al. [ 65 , 66 , 73 ] have concluded based on multiple empirical studies, that while the perception of academics and industry practitioners is different, there is at least some agreement on the challenges of adopting software product lines. It remains also a key challenge for academics to transfer their research into industry and for industrial practitioners to get access to knowledge from our (academic) community.

The workshop which provided the inspiration and material for this paper is further proof of that, while also being a way to alleviate this challenge by bringing together academia and industry to discuss existing solutions (such as those described in this section) and problems (such as those described in the previous sections).

Regarding variability and modularisation the workshop as well as discussions with practitioners and academics at the workshop and afterwards indicate the following being important avenues for future research motivated by industry challenges:

The need to deal with legacy systems complicates variability management and motivates refactoring such legacy systems into a modular architecture, to even enable an SPL approach. That this is often not done results from the associated human and financial effort. Automation of this refactoring (into a PL [ 41 ]) process is a necessity. Specifically, approaches for variability (or feature) location [ 68 ] or mining [ 40 ] from existing systems, automated generation of reusable artefacts and variability models [ 4 ], automated support for checking and fixing inconsistencies between artefacts and models [ 83 ], automated support for variability model and engineering artefact maintenance [ 50 ] are important. While there are initial efforts in all these directions (some cited above), those typically are limited to very specific scenarios and artefacts and not yet flexible enough to be applied in practice.

The size of real-world systems is motivating research to deal with variability management and modularisation in a way that works in practice. Put differently, scalability of existing approaches, e.g., for variability modelling and modularisation needs to be investigated more, in real empirical studies , not just with toy examples [ 65 ].

Extracting variability knowledge , mostly available in unstructured documents or the heads of engineers, is not just a technical challenge and motivates further research. Particularly, managing variability often requires interdisciplinary knowledge , not “just” software engineering. Especially in cyber-physical and software-intensive systems contexts, other disciplines need to be involved. There are initiatives towards multi-disciplinary approaches to variability management [ 26 , 27 ] to better cover this issue.

Variability management in the future might also benefit from recent generative AI approaches , particularly Large Language Models (LLMs), for instance, to assist in variability modelling and variability implementation [ 1 , 30 ]. In form of a “co-pilot” we expect LLMs to already now be very helpful for industry practitioners.

5.2 Product Line Scoping

Literature . PL scoping defines the member products of a PL and the major (externally visible) common and variable features of the member products, analyses the products from an economic point of view, and controls and schedules the development, production, and marketing of the product line and its products [ 36 ]. This is a pivotal activity to ensure the economical success of a PL. In scoping we should take a problem-oriented perspective (“What does the customer value most?”), but we also need to consider solution-oriented aspects (“What can we implement most easily?”) [ 75 ]. Various approaches have been proposed [ 56 , 71 ] and the field has been surveyed [ 38 , 44 , 48 ] over time. Several industrial case studies and experience reports exist [ 15 , 20 , 23 , 39 ]. Approaches such as Modular Function Deployment (MFD) [ 25 , 29 , 43 ] or Metus [ 8 , 42 ] should be considered from an industrial perspective.

Research Opportunities . Scoping necessitates a multidisciplinary approach, and it would be beneficial to explore how various methods can be integrated across engineering disciplines, product levels, and organisations. There is a need for case studies examining the impact of scoping on modularisation decisions, particularly given the increasing influence of software on product innovation. As in many other PL areas that need to process heterogeneous input, partly consisting of natural language, PL Scoping might benefit from applying LLMs. A particular research challenge, is to start from inconsistent, incomplete information and, nevertheless, arrive at a scope representation that (1) is precise, consistent, and complete and (2) contains sufficient semantics to be useful for further activities (e.g., by defining features and constraints on their combinations, by defining included/excluded functionality in representations amenable for automatic processing).

