Product Line Engineering Research Articles

Development complexity of cyber-physical systems: theoretical and practical benefits from Pre-Integrated Architectures

Aim: The growing complexity of cyber-physical systems impacts resources and development time. Hence, numerous component-based design approaches have been developed to mitigate complexity and, consequently, the R&D effort. But is complexity even measurable? The aims of this paper are: to contribute to the Cyber-Physical Systems (CPS) and Product Line Engineering (PLE) fields of research; to understand and apply the tools estimating Cyber-Physical System complexity; to evaluate the benefits of Pre-Integrated Architectures (PIARCHs) from the point of view of Cyber-Physical System complexity. Methods: Based on prior studies, we found that complexity is measurable. We used a structural complexity metric to calculate the impact of PIARCHs by creating variants of a given system architecture. In a practical application project, we used PIARCHs on two types of use cases: generic ones, like localization and perception, and a highly specific one: Urban Automated Driving. Results: Based on the calculation established by complexity metrics, PIARCHs reduce complexity. This has been revealed in theoretical and practical approaches. Generic use cases like localization and perception of an automated vehicle have more benefits with PIARCHs than the complex Urban Automated Driving use case. This can be explained by the fact that the number of inputs and parameters is smaller, and after the initial investment, the field of applications is wider. Conclusion: Project complexity is measurable, and the impact of PIARCHs mitigating complexity can be assessed. Their impact varies according to the complexity of the use case and the width of the field of applications. A minimum of complexity is required to justify the initial investment. However, an excessive PIARCH complexity reduces the number of applications and the payback of the initial investment.

Security and Configurable Storage Systems in Industry 4.0 Environments: A Systematic Literature Study

An increasing amount of Industry 4.0 data storages is highly configurable. As each variant includes individual features and interactions, ensuring data security becomes increasingly challenging. However, we are missing an analysis of research on security and configurable storages in Industry 4.0, especially those based on product-line engineering. To address this gap, we conducted a literature study covering relevant state-of-the-art publications (2013–2022). Overall, security for configurable systems seems under-explored. We highlighted that security standards and concrete mitigations techniques are usually not considered. In addition, we are missing an analysis of configurable storage and software systems in concert to identify threats, risks, and vulnerabilities caused by variability.

A Reference Framework for Variability Management of Software Product Lines

Variability management (VM) in software product line engineering (SPLE) is introduced as an abstraction that enables the reuse and customization of assets. VM is a complex task involving the identification, representation, and instantiation of variability for specific products, as well as the evolution of variability itself. This work presents a comparison and contrast between existing VM approaches using “qualitative meta-synthesis” to determine the underlying perspectives, metaphors, and concepts of existing methods. A common frame of reference for the VM was proposed as the result of this analysis. Putting metaphors in the context of the dimensions in which variability occurs and identifying its key concepts provides a better understanding of its management and enables several analyses and evaluation opportunities. Finally, the proposed framework was evaluated using a qualitative study approach. The results of the evaluation phase suggest that the organizations in practice only focus on one dimension. The presented frame of reference will help the organization to cover this gap in practice.

Projectional Editing of Software Product Lines Using Multi-variant Model Editors

Model-driven software engineering (MDSE) as well as software product line engineering (SPLE) achieve productivity gains by raising the level of abstraction and fostering organized reuse. Consequently, the integrating discipline model-driven software product line engineering (MDSPLE) aims at combining the best of both worlds by creating multi-variant models which are (automatically) configured into single-variant models which are in turn adapted further (if required). Inherently complex multi-variant models call for urgently needed tools providing support for editing multi-variant models. In this paper, we present a framework for projectional multi-variant editors which make complexity manageable using a user-friendly representation. At all times, a domain engineer is aware of editing a multi-variant model which is necessary to assess the impact of changes on all model variants. Supporting a clear separation of product space (domain model) and variant space (variability annotations), our projectional multi-variant editors provide a novel approach to representing variability information which is displayed non-intrusively. Furthermore, the domain engineer may employ a projectional multi-variant editor to adapt the representation of the multi-variant domain model in a flexible way, according to the current focus of interest.

