Requirements engineering for software product lines: A systematic literature review

ContextSoftware product line engineering (SPLE) is a growing area showing promising results in research and practice. In order to foster its further development and acceptance in industry, it is necessary to assess the quality of the research so that proper evidence for adoption and validity are ensured. This holds in particular for requirements engineering (RE) within SPLE, where a growing number of approaches have been proposed.ObjectiveThis paper focuses on RE within SPLE and has the following goals: assess research quality, synthesize evidence to suggest important implications for practice, and identify research trends, open problems, and areas for improvement.MethodA systematic literature review was conducted with three research questions and assessed 49 studies, dated from 1990 to 2009.ResultsThe evidence for adoption of the methods is not mature, given the primary focus on toy examples. The proposed approaches still have serious limitations in terms of rigor, credibility, and validity of their findings. Additionally, most approaches still lack tool support addressing the heterogeneity and mostly textual nature of requirements formats as well as address only the proactive SPLE adoption strategy.ConclusionsFurther empirical studies should be performed with sufficient rigor to enhance the body of evidence in RE within SPLE. In this context, there is a clear need for conducting studies comparing alternative methods. In order to address scalability and popularization of the approaches, future research should be invested in tool support and in addressing combined SPLE adoption strategies.     

A systematic review of evaluation of variability management approaches in software product lines

Context

Variability management (VM) is one of the most important activities of software product-line engineering (SPLE), which intends to develop software-intensive systems using platforms and mass customization. VM encompasses the activities of eliciting and representing variability in software artefacts, establishing and managing dependencies among different variabilities, and supporting the exploitation of the variabilities for building and evolving a family of software systems. Software product line (SPL) community has allocated huge amount of effort to develop various approaches to dealing with variability related challenges during the last two decade. Several dozens of VM approaches have been reported. However, there has been no systematic effort to study how the reported VM approaches have been evaluated.

Objective

The objectives of this research are to review the status of evaluation of reported VM approaches and to synthesize the available evidence about the effects of the reported approaches.

Method

We carried out a systematic literature review of the VM approaches in SPLE reported from 1990s until December 2007.

Results

We selected 97 papers according to our inclusion and exclusion criteria. The selected papers appeared in 56 publication venues. We found that only a small number of the reviewed approaches had been evaluated using rigorous scientific methods. A detailed investigation of the reviewed studies employing empirical research methods revealed significant quality deficiencies in various aspects of the used quality assessment criteria. The synthesis of the available evidence showed that all studies, except one, reported only positive effects.

Conclusion

The findings from this systematic review show that a large majority of the reported VM approaches have not been sufficiently evaluated using scientifically rigorous methods. The available evidence is sparse and the quality of the presented evidence is quite low. The findings highlight the areas in need of improvement, i.e., rigorous evaluation of VM approaches. However, the reported evidence is quite consistent across different studies. That means the proposed approaches may be very beneficial when they are applied properly in appropriate situations. Hence, it can be concluded that further investigations need to pay more attention to the contexts under which different approaches can be more beneficial.     

Supporting distributed product configuration by integrating heterogeneous variability modeling approaches

ContextIn industrial settings products are developed by more than one organization. Software vendors and suppliers commonly typically maintain their own product lines, which contribute to a larger (multi) product line or software ecosystem. It is unrealistic to assume that the participating organizations will agree on using a specific variability modeling technique—they will rather use different approaches and tools to manage the variability of their systems.ObjectiveWe aim to support product configuration in software ecosystems based on several variability models with different semantics that have been created using different notations.MethodWe present an integrative approach that provides a unified perspective to users configuring products in multi product line environments, regardless of the different modeling methods and tools used internally. We also present a technical infrastructure and a prototype implementation based on web services.ResultsWe show the feasibility of the approach and its implementation by using it with the three most widespread types of variability modeling approaches in the product line community, i.e., feature-based, OVM-style, and decision-oriented modeling. To demonstrate the feasibility and flexibility of our approach, we present an example derived from industrial experience in enterprise resource planning. We further applied the approach to support the configuration of privacy settings in the Android ecosystem based on multiple variability models. We also evaluated the performance of different model enactment strategies used in our approach.ConclusionsTools and techniques allowing stakeholders to handle variability in a uniform manner can considerably foster the initiation and growth of software ecosystems from the perspective of software reuse and configuration.     

