Software Product Line Development Research Articles

Comparing the intensity of variability changes in software product line evolution

The evolution of a Software Product Line (SPL) typically affects multiple kinds of artifacts. The intensity (frequency and amount) in which developers change variability information in them was unknown, until we introduced a fine-grained approach for the variability-centric extraction and analysis of changes to code, build, and variability model artifacts. Its application to the commits of the Linux kernel revealed that changes to variability information occur infrequently and only affect small parts of the analyzed artifacts. Further, we outlined how these results may improve certain analysis and verification tasks during SPL evolution. However, the sole analysis of a single SPL did not allow for generic conclusions.In this paper, we extend our previous work to a comparative evolution analysis of four SPLs. We provide a detailed analysis of the individual intensities of variability changes by applying our updated approach to each SPL. A comparison of these results confirms our findings of infrequent and small changes to variability information in our previous study. However, differences in the details of these changes exist, which we cannot explain solely by the characteristics of the SPLs or their development processes. We discuss their implications on supporting SPL evolution and on our previous optimization proposals.

On Autonomous Dynamic Software Ecosystems

Software ecosystems are considered the natural evolution of software product lines. A software ecosystem provides a (software) product within a particular business and organizational context that supports the exchange of activities and services within a domain. However, the increasing degree of autonomy demanded by software ecosystems is elevating the system response to end users, while the existing software ecosystem architectures are not well prepared to deal with the dynamicity of context changes and autonomous behavior needs. In order to provide a transition toward an increased level of autonomy, in this article, we introduce the notion of autonomous dynamic ecosystems as representative of those software ecosystems able to support dynamic, smart, and autonomous features demanded by modern software systems. In this work, we further investigate and provide evidence of four industrial examples that have fully embodied the principles of autonomous dynamic ecosystems, and we characterize the main features and technology requirements of this kind of new ecosystems.

An SPL Reference Model based on Domain Taxonomies & Standards

Building reusable software is always a challenge, even when well-established approaches are applied. Software Product Line (SPL) development is one these approaches, which allows domain modeling be a way of dealing with common and variable aspects of reality. However, domain engineering itself can be complex, many times depending on the domain scope and/or its associated functionality. In this paper, our proposal to SPL development is structured as a leveled reference model built upon standardized semantic resources. This model and its associated process are exemplified through several cases from the field, drawing influencing factors subjectively assessed. Our experiences show that systematically enriching domain engineering may improve SPL development in the practice.

Intensifying the search-based optimization of product line architectures with crossover operators.

The Product Line Architecture (PLA) is a crucial artifact for the development of Software Product Lines. However, PLA is a complex artifact to be designed due to its large size and the multiple conflicting properties that need to be considered to ensure its quality, requiring a great effort for the architect. PLA designing has been formulated as an optimization problem aiming at improving some architectural properties in order to maximize both the feature modularization and the relational cohesion, and to minimize the class coupling. This kind of problem was successfully solved by multi-objective evolutionary algorithm. Nevertheless, most of existing approaches optimize PLA designs without applying the crossover operator, one of the fundamental genetic operators. To overcome these limitations, this paper aims to intensify the search-based PLA design optimization by presenting three crossover operators. These operators were empirically evaluated in quantitative and qualitative studies using three well-studied PLA designs. The experiments were conducted with eight experimental configurations of NSGA-II in comparison with a baseline that uses only mutation operators. Empirical results showed that there are significant differences among the use of only mutation and mutation with crossover. Also, we observed that the crossover operators contributed to generate solutions with better feature modularization. Finally, we could see that the proposed operators complement each other, since the experiment that combines at least two of the proposed operators achieved better results.

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.

Managed Evolution of Automotive Software Product Line Architectures: A Systematic Literature Study

The rapidly growing number of software-based features in the automotive domain as well as the special requirements in this domain ask for dedicated engineering approaches, models, and processes. Nowadays, software development in the automotive sector is generally developed as product line development, in which major parts of the software are kept adaptable in order to enable reusability of the software in different vehicle variants. In addition, reuse also plays an important role in the development of new vehicle generations in order to reduce development costs. Today, a high number of methods and techniques exist to support the product line driven development of software in the automotive sector. However, these approaches generally consider only partial aspects of development. In this paper, we present an in-depth literature study based on a conceptual model of artifacts and activities for the managed evolution of automotive software product line architectures. We are interested in the coverage of the particular aspects of the conceptual model and, thus, the fields covered in current research and research gaps, respectively. Furthermore, we aim to identify the methods and techniques used to implement automotive software product lines in general, and their usage scope in particular. As a result, this in-depth review reveals that none of the studies represent a holistic approach for the managed evolution of automotive software product lines. In addition, approaches from agile software development are of growing interest in this field.