A DSPL and Reinforcement Learning Approach for Context-Aware IoT Systems Development

The internet of things is a paradigm of interconnected devices able to communicate and exchange information to achieve users' requirements. In spite of their expansion in the last years, IoT systems still face challenges that hinder gaining major advantages from them. One of these challenges is to automatically adapt the system to the user's context and preferences. As a proposition to deal with this problem, this paper presents a methodology to design and develop IoT systems that adapt their behavior to their context, which can be a user or environmental context. This methodology is based on dynamic software product line engineering and uses Markov process to design the adaptation plan of the system and a reinforcement learning algorithm to implement it.

Lifted structural invariant analysis of Petri net product lines

Petri nets are commonly used to represent concurrent systems. However, they lack support for modelling and analysing system families, like variants of controllers, different variations of a process model, or the possible configurations of a flexible assembly line.To facilitate modelling potentially large collections of similar systems, in this paper, we enrich Petri nets with variability mechanisms based on product line engineering. Moreover, we present methods for the efficient analysis of the place and transition invariants in all defined versions of a Petri net. Efficiency is achieved by analysing the system family as a whole, instead of analysing each possible net variant separately. For this purpose, we lift the notion of incidence matrix to the product line level, and rely on constraint solving techniques. We present tool support and evaluate the benefits of our techniques on synthetic and realistic examples, achieving in some cases speed-ups of two orders of magnitude with respect to analysing each net variant separately.

E-Business Software Product Line Methodology Based on SMEs Characteristics

The growth of Small and Medium Enterprises (SMEs) will certainly have a positive influence on economic development in a country. However, many SMEs struggle to survive, grow, and show limited productivity. It was recorded that there were around 63.9% of SMEs in Indonesia whose turnover had decreased by more than 30% during the COVID-19 pandemic. Among the factors that cause the low survival rate of SMEs, a factor that is considered critical is the lack of success in the use of e-business. The use of e-business by SMEs is not a one-size-fits-all solution, because SMEs have various characteristics. In this study, an E-Business Software Product Line Methodology based on SMEs characteristics was proposed using Software Product Line Engineering (SPLE) approach. In general, the proposed methodology was sufficient to describe the aspects needed in building a software development methodology. Aspects that had not been described were those related to software project management. The proposed methodology is useful for building an e-business application platform that can be customized based on SMEs characteristics.

Towards Erlang-based ABS Microservices Framework for Software Product Line Development

The current widely used software system can be categorised as a large or very large decentralised control system with various requirements and continuous interchangeable elements. This characteristic leads to a need to control the variability to manage such systems. Software Product Line Engineering (SPLE) is one of the approaches that can manage the variability by developing sets of products. However, there is a need for support tools for development with software product line engineering. One language that supports the SPLE process is Abstract Behavioral Specification (ABS). Some SPLE research has used ABS to create frameworks that support the SPLE process. ABS Microservices is one research that utilises ABS to create a web framework that supports the SPLE process. This framework uses ABS to generate Java-based applications. The research interest in the web application is driven by the fact that it is one of the software types widely used by organisations and serves as the primary support of their business. Microservices are highly interoperable, thus enabling researchers to integrate different technology from other research. However, there is a need for renewal to the ABS Microservices framework. There is a need for more variants of SPLE-enabled frameworks that use more programming language as a specific programming language has its strength and weakness. Deprecation of the Java backend of the ABS opens a new exploration of another web framework that uses other ABS backend languages. We present the ABS microservices web framework based on Erlang OTP. We choose Erlang because it promises more efficient resource usage and the Erlang backend is one of the ABS backends with the most available features. This research aims to create an entry point for ABS Microservices to support more language. This research shows that the Erlang variant of ABS Microservices has less resource usage than the Java variant. Hence, this promises more options to develop product lines using ABS Microservices.

UML Transformation to Java-based Software Product Lines

Software product line engineering (SPLE) is an emerging approach that enables variability management in software development. SPLE offers tremendous benefits, but lack of tool support becomes a barrier in the adoption of SPLE. Variability modules for Java (VMJ) is an implementation approach that is defined based on the variability modules (VM) concept to support SPLE. VMJ combines Java modules system and design patterns that are commonly used by software developers. VMJ is accompanied by a UML profile, called UML-VM profile, which extends UML notation to model variability in the UML diagram. UML-VM diagram is used to model the problem domain, and VMJ is used in the domain implementation. In this research, we design a model transformation from Unified Modeling Language (UML) diagram into VMJ. The transformation rules are defined based on the UML-VM profile and implemented in the Eclipse Acceleo model to text transformation. As a result, a UML diagram can be transformed automatically into Java-based software product lines. The transformation tool is evaluated using a case study by comparing the generated code and the actual implementation.