Empirical evaluation of a decision support model for adopting software product line engineering

ContextThe software product line engineering (SPLE) community has provided several different approaches for assessing the feasibility of SPLE adoption and selecting transition strategies. These approaches usually include many rules and guidelines which are very often implicit or scattered over different publications. Hence, for the practitioners it is not always easy to select and use these rules to support the decision making process. Even in case the rules are known, the lack of automated support for storing and executing the rules seriously impedes the decision making process.ObjectiveWe aim to evaluate the impact of a decision support system (DSS) on decision-making in SPLE adoption. In alignment with this goal, we provide a decision support model (DSM) and the corresponding DSS.MethodFirst, we apply a systematic literature review (SLR) on the existing primary studies that discuss and present approaches for analyzing the feasibility of SPLE adoption and transition strategies. Second, based on the data extraction and synthesis activities of the SLR, the required questions and rules are derived and implemented in the DSS. Third, for validation of the approach we conduct multiple case studies.ResultsIn the course of the SLR, 31 primary studies were identified from which we could construct 25 aspects, 39 questions and 312 rules. We have developed the DSS tool Transit-PL that embodies these elements.ConclusionsThe multiple case study validation showed that the adoption of the developed DSS tool is justified to support the decision making process in SPLE adoption.     

The DOPLER meta-tool for decision-oriented variability modeling: a multiple case study

The variability of a product line is typically defined in models. However, many existing variability modeling approaches are rigid and don’t allow sufficient domain-specific adaptations. We have thus been developing a flexible and extensible approach for defining product line variability models. Its main purposes are to guide stakeholders through product derivation and to automatically generate product configurations. Our approach is supported by the DOPLER (Decision-Oriented Product Line Engineering for effective Reuse) meta-tool that allows modelers to specify the types of reusable assets, their attributes, and dependencies for their specific system and context. The aim of this paper is to investigate the suitability of our approach for different domains. More specifically, we explored two research questions regarding the implementation of variability and the utility of DOPLER for variability modeling in different domains. We conducted a multiple case study consisting of four cases in the domains of industrial automation systems and business software. In each of these case studies we analyzed variability implementation techniques. Experts from our industry partners then developed domain-specific meta-models, tool extensions, and variability models for their product lines using DOPLER. The four cases demonstrate the flexibility of the DOPLER approach and the extensibility and adaptability of the supporting meta tool.     

Analyzing impact of experience curve on ROI in the software product line adoption process

ContextExperience curve is a well-known concept in management and education science, which explains the phenomenon of increased worker efficiency with repetitive production of a good or service.ObjectiveWe aim to analyze the impact of the experience curve effect on the Return on Investment (ROI) in the software product line engineering (SPLE) process.MethodWe first present the results of a systematic literature review (SLR) to explicitly depict the studies that have considered the impact of experience curve effect on software development in general. Subsequently, based on the results of the SLR, the experience curve effect models in the literature, and the SPLE cost models, we define an approach for extending the cost models with the experience curve effect. Finally, we discuss the application of the refined cost models in a real industrial context.ResultsThe SLR resulted in 15 primary studies which confirm the impact of experience curve effect on software development in general but the experience curve effect in the adoption of SPLE got less attention. The analytical discussion of the cost models and the application of the refined SPLE cost models in the industrial context showed a clear impact of the experience curve effect on the time-to-market, cost of development and ROI in the SPLE adoption process.ConclusionsThe proposed analysis with the newly defined cost models for SPLE adoption provides a more precise analysis tool for the management, and as such helps to support a better decision making.     

A systematic review and an expert survey on capabilities supporting multi product lines

ContextComplex software-intensive systems comprise many subsystems that are often based on heterogeneous technological platforms and managed by different organizational units. Multi product lines (MPLs) are an emerging area of research addressing variability management for such large-scale or ultra-large-scale systems. Despite the increasing number of publications addressing MPLs the research area is still quite fragmented.ObjectiveThe aims of this paper are thus to identify, describe, and classify existing approaches supporting MPLs and to increase the understanding of the underlying research issues. Furthermore, the paper aims at defining success-critical capabilities of infrastructures supporting MPLs.MethodUsing a systematic literature review we identify and analyze existing approaches and research issues regarding MPLs. Approaches described in the literature support capabilities needed to define and operate MPLs. We derive capabilities supporting MPLs from the results of the systematic literature review. We validate and refine these capabilities based on a survey among experts from academia and industry.ResultsThe paper discusses key research issues in MPLs and presents basic and advanced capabilities supporting MPLs. We also show examples from research approaches that demonstrate how these capabilities can be realized.ConclusionsWe conclude that approaches supporting MPLs need to consider both technical aspects like structuring large models and defining dependencies between product lines as well as organizational aspects such as distributed modeling and product derivation by multiple stakeholders. The identified capabilities can help to build, enhance, and evaluate MPL approaches.     