5.3 Verification and Validation

Literature . Verification and validation in SPLE aims to ensure quality while coping with large numbers of product configurations and constant change. Efforts have to be balanced between domain and application engineering. The field has been surveyed [ 22 , 37 , 45 , 58 , 77 ] and some industrial experience reports exist [ 67 , 80 ]. Testing reference configurations, pairwise testing [ 47 , 49 , 57 , 60 ], model-based testing [ 34 ] approaches, and hardware virtualisation approaches help to mitigate V&V complexity. Several formal analysis techniques have been applied to product lines or have been extended to consider the particular properties for product lines, e.g., Type Checking, Static Analysis, Model-checking, Theorem Proving. Such analyses can then be designed as product-based analyses, family-based analyses (considering the whole PL), or feature-based analyses (looking at the implementation or dependencies of a particular feature) [ 78 ]. Somewhere in between product-based and family-based analyses are sample-based approaches that analyse/test the PL by sampling a subset of products. While they reduce complexity, they risk missing defects due to incomplete coverage  [ 3 ].

Research Opportunities . An area with ongoing research and potential opportunities is traceability between requirements, variability models, and implementation. This is, e.g., needed to ensure coverage of requirements and identify gaps, e.g., to validate regulatory compliance. Such approaches should maximise “return-on-investment”, by reducing cost for usage (e.g., through tool support) and increasing the value (e.g., by automatically generating and executing tests that are mapped to requirements).

5.4 Evolution and Maintenance

Literature . Like any software system that addresses the real world, a software product line has to undergo continuous adaptation and change if it is to remain satisfactory in use [ 46 ]. Compared to general software evolution, for PLs the situation gets more complex due to their specific characteristics [ 13 ]:

• Long life-span . A PL is a long-term investment, with increased return-on-investment with more derived products. On the other hand, it must also evolve to reflect new products.
• Large size and complexity . An SPL represents a whole family of systems, with multiple teams involved, distributed knowledge, and evolution of different parts happening at different speeds.
• More interdependencies . For instance, changes in PL level can affect many products; new requirements on product level can require changes for the whole PL.

Evolution gets even more complex in approaches that use multiple PLs [ 72 ], e.g., multiple PLs with a shared architecture [ 21 ], hierarchical PLs [ 12 ], sharing across PLs [ 81 ].

Deelstra et al. [ 21 ] and Schmid et al.  [ 74 ] report on evolution strategies that commonly occur in practice: In proactive evolution future requirements are planned in advance and added on the PL level. This is usually a pure domain engineering activity, often based on business goals. In constrast, there are three common ways to deal with changes in hindsight , during product derivation:

• During reactive evolution requirements are implemented as they arise, e.g., as variable assets. Advantages are immediate availability on PL level and avoidance of product-specific implementations. Highly automated approaches often aim for this strategy so that complete products can be derived automatically. Disadvantages are required frequent changes on PL level and need to co-evolve products.
• In branch-and-unite , requirements are initially handled on product level, e.g., by creating new product-specific branches, which are later reunified with the SPL. This way, PL changes can be reduced and emphasis can be put on the product first. However, the merge can become complex and error-prone.
• A bulk situation occurs when we create too many branches by evolving on product level. This can lead to maintenance problems and major effort is required to reintegrate all branches.

There are some model-driven approaches to PL evolution, e.g., EvoFM [ 13 , 61 ]. Some models focussing on differences can also be used to describe evolution, e.g., delta models by Schäfer et al.  [ 70 ] or change sets by Hendrickson et al.  [ 35 ]. However, the overall use of such approaches in industrial practice is limited.

Many other approaches to PL evolution have been described, well summarised in a systematic literature review by Marques et al. [ 50 ]. They conclude that there is no consensus about the evolution process and that while case studies are quite popular, few industry-sized case studies are publicly available. Furthermore, few of the proposed PL evolution techniques come with tool support.

There is some tool support for change impact analysis. For instance, Heider et al. [ 33 ] use regression testing to asses the effects of changes in variability models on derived products. This can potentially provide rapid feedback on unintended consequences of changes. However, in general tool support is sparse [ 50 ].

Research Opportunities . Within evolution of PLs, the research area with most potential for industrial practice is probably automation and tool support. This affects all areas mentioned above, e.g., identification of features, construction of variability models, and transformation of assets with variability into a full product line.

A related topic that currently receives a lot of attention, and might also be somewhat over-hyped, is whether LLMs are useful for these tasks, e.g., to refactor artefacts or to transform artefacts into a PL. For general development operations, e.g., refactoring, extracting methods, or reorganising a class hierarchy there is powerful support in IDEs like IntelliJ IDEA 10 or Microsoft Visual Studio Code 11 – this is only getting amplified by recently added AI assistant functions like GitHub copilot. Similar mechanisms could be offered in feature-aware or variability-aware variants.