Practical Experience Applying Feature‐based Product Line Engineering in a DevOps Environment: Achieving the Best of Both Worlds

AbstractSystems and Software Product Line Engineering (PLE) is an engineering discipline to produce and maintain a family of similar products in an efficient manner. It has long been known that managing a product portfolio as a single entity, as opposed to a multitude of separate products, can bring substantial improvements in schedule, cost, and quality. DevOps is an engineering discipline, practiced within an infrastructure of test and deployment automation, that seeks to minimize the time that a change to a product is made, and the product is built, validated, deployed, and made available to the end users. Many organizations find themselves willing to employ both disciplines – that is, to employ DevOps for products in a product line. This paper shows how that can be done, relates a case where it was done, and reports on the substantial benefits that were realized.

A conceptual model for unifying variability in space and time: Rationale, validation, and illustrative applications

With the increasing demand for customized systems and rapidly evolving technology, software engineering faces many challenges. A particular challenge is the development and maintenance of systems that are highly variable both in space (concurrent variations of the system at one point in time) and time (sequential variations of the system, due to its evolution). Recent research aims to address this challenge by managing variability in space and time simultaneously. However, this research originates from two different areas, software product line engineering and software configuration management, resulting in non-uniform terminologies and a varying understanding of concepts. These problems hamper the communication and understanding of involved concepts, as well as the development of techniques that unify variability in space and time. To tackle these problems, we performed an iterative, expert-driven analysis of existing tools from both research areas to derive a conceptual model that integrates and unifies concepts of both dimensions of variability. In this article, we first explain the construction process and present the resulting conceptual model. We validate the model and discuss its coverage and granularity with respect to established concepts of variability in space and time. Furthermore, we perform a formal concept analysis to discuss the commonalities and differences among the tools we considered. Finally, we show illustrative applications to explain how the conceptual model can be used in practice to derive conforming tools. The conceptual model unifies concepts and relations used in software product line engineering and software configuration management, provides a unified terminology and common ground for researchers and developers for comparing their works, clarifies communication, and prevents redundant developments.

Reducing Redundant Test Executions in Software Product Line Testing—A Case Study

In the context of software product line (SPL) engineering, test cases can be reused for testing a family of products that share common parts of source code. An approach to test the products of a product family is to exhaustively execute each test case on all the products. However, such an approach would be very inefficient because the common parts of source code will be tested multiple times unnecessarily. To reduce unnecessary repetition of testing, we previously proposed a method to avoid equivalent test executions of a product line in the context of regression testing. However, it turns out that the same approach can be used in a broader context than just regression testing of product families. In this paper, we argue the generality of the method in the sense that it can be used for testing of the first version of a product family as well as regression testing of its subsequent versions. In addition, in this paper, in order to make the method practically usable for users, we propose a process for applying it to SPL testing. We demonstrate the generality of our method and the practical applicability of the proposed process for the method by conducting a case study.

Towards a component-based system model to improve the quality of highly configurable systems.

Due to ever-evolving software developments processes, companies are motivated to develop desired quality products quickly and effectively. Industries are now focusing on the delivery of configurable systems to provide several services to a wide range of customers by making different configurations in a single largest system. Nowadays, component-based systems are highly demanded due to their capability of reusability and restructuring of existing components to develop new systems. Moreover, product line engineering is the major branch of the component-based system for developing a series of systems. Software product line engineering (SPLE) provides the ability to design several software modifications according to customer needs in a cost-effective manner. Researchers are trying to tailor the software product line (SPL) process that integrates agile development technologies to overcome the issues faced during the execution of the SPL process such as delay in product delivery, restriction to requirements change, and exhaustive initial planning. The selection of suitable components, the need for documentation, and tracing back the user requirements in the agile-integrated product line (APL) models still need to improve. Furthermore, configurable systems demand the selected features to be the least dependent. In this paper, a hybrid APL model, quality enhanced application product line engineering (QeAPLE) is proposed that provides support for highly configurable systems (HCS) by evaluating the dependency of features before making the final selection. It also has a documentation and requirement traceability function to ensure that the product meets the desired quality. Two-fold assessments are undertaken to validate the suggested model, with the proposed model being deployed on an active project. After that, we evaluated the proposed model performance and effectiveness using after implementing it in a real-world environment and compared the results with an existing method using statistical analysis. The results of the experimental study proofs that the proposed model is practically and statistically significant as compared to the existing method in terms of effectiveness and participants’ performance. Hence, the statistical results of the comparative analysis show that the proposed model improved ease of understanding and adaptability, required effort, high-quality achievement, and version management are significant i.e., more the 50% as compared to the exiting method i.e., less than 50%. The proposed model offers to assist in the development of a highly configurable system that achieves the needed quality. Therefore, the proposed model manages the variation identification, versions control, components dependency for correct selection of components, and validation activities from domain engineering to application engineering.