Variability in quality attributes of service-based software systems: A systematic literature review

ContextVariability is the ability of a software artifact (e.g., a system, component) to be adapted for a specific context, in a preplanned manner. Variability not only affects functionality, but also quality attributes (e.g., security, performance). Service-based software systems consider variability in functionality implicitly by dynamic service composition. However, variability in quality attributes of service-based systems seems insufficiently addressed in current design practices.ObjectiveWe aim at (a) assessing methods for handling variability in quality attributes of service-based systems, (b) collecting evidence about current research that suggests implications for practice, and (c) identifying open problems and areas for improvement.MethodA systematic literature review with an automated search was conducted. The review included studies published between the year 2000 and 2011. We identified 46 relevant studies.ResultsCurrent methods focus on a few quality attributes, in particular performance and availability. Also, most methods use formal techniques. Furthermore, current studies do not provide enough evidence for practitioners to adopt proposed approaches. So far, variability in quality attributes has mainly been studied in laboratory settings rather than in industrial environments.ConclusionsThe product line domain as the domain that traditionally deals with variability has only little impact on handling variability in quality attributes. The lack of tool support, the lack of practical research and evidence for the applicability of approaches to handle variability are obstacles for practitioners to adopt methods. Therefore, we suggest studies in industry (e.g., surveys) to collect data on how practitioners handle variability of quality attributes in service-based systems. For example, results of our study help formulate hypotheses and questions for such surveys. Based on needs in practice, new approaches can be proposed.     

A holistic approach to feature modeling for product line requirements engineering

Requirements engineering (RE) offers the means to discover, model, and manage the requirements of the products that comprise a product line, while software product line engineering (SPLE) offers the means of realizing the products’ requirements from a common base of software assets. In practice, however, RE and SPLE have proven to be less complementary than they should. While some RE techniques, particularly goal modeling, support the exploration of alternative solutions, the appropriate solution is typically conditional on context and a large product line may have many product-defining contexts. Thus, scalability and traceability through into product line features are key challenges for RE. Feature modeling, by contrast, has been widely accepted as a way of modeling commonality and variability of products of a product line that may be very complex. In this paper, we propose a goal-driven feature modeling approach that separates a feature space in terms of problem space and solution space features, and establish explicit mappings between them. This approach contributes to reducing the inherent complexity of a mixed-view feature model, deriving key engineering drivers for developing core assets of a product line, and facilitating the quality-based product configuration.     

A systematic mapping study of search-based software engineering for software product lines

ContextSearch-Based Software Engineering (SBSE) is an emerging discipline that focuses on the application of search-based optimization techniques to software engineering problems. Software Product Lines (SPLs) are families of related software systems whose members are distinguished by the set of features each one provides. SPL development practices have proven benefits such as improved software reuse, better customization, and faster time to market. A typical SPL usually involves a large number of systems and features, a fact that makes them attractive for the application of SBSE techniques which are able to tackle problems that involve large search spaces.ObjectiveThe main objective of our work is to identify the quantity and the type of research on the application of SBSE techniques to SPL problems. More concretely, the SBSE techniques that have been used and at what stage of the SPL life cycle, the type of case studies employed and their empirical analysis, and the fora where the research has been published.MethodA systematic mapping study was conducted with five research questions and assessed 77 publications from 2001, when the term SBSE was coined, until 2014.ResultsThe most common application of SBSE techniques found was testing followed by product configuration, with genetic algorithms and multi-objective evolutionary algorithms being the two most commonly used techniques. Our study identified the need to improve the robustness of the empirical evaluation of existing research, a lack of extensive and robust tool support, and multiple avenues worthy of further investigation.ConclusionsOur study attested the great synergy existing between both fields, corroborated the increasing and ongoing interest in research on the subject, and revealed challenging open research questions.     