Evolution in Software Product Lines: Defining and Modelling for Management

Evolution in Software Product Lines: Defining and Modelling for Management by Amougou Ngoumou * , Marcel Fouda Ndjodo Department of Computer Science, Higher Teacher Training College, University of Yaounde I, Cameroon * Author to whom correspondence should be addressed. Journal of Engineering Research and Sciences, Volume 1, Issue 5, Page # 179-185, 2022; DOI: 10.55708/js0105019

A study on alternative container-based technologies for virtualization of components deployment in software product lines

The application containerization approach allows creating virtualization environments that could be used as a code. It allows running application in the isolated container that could be reproduced on any other hardware or cloud environment. One of the benefits of the containerization approach is the possibility to allocate necessary hardware resources like a RAM, CPU and storage. An approach to support agile development of software product lines (SPL) by using variability management techniques within the framework of the Scrum methodology has been proposed in the article. The main goal of the work is to analyze containers for virtualization of the runtime environment when deploying SPL. The information base for the proposed approach to managing the variability of deployment has been structured. The role of the approach in the general method of Scrum has been shown, and a conceptual diagram of the management process at the stage of application deployment has been proposed. The experimental analysis has been carried out and metrics for two types of containers, Docker and Vagrant, have been calculated. The following two metrics, namely, portability and productivity, for both containers have been analyzed. These metrics for the test component software solution have been calculated and executed in cloud environment with different configurations. The portability metric indicates how easily the application can be migrated to other platform basing on the time required to start container with the application. The second metric is the time necessary for the same operations in different container.

Visualizing the customization endeavor in product-based-evolving software product lines: a case of action design research

Software Product Lines (SPLs) aim at systematically reusing software assets, and deriving products (a.k.a., variants) out of those assets. However, it is not always possible to handle SPL evolution directly through these reusable assets. Time-to-market pressure, expedited bug fixes, or product specifics lead to the evolution to first happen at the product level, and to be later merged back into the SPL platform where the core assets reside. This is referred to as product-based evolution. In this scenario, deciding when and what should go into the next SPL release is far from trivial. Distinct questions arise. How much effort are developers spending on product customization? Which are the most customized core assets? To which extent is the core asset code being reused for a given product? We refer to this endeavor as Customization Analysis, i.e., understanding the functional increments in adjusting products from the last SPL platform release. The scale of the SPLs’ code-base calls for customization analysis to be conducted through Visual Analytics tools. This work addresses the design principles for such tools through a joint effort between academia and industry, specifically, Danfoss Drives, a company division in charge of the P400 SPL. Accordingly, we adopt an Action Design Research approach where answers are sought by interacting with the practitioners in the studied situations. We contribute by providing informed goals for customization analysis as well as an intervention in terms of a visual analytics tool. We conclude by discussing to what extent this experience can be generalized to product-based evolving SPL organizations other than Danfoss Drives.

A Non-Exclusive Multi-Class Convolutional Neural Network for the Classification of Functional Requirements in AUTOSAR Software Requirement Specification Text

Software Requirement Specification (SRS) describes a software system to be developed that captures the functional, non-functional, and technical aspects of the stakeholder’s requirements. Retrieval and extraction of software information from SRS are essential to the development of software product line (SPL). Albeit Natural Language Processing (NLP) techniques, such as information retrieval and standard machine learning, have been advocated in the recent past as a semi-automatic means of optimising requirements specifications, they have not been widely embraced. The complexity in the organization’s information makes requirement analysis intricately a challenging task. The interdependence of subsystems and within an organisation drives this complexity. A plain multi-class classification framework may not address this issue. Hence, this paper propounds an automated non-exclusive approach for classification of functional requirements from SRS, using a deep learning framework. Specifically, Word2Vec and FastText word embeddings are utilised for document representation for training a convolutional neural network (CNN). The study was carried out by the compilation of manually categorised relevant enterprise data (AUTomotive Open System ARchitecture (AUTOSAR)), which were also employed for model training. Over a convolutional neural network, the impact of data trained with Word2Vec and FastText word embeddings from SRS documentation were compared to pre-trained word embeddings models, available online.

Comparing the Intensity of Variability Changes in Software Product Line Evolution

Comparing the Intensity of Variability Changes in Software Product Line Evolution

Embedding Quality into Software Product Line Variability Artifacts

The success of any software product line development project is closely tied to its domain variability management. Whereas a lot of effort has been put into functional variability management by the SPL community, non-functional variability is considered implicit. The result has been dissatisfaction among clients due to resultant poor quality systems. This work presents an integrated requirement specification template for quality and functional requirements at software product line variation points. The implementation of this approach at the analytical description phase increases the visibility of quality requirements obliging developers to implement them. The approach proposes the use of decision tree classification techniques to support the weaving of functional quality attributes at respective variation points. This work, therefore, promotes software product line variability management objectives by proposing new functional quality artifacts during requirements specification phase. The approach is illustrated with an exemplar mobile phone family data storage requirements case study.