In software evolution, we have to deal with inconsistencies that arise naturally (e.g., when requirements change but the implementation has not changed yet or when parts of the system change but related dependent parts have not changed yet). Handling such inconsistencies, e.g., by propagating the necessary changes through the PL could be a promising research area. Again, LLMs might be used for generating necessary artefacts/changes. However, there is little experience of how well they will perform, especially if the goal is to establish a correct and consistent PL.

We still need more empirical in-vivo research, providing, e.g., an evaluation of approaches in realistic projects, helping to understand why some projects succeed or fail in practice.

Alos, it seems that research on migration (from legacy systems into a PL) emphasises early phases (e.g., identification of features, variability analysis), with less works dealing with the transformation into a product, i.e., actually “doing” the migration [ 5 ]. Hence, there might be research opportunities in developing practical, tool-supported approaches that allow such migration.

5.5 So What?

Let us take a step back and look again at the main question this paper raises: there is considerable research in SPLE, nevertheless industry practitioners are still struggling in everyday projects when trying to make product lines work in practice – why is that?

In reviewing the workshop and the extracted information, it seems that there are different kinds of challenges and “pain points”, which require different approaches to move forward:

• Industry needs to catch up – Industry does not know approaches and techniques that are actually available. Way forward: Industry needs to inform themselves, collaborate and communicate with researchers.
• Academics need to catch up – They do not know enough about the real world, have biased/incomplete understanding of industrial practice. Way forward: They should not assume they know or rely only on literature to identify problems, but elicit problems and challenges from industry.
• Problems are inherently hard – Some challenges are just hard by the nature of the problem (complexity and scale of real systems, constant change caused by the need to address changing requirements and technologies). Way forward: Additional research needed; potentially joint forces of industry practitioners and academics can tackle the problems; technological progress opens new opportunities.

Based on these pain points we aim to explicitly answer our second research question, i.e., what are the reasons for the challenges industry has and what are existing solutions:

We summarise a potential way forward, from our perspective and based on our interpretation of opinions expressed by the workshop participants as answer to our third research question:

5.6 Limitations and Threats to Validity

Generalisability . Our case companies are from a wide spectrum of domains that have traditionally participated in the SPLE community. Hence, we believe that the reported challenges and opportunities are representative for the community. On the other hand, we should be aware that there are industries with software-intensive products that have not been connected with the SPLE community, e.g., banking and financial services, cyber-security, education, robotics and autonomous vehicles. These domains might have their own objectives and challenges, which might not be reflected in the reported results. Also, companies in our case are mostly from Europe, which might also have had an influence on our results.

Selection bias . We selected companies based on our own networks. We naturally selected companies we knew are working on product lines and can report about challenges.

Influence by researchers . We actively participated in the workshop and also performed the grouping of challenges to theme clusters. However, we followed a systematic research method (thematic analysis) to extract our results.

6 RELATED WORK

Over more than three decades diverse researchers have discussed the challenges industry faced with adopting SPLs [ 9 , 10 , 11 , 16 , 51 , 53 , 80 ]. From the nineties to 2024, we see many challenges, especially those also described in this paper, remain relevant for industry. For example, Berger et al. [ 9 ] presented the results of a survey distributed among industry practitioners (35 responses analysed) to study to what extent/how variability modelling is done in industrial practice. Similarly to our conclusions, they conclude that industry is still experimenting with various solutions.

Berger et al. [ 10 ] also recently presented a multiple-case study in which they analyse the current adoption of variability management techniques in twelve medium- to large-scale industrial cases in domains such as automotive, aerospace or railway systems. They conclude with a brief discussion of challenges, most notably that “the adoption of SPLE concepts is still a tool-integration problem, given all the different types of artefacts and existing tooling, which engineers are familiar with and that is core to the development”.

While some challenges might be hard to address due to the inherent characteristics of complex software systems, we firmly believe that cooperation between academia and industry [ 66 ] is the only way to effectively address most of the challenges.