A pattern-based model-driven approach for situational method engineering

ContextConstructing bespoke software development methodologies for specific project situations has become a crucial need, giving rise to Situational Method Engineering (SME). Compared with Software Engineering, SME has a long way to go yet; SME approaches are especially deficient as to support for modeling, portability, and automation. Model-Driven Development (MDD) has been effectively used for addressing these issues in Software Engineering, and is also considered a promising approach for resolving them in SME.ObjectiveThis paper aims to address the shortcomings of existing SME approaches by introducing a novel MDD approach, specifically intended for SME purposes, that uses a pattern-based approach for model transformation.MethodDeveloping a MDD approach for SME requires that a modeling framework, consisting of modeling levels, be defined for modeling software development methodologies. Transformation patterns should also be specified for converting the models from one level to the next. A process should then be defined for applying the framework and transformations patterns to real SME projects. The resulting MDD approach requires proper evaluation to demonstrate its applicability.ResultsA framework and a semi-automated process have been proposed that adapt pattern-based model transformation techniques for application to the methodology models used in SME. The transformation patterns have been implemented in the Medini-QVT model transformation tool, along with two supplementary method bases: one for mapping the situational factors of SME projects to requirements, and the other for mapping the requirements to method fragments. The method engineer can produce the methodology models by using the method bases and executing the transformation patterns via the tool.ConclusionThe validity of the proposed approach has been assessed based on special evaluation criteria, and also through application to a real-world project. Evaluation results indicate that the proposed approach addresses the deficiencies of existing approaches, and satisfies the practicality requirements of SME approaches.     

SimPL: A product-line modeling methodology for families of integrated control systems

ContextIntegrated control systems (ICSs) are heterogeneous systems where software and hardware components are integrated to control and monitor physical devices and processes. A family of ICSs share the same software code base, which is configured differently for each product to form a unique installation. Due to the complexity of ICSs and inadequate automation support, product configuration in this context is typically error-prone and costly.ObjectiveAs a first step to overcome these challenges, we propose a UML-based product-line modeling methodology that provides a foundation for semi-automated product configuration in the specific context of ICSs.MethodWe performed a comprehensive domain analysis to identify characteristics of ICS families, and their configuration challenges. Based on this, we formulated the characteristics of an adequate configuration solution, and derived from them a set of modeling requirements for a model-based solution to configuration. The SimPL methodology is proposed to fulfill these requirements.ResultsTo evaluate the ability of SimPL to fulfill the modeling requirements, we applied it to a large-scale industrial case study. Our experience with the case study shows that SimPL is adequate to provide a model of the product family that meets the modeling requirements. Further evaluation is still required to assess the applicability and scalability of SimPL in practice. Doing this requires conducting field studies with human subjects and is left for future work.ConclusionWe conclude that configuration in ICSs requires better automation support, and UML-based approaches to product family modeling can be tailored to provide the required foundation.     

Current state and potential of variability management practices in software-intensive SMEs: Results from a regional industrial survey

ContextMore and more, small and medium-sized enterprises (SMEs) are using software to augment the functionality of their products and offerings. Variability management of software is becoming an interesting topic for SMEs with expanding portfolios and increasingly complex product structures. While the use of software product lines to resolve high variability is well known in larger organizations, there is less known about the practices in SMEs.ObjectiveThis paper presents results from a survey of software developing SMEs. The purpose of the paper is to provide a snapshot of the current awareness and practices of variability modeling in organizations that are developing software with the constraints present in SMEs.MethodA survey with questions regarding the variability practices was distributed to software developing organizations in a region of Sweden that has many SMEs. The response rate was 13% and 25 responses are used in this analysis.ResultsWe find that, although there are SMEs that develop implicit software product lines and have relatively sophisticated variability structures for their solution space, the structures of the problem space and the product space have room for improvement.ConclusionsThe answers in the survey indicate that SMEs are in situations where they can benefit from more structured variability management, but the awareness need to be raised. Even though the problem space similarity is high, there is little reuse and traceability activities performed. The existence of SMEs with qualified variability management and product line practices indicates that small organizations are capable to apply such practices.     