Reparation in Evolutionary Algorithms for Multi-objective Feature Selection in Large Software Product Lines

Software Product Lines Engineering is the area of software engineering that aims to systematise the modelling, creation and improvement of groups of interconnected software systems by formally expressing possible alternative products in the form of Feature Models. Deriving a software product/system from a feature model is called Feature Configuration. Engineers select the subset of features (software components) from a feature model that suits their needs, while respecting the underlying relationships/constraints of the system–which is challenging on its own. Since there exist several (and often antagonistic) perspectives on which the quality of software could be assessed, the problem is even more challenging as it becomes a multi-objective optimisation problem. Current multi-objective feature selection in software product line approaches (e.g., SATIBEA) combine the scalability of a genetic algorithm (IBEA) with a solution reparation approach based on a SAT solver or one of its derivatives. In this paper, we propose MILPIBEA, a novel hybrid algorithm which combines IBEA with the accuracy of a mixed-integer linear programming (MILP) reparation. We show that the MILP reparation modifies fewer features from the original infeasible solutions than the SAT reparation and in a shorter time. We also demonstrate that MILPIBEA outperforms SATIBEA on average on various multi-objective performance metrics, especially on the largest feature models. The other major challenge in software engineering in general and in software product lines, in particular, is evolution. While the change in software components is common in the software engineering industry, the particular case of multi-objective optimisation of evolving software product lines is not well-tackled yet. We show that MILPIBEA is not only able to better take advantage of the evolution than SATIBEA, but it is also the one that continues to improve the quality of the solutions when SATIBEA stagnates. Overall, IBEA performs better when combined with MILP instead of SAT reparation when optimising the multi-objective feature selection in large and evolving software product lines.

A family of standards for software and systems product lines

There is a drastic rise and evolution of Software and Systems Product Lines (SSPL) as a potential solution to deliver quality software products in a shorter time and with less effort. This has led to a plethora of diversified tools across the entire life cycle of SSPL, making it difficult for product line organizations to select the right set of tools for product line realization and tool vendors to develop interoperable tools. In this paper, we motivate the need for standardization of tools and methods for SSPL. The ISO/IEC JTC1/SC7 (Software and Systems Engineering) of the International Organization for Standardization (ISO) has proposed a set of interrelated standards in the area of SSPL to cater to the emerging demands of software and systems industry. We present the foundation of SSPL family of standards that are driven by market needs and discuss the core patterns and processes of SSPL. We then present an overview of ISO/IEC 26550, which is the reference model for SSPL family of standards and provide examples from current and ongoing standards. We highlight a few examples of industry adoption of SSPL and standards and emphasize the need for further research for standards in SSPL. We see this paper as a first step to bring standards knowledge into the academic world in the field of SSPL.

Embedding Quality into Software Product Line Variability Artifacts

The success of any software product line development project is closely tied to its domain variability management. Whereas a lot of effort has been put into functional variability management by the SPL community, non-functional variability is considered implicit. The result has been dissatisfaction among clients due to resultant poor quality systems. This work presents an integrated requirement specification template for quality and functional requirements at software product line variation points. The implementation of this approach at the analytical description phase increases the visibility of quality requirements obliging developers to implement them. The approach proposes the use of decision tree classification techniques to support the weaving of functional quality attributes at respective variation points. This work, therefore, promotes software product line variability management objectives by proposing new functional quality artifacts during requirements specification phase. The approach is illustrated with an exemplar mobile phone family data storage requirements case study.

Handling of expert knowledge in software product lines development with usage of repertory grids method

The development of software product lines (SPL) is a promising way to create competitive software for the modern IT - market. Because of perpetual changes in user needs and the appearance of new software and hardware components for SPL, maintaining a certain level of variability at all stages of their full life cycle (FLC) becomes an actual problem. One of the most important stages is requirements engineering. To support this process it is advisable to utilize the methods of expert knowledge elicitation and analysis. Based on the recognized multilevel approach to SPL engineering proposed by K. Pohl, the research goal is to develop an approach to correct specification of variability features at the initial stages of SPL FLC. The analysis of methods to extract and process the expert knowledge is carried out, their classification is presented, and the method of repertory grid (RG) is chosen for the further usage. It allows analyzing and structuring expert knowledge in a multidimensional information space and makes it possible to consider various contextual factors that affect relevant requirements for the target SPL. The essentials of the RG method are considered and its formal description is elaborated. The examples of its usage in designing ​ “Smart House” systems which allow analyzing the technical, social and economic aspects of user requirements for software and hardware variability at the conceptual design stage of these systems are considered. As the result, a possibility to automate a process of a corresponding FODA-model creation is shown. That provides variability support at the next FLC stages of such systems.