7 CONCLUSION

Adopting system and software product line engineering remains desirable yet challenging for industry despite a plethora of approaches proposed in academia. The domain-specific needs of industry, and inherent industry challenges, such as the need to deal with legacy systems and the size and complexity of highly-variable systems, need to be taken into account.

In this paper, we summarised challenges of 9 companies from industry, clustered into 7 theme clusters. For 4 of these clusters, we discussed existing solutions to address challenges and opportunities for further research. More frequent interaction between academia and industry in diverse formats should help to exchange and discuss challenges, use cases, knowledge and solutions.

ACKNOWLEDGMENTS

The financial support by the Austrian Federal Ministry for Digital and Economic Affairs, the National Foundation for Research, Technology and Development, and the Christian Doppler Research Association is gratefully acknowledged. This work is supported, in part, by Science Foundation Ireland grant 13/RC/2094. We want to thank all participants of the SPLC 2023 industry challenges workshop, particularly the representatives from the nine companies who presented their challenges.

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3 https://featureide.github.io/

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5 https://github.com/SECPS/VMBoK

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SPLC '24, September 02–06, 2024, Dommeldange, Luxembourg

© 2024 Copyright held by the owner/author(s). ACM ISBN 979-8-4007-0593-9/24/09. DOI: https://doi.org/10.1145/3646548.3672587

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New roadmap toward social sustainability, from physical structures to perceived spaces.

1. Introduction

2. materials and methods, 2.1. literature review process:, 2.2. research strategy and data collection, 2.3. data analysis.

• Familiarization: Engaging deeply with the selected literature to understand the breadth and depth of the content.
• Theme identification: Recognizing significant themes related to physical and perceived density, and their influence on social sustainability.
• Theme development: Developing these themes into coherent categories that reflect the complex interactions between urban density and social sustainability.
• Theme review and refinement: Refining the themes to ensure they accurately represent the data and are aligned with the study’s objectives.
• Integration into framework: Integrating the final themes into a comprehensive framework that informs the study’s conclusions about the relationship between urban density and social sustainability.

3. Literature Review

3.1. the literature on density and physical structures.

3.2. The Literature on Resident Perception of Density

3.3. The Literature on the Interplay between Social Sustainability and Density

4.1. Summary of Key Findings

4.1.1. Findings from Density and Physical Structures Studies

4.1.2. Findings from Resident Perception of Density Studies

4.1.3. Findings from Social Sustainability and Housing Density Studies

4.2. Thematic Findings

4.2.1. analysis of physical density factors.

• Building height and spacing: Tall buildings and closely spaced structures often create a sense of enclosure, leading to perceptions of overcrowding. This has a direct impact on mental well-being and satisfaction among residents [ 12 , 31 ].
• Population and residential density: High population density enhances urban efficiency by reducing per capita land consumption and supporting sustainable transportation systems. However, it also contributes to perceived crowding if not adequately balanced with infrastructure and amenities [ 1 , 4 ].
• Floor Area Ratio (FAR) and Building Coverage Ratio (BCR): Higher FAR values can support urban density by reducing urban sprawl but can also lead to reduced access to sunlight and ventilation, impacting environmental quality and residents’ quality of life [ 21 , 23 ].
• Design and layout of urban spaces: The design and layout of urban spaces play a crucial role in shaping perceptions of density. Well-designed public spaces and green areas can mitigate the negative impacts of high physical density, enhancing comfort and privacy [ 9 , 24 ].

4.2.2. Perceived Density and Its Implications

• Visual perception: Areas with well-maintained green spaces and attractive architecture are perceived as less dense, even in physically dense environments, leading to improved mental well-being and greater satisfaction [ 7 , 12 , 31 ].
• Functional density: High functional density, where amenities and services are within walking distance, enhances the sense of convenience and livability, reducing negative perceptions of density [ 33 , 38 ].
• Social density: Public spaces that support positive social interactions contribute to a stronger sense of community cohesion, reducing feelings of isolation and enhancing social sustainability [ 8 , 9 , 10 ].
• Spatial perception: Well-connected streets and sufficient open spaces create a sense of openness, which helps alleviate the negative perceptions associated with high density [ 7 , 39 ].