Simulating evolution in model-based product line engineering

ContextNumerous approaches are available for modeling product lines and their variability. However, the long-term impacts of model-based development on maintenance effort and model complexity can hardly be investigated due to a lack of empirical data. Conducting empirical research in product line engineering is difficult as companies are typically reluctant to provide access to data from their product lines. Also, many benefits of product lines can be measured only in longitudinal studies, which are difficult to perform in most environments.ObjectiveIn this paper, we thus aim to explore the benefit of simulation to investigate the evolution of model-based product lines.MethodWe present a simulation approach for exploring the effects of product line evolution on model complexity and maintenance effort. Our simulation considers characteristics of product lines (e.g., size, dependencies in models) and we experiment with different evolution profiles (e.g., technical refactoring vs. placement of new products).ResultsWe apply the approach in a simulation experiment that uses data from real-world product lines from the domain of industrial automation systems to demonstrate its feasibility.ConclusionOur results demonstrate that simulation contributes to understanding the effects of maintenance and evolution in model-based product lines.     

Model-based incremental conformance checking to enable interactive product configuration

ContextModel-based product line engineering (PLE) is a paradigm that can enable automated product configuration of large-scale software systems, in which models are used as an abstract specification of commonalities and variabilities of products of a product line.ObjectiveIn the context of PLE, providing immediate feedback on the correctness of a manual configuration step to users has a practical impact on whether a configuration process with tool support can be successfully adopted in practice.MethodIn an existing work, a UML-based variability modeling methodology named as SimPL and an interactive configuration process was proposed. Based on the existing work, we propose an automated, incremental and efficient conformance checking approach to ensure that the manual configuration of a variation point conforms to a set of pre-defined conformance rules specified in the Object Constraint Language (OCL). The proposed approach, named as Zen-CC, has been implemented as an integrated part of our product configuration and derivation tool: Zen-Configurator.ResultsThe performance and scalability of Zen-CC have been evaluated with a real-world case study. Results show that Zen-CC significantly outperformed two baseline engines in terms of performance. Besides, the performance of Zen-CC remains stable during the configuration of all the 10 products of the product line and its efficiency also remains un-impacted even with the growing product complexity, which is not the case for both of the baseline engines.ConclusionThe results suggest that Zen-CC performs practically well and is much more scalable than the two baseline engines and is scalable for configuring products with a larger number of variation points.     

An industrial case study on variability handling in large enterprise software systems

ContextEnterprise software systems (e.g., enterprise resource planning software) are often deployed in different contexts (e.g., different organizations or different business units or branches of one organization). However, even though organizations, business units or branches have the same or similar business goals, they may differ in how they achieve these goals. Thus, many enterprise software systems are subject to variability and adapted depending on the context in which they are used.ObjectiveOur goal is to provide a snapshot of variability in large scale enterprise software systems. We aim at understanding the types of variability that occur in large industrial enterprise software systems. Furthermore, we aim at identifying how variability is handled in such systems.MethodWe performed an exploratory case study in two large software organizations, involving two large enterprise software systems. Data were collected through interviews and document analysis. Data were analyzed following a grounded theory approach.ResultsWe identified seven types of variability (e.g., functionality, infrastructure) and eight mechanisms to handle variability (e.g., add-ons, code switches).ConclusionsWe provide generic types for classifying variability in enterprise software systems, and reusable mechanisms for handling such variability. Some variability types and handling mechanisms for enterprise software systems found in the real world extend existing concepts and theories. Others confirm findings from previous research literature on variability in software in general and are therefore not specific to enterprise software systems. Our findings also offer a theoretical foundation for describing variability handling in practice. Future work needs to provide more evaluations of the theoretical foundations, and refine variability handling mechanisms into more detailed practices.     

Software process modeling languages: A systematic literature review

ContextOrganizations working in software development are aware that processes are very important assets as well as they are very conscious of the need to deploy well-defined processes with the goal of improving software product development and, particularly, quality. Software process modeling languages are an important support for describing and managing software processes in software-intensive organizations.ObjectiveThis paper seeks to identify what software process modeling languages have been defined in last decade, the relationships and dependencies among them and, starting from the current state, to define directions for future research.MethodA systematic literature review was developed. 1929 papers were retrieved by a manual search in 9 databases and 46 primary studies were finally included.ResultsSince 2000 more than 40 languages have been first reported, each of which with a concrete purpose. We show that different base technologies have been used to define software process modeling languages. We provide a scheme where each language is registered together with the year it was created, the base technology used to define it and whether it is considered a starting point for later languages. This scheme is used to illustrate the trend in software process modeling languages. Finally, we present directions for future research.ConclusionThis review presents the different software process modeling languages that have been developed in the last ten years, showing the relevant fact that model-based SPMLs (Software Process Modeling Languages) are being considered as a current trend. Each one of these languages has been designed with a particular motivation, to solve problems which had been detected. However, there are still several problems to face, which have become evident in this review. This let us provide researchers with some guidelines for future research on this topic.     