Realizing self-adaptive systems via online reinforcement learning and feature-model-guided exploration

AbstractA self-adaptive system can automatically maintain its quality requirements in the presence of dynamic environment changes. Developing a self-adaptive system may be difficult due to design time uncertainty; e.g., anticipating all potential environment changes at design time is in most cases infeasible. To realize self-adaptive systems in the presence of design time uncertainty, online machine learning, i.e., machine learning at runtime, is increasingly used. In particular, online reinforcement learning is proposed, which learns suitable adaptation actions through interactions with the environment at runtime. To learn about its environment, online reinforcement learning has to select actions that were not selected before, which is known as exploration. How exploration happens impacts the performance of the learning process. We focus on two problems related to how adaptation actions are explored. First, existing solutions randomly explore adaptation actions and thus may exhibit slow learning if there are many possible adaptation actions. Second, they are unaware of system evolution, and thus may explore new adaptation actions introduced during evolution rather late. We propose novel exploration strategies that use feature models (from software product line engineering) to guide exploration in the presence of many adaptation actions and system evolution. Experimental results for two realistic self-adaptive systems indicate an average speed-up of the learning process of 33.7% in the presence of many adaptation actions, and of 50.6% in the presence of evolution.

A Case Study of Domain Engineering in Software Product Line Engineering

A Case Study of Domain Engineering in Software Product Line Engineering

Towards a Proactive Variability Modeling Process for Cyber-Physical Systems Supported by Modern Product Line Engineering

Towards a Proactive Variability Modeling Process for Cyber-Physical Systems Supported by Modern Product Line Engineering

A concrete product derivation in software product line engineering: a practical approach

A concrete product derivation in software product line engineering: a practical approach

A concrete product derivation in software product line engineering: a practical approach

A concrete product derivation in software product line engineering: a practical approach

A novel approach for Software Architecture Product Line Engineering

A large software system exists in different forms, as different variants targeting different business needs and users. This kind of systems is provided as a set of “independent” products and not as a “single-whole”. Developers use ad-hoc mechanisms to manage variability. We defend a vision of software development where we consider an SPL architecture starting from which the architecture of each variant can be derived before its implementation. Indeed, each derived variant can have its own life. In this paper, we propose a novel approach for Software Architecture Product Line (SAPL) Engineering. It consists of, i) a generic process for recovering an SAPL model which is a product line of “software architectures” from large-sized variants. ii) a forward-engineering process that uses the recovered SAPL to derive new customized software architecture variants. The approach is firstly experimented on thirteen Eclipse variants to create a new SAPL. Then, an intensive evaluation is conducted using an existing benchmark which is also based on Eclipse IDE. Our results showed that we can accurately reconstruct such an SAPL and derive effectively pertinent variants. Our study provides insights that recovering SAPL and then deriving software architectures offers good documentation to understand the software before changing it.

Development of Digital Libraries with Software Product Line Engineering

Digital Libraries have become popular nowadays since important libraries all over the world started distributing their collections online, properly classified, and, in many cases, with access to the digital version of the resource. These programs have been beneficial to the general population as well as research groups in fields such as language and literature. Nonetheless, since their creation is a time-consuming and costly process, small organizations are forced to rely on obsolete or poorly designed software. However, most of the features, including the data model, are shared by this type of system, with minor variations depending on the type of resources to be handled. This article presents a Software Product Line (SPL) for the semi-automatic generation of Digital Libraries (DL). Our SPL allows developers to specify which DL features are required, which will define the data model variationand the generated source code. The specification is then transformed into a fully functional DL application with the specified features that is ready for deployment. We present the feature model, the SPL implementation, and acase study on three sample projects that enabled us to evaluate the resulting software, with a focus on development effort savings.