4.2.3. Interplay between Social Sustainability and Housing Density

• Inclusivity and accessibility: Ensuring inclusivity through accessible and affordable housing is crucial for social sustainability in high-density environments. The integration of diverse housing options prevents social segregation and supports community cohesion [ 28 , 29 ].
• Community engagement: The active participation of residents in planning and decision-making processes is essential for fostering social sustainability. Well-designed public spaces and amenities facilitate this engagement, enhancing the overall quality of life [ 8 , 29 ].
• Cultural diversity and social interaction: Urban designs that embrace cultural diversity and promote social interaction in public spaces are more likely to achieve higher levels of social sustainability. These factors contribute to a vibrant, resilient, and inclusive urban environment [ 8 , 29 ].

4.2.4. Social Sustainability Criteria

• Inclusivity: This is the ability of urban environments to provide equal opportunities for all community members, regardless of their socio-economic background. Inclusivity is supported by diverse housing options and equitable access to amenities and services [ 28 ].
• Community engagement: This is the level of resident participation in planning and decision-making processes. Community engagement is enhanced by accessible public spaces and amenities that encourage social interaction and collective involvement [ 29 ].
• Quality of life: Overall well-being, including health, housing satisfaction, and access to essential services, is a crucial component of social sustainability. Quality of life is influenced by the availability of green spaces, the design and layout of urban environments, and the effective management of density [ 21 , 24 ].
• Cultural diversity: This is the extent to which cultural diversity is embraced and promoted within the community. Cultural diversity is supported by inclusive urban design that reflects the values and identities of diverse population groups [ 8 ].
• Social cohesion: The strength of social bonds and a sense of belonging and security among residents are critical for social sustainability. Social cohesion is fostered by well-designed public spaces that encourage positive social interactions and community building [ 8 , 9 ].

5. Implication of Findings

5.1. the impact of density on social sustainability, 5.1.1. criteria for assessing social sustainability.

• Inclusivity: The literature underscores the importance of designing urban environments that offer equal opportunities for all community members, regardless of socio-economic background. Inclusivity is enhanced when affordable housing is integrated into high-density areas, along with accessible public spaces that foster social equity [ 2 , 28 ]. Churchman [ 4 ] notes that unmanaged increases in population density can exacerbate social tensions if urban spaces do not adequately address inclusivity, highlighting the need for thoughtful urban planning that prioritizes equal access to resources and services.
• Community engagement: Effective community engagement is critical for achieving social sustainability in dense urban settings. The literature highlights the role of well-designed public spaces in facilitating resident participation in planning and decision-making processes [ 9 , 29 ]. Woodcraft et al. [ 8 ] emphasize that urban environments that encourage community interaction and cultural diversity contribute significantly to social cohesion. Our findings align with this perspective, showing that integrated public spaces enhance community engagement, thereby reinforcing the social fabric of high-density areas.
• Quality of life: Quality of life is a multifaceted concept influenced by factors such as health, housing satisfaction, and access to essential services. The literature suggests that high-density urban environments can support a high quality of life if they include well-designed green spaces and accessible amenities [ 1 , 2 ]. Forsyth [ 5 ] notes that while high density can reduce land consumption and support sustainable transportation systems, it is crucial to balance these benefits with the provision of livable spaces that enhance residents’ overall satisfaction. Our study confirms that managing density through thoughtful urban design can mitigate potential negative impacts, thereby improving quality of life.
• Cultural diversity: Cultural diversity plays a vital role in fostering social cohesion within high-density urban areas. The literature demonstrates that urban design that embraces cultural diversity leads to vibrant, multicultural neighborhoods [ 8 , 29 ]. Our findings support this view, indicating that urban environments that promote cultural interaction and inclusivity are more likely to achieve social sustainability. This aligns with Healey [ 29 ] and Woodcraft et al. [ 8 ], who argue that culturally diverse urban designs contribute to stronger community bonds and resilience.
• Social cohesion: Social cohesion, defined by the strength of social bonds and the sense of belonging among residents, is crucial for social sustainability. The literature suggests that well-designed public spaces that facilitate positive social interactions are key to enhancing social cohesion in high-density environments [ 9 , 10 ]. Dempsey et al. [ 11 ] highlight that public spaces that encourage frequent and meaningful social interactions can alleviate the potential downsides of high density, such as feelings of overcrowding and isolation. Our findings resonate with this perspective, showing that urban spaces designed to foster social interaction contribute significantly to an overall sense of community and well-being.
• To further elucidate the relationship between the discussed social sustainability indicators and urban density, Figure 3 present a comprehensive framework that illustrates how physical and perceived density interact with these indicators.