Comprehensibility of UML-based software product line specifications

Software Product Line Engineering (SPLE) deals with developing artifacts that capture the common and variable aspects of software product families. Domain models are one kind of such artifacts. Being developed in early stages, domain models need to specify commonality and variability and guide the reuse of the artifacts in particular software products. Although different modeling methods have been proposed to manage and support these activities, the assessment of these methods is still in an inceptive stage. In this work, we examined the comprehensibility of domain models specified in ADOM, a UML-based SPLE method. In particular, we conducted a controlled experiment in which 116 undergraduate students were required to answer comprehension questions regarding a domain model that was equipped with explicit reuse guidance and/or variability specification. We found that explicit specification of reuse guidance within the domain model helped understand the model, whereas explicit specification of variability increased comprehensibility only to a limited extent. Explicit specification of both reuse guidance and variability often provided intermediate results, namely, results that were better than specification of variability without reuse guidance, but worse than specification of reuse guidance without variability. All these results were perceived in different UML diagram types, namely, use case, class, and sequence diagrams and for different commonality-, variability-, and reuse-related aspects.     

Application of knowledge-based approaches in software architecture: A systematic mapping study

ContextKnowledge management technologies have been employed across software engineering activities for more than two decades. Knowledge-based approaches can be used to facilitate software architecting activities (e.g., architectural evaluation). However, there is no comprehensive understanding on how various knowledge-based approaches (e.g., knowledge reuse) are employed in software architecture.ObjectiveThis work aims to collect studies on the application of knowledge-based approaches in software architecture and make a classification and thematic analysis on these studies, in order to identify the gaps in the existing application of knowledge-based approaches to various architecting activities, and promising research directions.MethodA systematic mapping study is conducted for identifying and analyzing the application of knowledge-based approaches in software architecture, covering the papers from major databases, journals, conferences, and workshops, published between January 2000 and March 2011.ResultsFifty-five studies were selected and classified according to the architecting activities they contribute to and the knowledge-based approaches employed. Knowledge capture and representation (e.g., using an ontology to describe architectural elements and their relationships) is the most popular approach employed in architecting activities. Knowledge recovery (e.g., documenting past architectural design decisions) is an ignored approach that is seldom used in software architecture. Knowledge-based approaches are mostly used in architectural evaluation, while receive the least attention in architecture impact analysis and architectural implementation.ConclusionsThe study results show an increased interest in the application of knowledge-based approaches in software architecture in recent years. A number of knowledge-based approaches, including knowledge capture and representation, reuse, sharing, recovery, and reasoning, have been employed in a spectrum of architecting activities. Knowledge-based approaches have been applied to a wide range of application domains, among which “Embedded software” has received the most attention.     

Exploring principles of user-centered agile software development: A literature review

ContextIn the last decade, software development has been characterized by two major approaches: agile software development, which aims to achieve increased velocity and flexibility during the development process, and user-centered design, which places the goals and needs of the system’s end-users at the center of software development in order to deliver software with appropriate usability. Hybrid development models, referred to as user-centered agile software development (UCASD) in this article, propose to combine the merits of both approaches in order to design software that is both useful and usable.ObjectiveThis paper aims to capture the current state of the art in UCASD approaches and to derive generic principles from these approaches. More specifically, we investigate the following research question: Which principles constitute a user-centered agile software development approach?MethodWe conduct a systematic review of the literature on UCASD. Identified works are analyzed using a coding scheme that differentiates four levels of UCASD: the process, practices, people/social and technology dimensions. Through subsequent synthesis, we derive generic principles of UCASD.ResultsWe identified and analyzed 83 relevant publications. The analysis resulted in a comprehensive coding system and five principles for UCASD: (1) separate product discovery and product creation, (2) iterative and incremental design and development, (3) parallel interwoven creation tracks, (4) continuous stakeholder involvement, and (5) artifact-mediated communication.ConclusionOur paper contributes to the software development body of knowledge by (1) providing a broad overview of existing works in the area of UCASD, (2) deriving an analysis framework (in form a coding system) for works in this area, going beyond former classifications, and (3) identifying generic principles of UCASD and associating them with specific practices and processes.