Supporting feature-oriented evolution in industrial automation product lines

In the domain of industrial automation companies nowadays need to serve a mass market while at the same time customers demand highly customized solutions. To tackle this problem, companies frequently define software product lines (SPLs), which allow to automatically derive and further customize individual solutions based on a common platform. SPLs rely on defining common and variable platform features together with mappings, which define how the features are realized in implementation artifacts. In concurrent engineering such a feature-oriented process is challenged by the evolution of features, the complexity of feature-to-artifact mappings, and the diversity of the implementation artifacts. To address these challenges this paper introduces an approach supporting feature-oriented development and evolution in industrial SPLs. We outline the key elements and operations of our approach, including an implementation in a development environment. We report results of evaluating our approach regarding functional correctness, usefulness, and scalability based on a case study of a Pick-and-Place Unit (PPU) and an industrial case system.

Evolution in dynamic software product lines

AbstractMany software systems today provide support for adaptation and reconfiguration at runtime, in response to changes in their environment. Such adaptive systems are designed to run continuously and may not be shut down for reconfiguration or maintenance tasks. The variability of such systems has to be explicitly managed, together with mechanisms that control their runtime adaptation and reconfiguration. Dynamic software product lines (DSPLs) can help to achieve this. However, dealing with evolution is particularly challenging in a DSPL, as changes made at runtime can easily lead to inconsistencies. This paper describes the challenges of evolving DSPLs using an example cyber‐physical system for home automation. We discuss the shortcomings of existing work and present a reference architecture to support DSPL evolution. To demonstrate its feasibility and flexibility, we implemented the proposed reference architecture for two different DSPLs: the aforementioned cyber‐physical system, which uses feature models to describe its variability, and a runtime monitoring infrastructure, which is based on decision models. To assess the industrial applicability of our approach, we also implemented the reference architecture for a real‐world DSPL, an automation software system for injection molding machines. Our results provide evidence on the flexibility, performance, and industrial applicability of our approach.

Automatic extraction of product line architecture and feature models from UML class diagram variants

Abstract Context Software Product Lines (SPLs) are families of related products developed for specific domains. SPLs commonly emerge from existing variants when their individual maintenance and/or evolution become complex. Even though there exists a vast research literature on SPL extraction, the majority of the approaches have only focused on source code, are partially automated, or do not reflect domain constraints. Such limitations can make more difficult the extraction, management, documentation and generation of some important SPL artifacts such as the product line architecture, a fact that can impact negatively the evolution and maintenance of SPLs. Objective To tackle these limitations, this work presents ModelVars2SPL (Model Variants to SPL Core Assets), an automated approach to aid the development of SPLs from existing system variants. Method The input for ModelVars2SPL is a set of Unified Modeling Language (UML) class diagrams and the list of features they implement. The approach extracts two main assets: (i) Feature Model (FM), which represents the combinations of features, and (ii) a Product Line Architecture (PLA), which represents a global structure of the variants. ModelVars2SPL is composed of four automated steps. We conducted a thorough evaluation of ModelVars2SPL to analyze the artefacts it generates and its performance. Results The results show that the FMs well-represent the features organization, providing useful information to define and manage commonalities and variabilities. The PLAs show a global structure of current variants, facilitating the understanding of existing implementations of all variants. Conclusions An advantage of ModelVars2SPL is to exploit the use of UML design models, that is, it is independent of the programming language, and supports the re-engineering process in the design level, allowing practitioners to have a broader view of the SPL.

Value-Oriented Requirements: Eliciting Domain Requirements from Social Network Services to Evolve Software Product Lines

Social network services allow a large population of end-users of software products to publicly share their concerns and experiences about software systems. From a software engineering perspective, such data can be collected and analyzed to help software development organizations to infer users’ emerging demands, receive their feedback, and plan the rapid evolution of software product lines. For the evolution of software product lines, organizations supplement emerging requirements in their products to meet user’s needs and also to retain their dominance in the market. Therefore, social network services, being a communication channel, have supported a number of software development activities such as requirements engineering. It has supported software development organizations to cope with numerous limitations of the traditional requirements engineering approaches by eliciting, prioritizing, and negotiating user requirements. However, these approaches do not consider eliciting requirements in terms of variability and commonality while identifying requirements. To address this issue, we have proposed a social network service-based requirement engineering process. It considers the attributes of users’ opinions to determine variability and commonality. In order to justify our proposed approach, a controlled experiment was conducted on a sample set of end-users on Facebook and Twitter. The experimental results show that the team using the proposed approach performed better in terms of efficiency and effectiveness than the team that used a traditional requirements engineering approach.