5.1.2. Impact of Physical Density on Resident Perception

• Building height and spacing: Tall buildings and closely spaced structures often create a sense of enclosure, leading to perceptions of overcrowding and reduced personal space. The literature indicates that areas with taller buildings tend to feel denser, affecting residents’ mental well-being and satisfaction [ 12 ]. Similarly, narrow streets and dense building arrangements could create a feeling of high spatial density, impacting the perception of openness [ 31 ].
• Population and residential density: High population and residential density can enhance urban efficiency but may also contribute to perceived crowding if not balanced with adequate infrastructure and amenities. Studies have shown that high population density can enhance urban efficiency by reducing per capita land consumption and supporting sustainable public transportation systems [ 1 ]. However, there is also the potential for overcrowding and stress on public services if high density is not managed properly [ 4 ].
• Floor Area Ratio (FAR) and Building Coverage Ratio (BCR): Higher FAR and BCR values indicate more intensive land use, which can impact residents’ perception of their living conditions. The studies suggest that while higher FAR values can support urban density by reducing urban sprawl, they can also lead to reduced access to sunlight and ventilation, affecting environmental quality [ 21 ].
• Design and layout of urban spaces: Well-designed public spaces and green areas can mitigate the negative impacts of high physical density. Researchers argue that high-density urban spaces need to be designed thoughtfully to ensure comfort and privacy, significantly affecting how residents perceive density [ 24 , 36 ].
• Resilience/adaptability: Resilience refers to the ability of urban systems to accommodate changes and unexpected events, such as natural disasters or rapid population growth, without adversely affecting quality of life. High resilience in urban environments fosters a sense of security and stability among residents, positively impacting their perceptions of density. Studies suggest that resilient urban systems can reduce the stress associated with high density and contribute to improved social interaction and community integration [ 15 ].
• Access to amenities and services: When residents have easy access to essential services such as shops, schools, healthcare, and recreational facilities, their perceptions of the urban environment are significantly enhanced. Research indicates that good access to these services reduces perceived overcrowding and improves comfort and quality of life [ 9 , 19 ].
• Figure 3 shows the role of physical density parameters such as building height, spacing, population density, and urban design in shaping resident perceptions.

Click here to enlarge figure

5.1.3. Impact of Perceived Density on Social Sustainability

• Visual density: This means the aesthetics and design of buildings and urban spaces. Studies have shown that areas with well-maintained green spaces, attractive architecture, and thoughtful urban design are perceived as less dense, even if they have high physical density [ 7 ]. This can lead to improved mental well-being and greater satisfaction within the living environment [ 31 ]. Additionally, elements such as building facades, street furniture, and public art contribute to a visually stimulating environment, which can positively influence residents’ perceptions [ 12 ].
• Functional density: This means the concentration of amenities and services within walking distance. High functional density means that residents have easy access to essential services such as grocery stores, schools, healthcare facilities, and recreational areas. Studies indicate that when these amenities are within close proximity, it reduces perceived distance and enhances the sense of convenience and livability [ 33 , 38 ]. Furthermore, mixed-use developments that integrate residential, commercial, and recreational spaces create a dynamic urban environment that fosters social interactions and community engagement [ 21 ]. Additionally, the integration of affordable housing within these areas is crucial. Affordable housing options help prevent socio-economic segregation by allowing residents from diverse income levels to live close to essential services and amenities. This integration supports a more inclusive community, enhancing social cohesion and promoting a balanced urban environment [ 28 , 29 ].
• Social density: This means the number of social interactions in public spaces. Well-used public spaces that support positive social interactions can enhance community cohesion and improve perceptions of high density. Areas with active public spaces, such as parks, plazas, and community centers where people can gather, socialize, and participate in communal activities, are perceived more positively [ 9 , 10 ]. Social density that promotes inclusivity and diversity can mitigate feelings of isolation and alienation, contributing to a sense of belonging and community well-being [ 8 ]. Furthermore, cultural diversity within these spaces plays a key role in enriching community life. Diverse cultural backgrounds contribute to vibrant social interactions, strengthening social bonds and enhancing an overall sense of belonging and resilience in high-density environments [ 8 , 29 ].
• Spatial density: This means the layout and connectivity of streets and open spaces which impact the perception of openness or confinement in urban areas. The literature shows that proper spatial planning, including well-connected streets and sufficient open spaces, can mitigate negative perceptions of high density. Urban layouts that prioritize pedestrian pathways, open plazas, and interconnected green spaces help create a sense of openness and freedom of movement [ 7 , 39 ]. Conversely, areas with poorly connected streets, a lack of public spaces, and limited green areas can feel congested and claustrophobic, negatively affecting residents’ perceptions and quality of life [ 36 ].

5.2. Conceptual Model of the Impact of Density on Social Sustainability

• Impact of physical density on perception: Physical density factors, such as building height and population density, influence residents’ perceptions of their environment. For example, taller buildings and higher population densities can create a sense of overcrowding, reducing personal space and impacting mental well-being.
• Mediating role of perceived density: Perceived density can either mitigate or exacerbate the effects of physical density on social sustainability. For instance, green spaces and aesthetically pleasing urban designs can improve environmental perception and reduce the negative impacts of high physical density. On the other hand, poor design and a lack of amenities can intensify the negative perception of density, leading to lower quality of life and social cohesion.
• Impact on social sustainability: The integrated effects of physical and perceived density influence the social sustainability criteria. Positive perceptions of density, supported by good urban design and community amenities, can enhance social cohesion, inclusivity, and quality of life. Conversely, negative perceptions can lead to social fragmentation, reduced quality of life, and decreased social capital.

• Building height and spacing: » Influence how enclosed or open an area feels, affecting perceptions of crowding. » Impact quality of life by determining access to light and air and providing space for social interactions.
• Population and residential density: Higher densities can » lead to perceptions of crowding if infrastructure does not match the demand. » Affect inclusivity and quality of life by influencing housing availability and community services.
• Floor Area Ratio (FAR) and Building Coverage Ratio (BCR): High FAR and BCR values » indicate intensive land use » impacting environmental quality and perceived crowding. If properly managed, they » can support efficient land use, enhancing quality of life and access to public spaces.
• Urban design: Well-designed urban spaces can » mitigate the negative perceptions of high density by providing comfort and aesthetic appeal » and promote cultural diversity and social interactions through inclusive design.
• Building design and aesthetics: » Influence visual density and the attractiveness of the area. » Contribute to quality of life by creating aesthetically pleasing environments.
• Green spaces and landscaping: » Provide visual relief and reduce perceptions of crowding. » Enhance quality of life by offering recreational spaces and improving environmental quality.
• Availability of amenities and accessibility to services: High functional density » improves convenience and livability. » Support inclusivity and community engagement by ensuring access to essential services.
• Public space usage and community activities: » Influence social density and community cohesion. » Foster social interactions and community engagement by providing venues for social activities.
• Street layout and connectivity: » Influence navigability and perceptions of congestion. » Enhance quality of life by improving accessibility and reducing travel times.
• Open spaces: » Reduce perceived density by providing areas for relaxation and recreation. » Enhance quality of life and support social interactions in public spaces.

6. Discussion and Conclusion

6.1. challenges and comparisons with the existing literature, 6.2. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest.

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Share and Cite

Al-saedi, A.Z.M.; Rasul, H.Q. New Roadmap toward Social Sustainability, from Physical Structures to Perceived Spaces. Sustainability 2024 , 16 , 7716. https://doi.org/10.3390/su16177716

Al-saedi AZM, Rasul HQ. New Roadmap toward Social Sustainability, from Physical Structures to Perceived Spaces. Sustainability . 2024; 16(17):7716. https://doi.org/10.3390/su16177716

Al-saedi, Abdulrazaq Zamil Menshid, and Hoshyar Qadir Rasul. 2024. "New Roadmap toward Social Sustainability, from Physical Structures to Perceived Spaces" Sustainability 16, no. 17: 7716. https://doi.org/10.3390/su16177716

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