Retrieving reusable components with variation points from software product lines

Reusing software through software product lines has been recognized as useful. To improve reuse efficiency, retrieving proper systems or subsystems from software product lines for reuse is an important issue. This paper proposes a technique to retrieve reusable software systems/subsystems from software product lines.     

A formal framework for software product lines

ContextA Software Product Line is a set of software systems that are built from a common set of features. These systems are developed in a prescribed way and they can be adapted to fit the needs of customers. Feature models specify the properties of the systems that are meaningful to customers. A semantics that models the feature level has the potential to support the automatic analysis of entire software product lines.ObjectiveThe objective of this paper is to define a formal framework for Software Product Lines. This framework needs to be general enough to provide a formal semantics for existing frameworks like FODA (Feature Oriented Domain Analysis), but also to be easily adaptable to new problems.MethodWe define an algebraic language, called SPLA, to describe Software Product Lines. We provide the semantics for the algebra in three different ways. The approach followed to give the semantics is inspired by the semantics of process algebras. First we define an operational semantics, next a denotational semantics, and finally an axiomatic semantics. We also have defined a representation of the algebra into propositional logic.ResultsWe prove that the three semantics are equivalent. We also show how FODA diagrams can be automatically translated into SPLA. Furthermore, we have developed our tool, called AT, that implements the formal framework presented in this paper. This tool uses a SAT-solver to check the satisfiability of an SPL.ConclusionThis paper defines a general formal framework for software product lines. We have defined three different semantics that are equivalent; this means that depending on the context we can choose the most convenient approach: operational, denotational or axiomatic. The framework is flexible enough because it is closely related to process algebras. Process algebras are a well-known paradigm for which many extensions have been defined.     

Heuristic and exact algorithms for product configuration in software product lines

Software product line (SPL) is a set of software applications that share a common set of features satisfying the specific needs of a particular market segment. SPL engineering is a paradigm to develop software applications that commonly use a feature model to capture and document common and variable features, and their relationships. A big challenge is to derive one product among all possible products in the SPL, which satisfies the business and customer requirements. This task is known as product configuration. Although product configuration has been extensively investigated in the literature, customer's preferences are frequently neglected. In this paper, we propose a novel approach to configure a product that considers both qualitative and quantitative feature properties. We model the product configuration task as a combinatorial optimization problem, and heuristic and exact algorithms are proposed. As far as we are concerned, this proposal is the first work in the literature that considers feature properties in both leaf and nonleaf features. Computational experiments showed that the best of our heuristics found optimal solutions for all instances where those are known. For the instances where optimal solutions are not known, our heuristic outperformed the best solution obtained by a one‐hour run of the exact algorithm by up to 67.89%.     

Toward automated feature model configuration with optimizing non-functional requirements

ContextA software product line is a family of software systems that share some common features but also have significant variabilities. A feature model is a variability modeling artifact, which represents differences among software products with respect to the variability relationships among their features. Having a feature model along with a reference model developed in the domain engineering lifecycle, a concrete product of the family is derived by binding the variation points in the feature model (called configuration process) and by instantiating the reference model.ObjectiveIn this work we address the feature model configuration problem and propose a framework to automatically select suitable features that satisfy both the functional and non-functional preferences and constraints of stakeholders. Additionally, interdependencies between various non-functional properties are taken into account in the framework.MethodThe proposed framework combines Analytical Hierarchy Process (AHP) and Fuzzy Cognitive Maps (FCM) to compute the non-functional properties weights based on stakeholders’ preferences and interdependencies between non-functional properties. Afterwards, Hierarchical Task Network (HTN) planning is applied to find the optimal feature model configuration.ResultOur approach improves state-of-art of feature model configuration by considering positive or negative impacts of the features on non-functional properties, the stakeholders’ preferences, and non-functional interdependencies. The approach presented in this paper extends earlier work presented in [1] from several distinct perspectives including mechanisms handling interdependencies between non-functional properties, proposing a novel tooling architecture, and offering visualization and interaction techniques for representing functional and non-functional aspects of feature models.Conclusionour experiments show the scalability of our configuration approach when considering both functional and non-functional requirements of stakeholders.     

Managing requirements specifications for product lines - An approach and industry case study

Software product line development has emerged as a leading approach for software reuse. This paper describes an approach to manage natural-language requirements specifications in a software product line context. Variability in such product line specifications is modeled and managed using a feature model. The proposed approach has been introduced in the Swedish defense industry. We present a multiple-case study covering two different product lines with in total eight product instances. These were compared to experiences from previous projects in the organization employing clone-and-own reuse. We conclude that the proposed product line approach performs better than clone-and-own reuse of requirements specifications in this particular industrial context.     

Multiresolution model based extraction of product feature lines in reverse engineering

In this paper, multiresolution models are employed in the context of reverse engineering for feature line extraction. Starting with a proper triangulation of the cloud point data as a priori, our feature line extraction algorithm has three steps: (1) establishing a Gauss normal sphere and creating multiresolution models for the Gauss sphere based on different levels of subdivisions for the sphere regions; (2) mapping the unit normal vectors of triangular faces in the multiresolution Gauss sphere and merging those connected triangular faces whose unit normal vectors fallen on the same Gauss sphere region with a given resolution to form super-faces (the collection of triangular facets with similar normal); and (3) extracting the boundaries from the super-faces and generating the feature lines from the extracted boundaries. We then use these feature lines as a base for tracing boundary curves for B-spline surface construction. Since feature lines maintain the characteristics of the original product models, in this way, we have a good chance to reconstruct B-spline surfaces with high quality. Examples are given in the paper to show the feature line extraction, the influence of the feature lines extracted under different resolutions, and the final reconstructed B-spline surfaces based on these feature lines.     

Key activities for product derivation in software product lines

More and more organizations adopt software product lines to leverage extensive reuse and deliver a multitude of benefits such as increased quality and productivity and a decrease in cost and time-to-market of their software development. When compared to the vast amount of research on developing product lines, relatively little work has been dedicated to the actual use of product lines to derive individual products, i.e., the process of product derivation. Existing approaches to product derivation have been developed independently for different aims and purposes. While the definition of a general approach applicable to every domain may not be possible, it would be interesting for researchers and practitioners to know which activities are common in existing approaches, i.e., what are the key activities in product derivation. In this paper we report on how we compared two product derivation approaches developed by the authors in two different, independent research projects. Both approaches independently sought to identify product derivation activities, one through a process reference model and the other through a tool-supported derivation approach. Both approaches have been developed and validated in research industry collaborations with different companies. Through the comparison of the approaches we identify key product derivation activities. We illustrate the activities’ importance with examples from industry collaborations. To further validate the activities, we analyze three existing product derivation approaches for their support for these activities. The validation provides evidence that the identified activities are relevant to product derivation and we thus conclude that they should be considered (e.g., as a checklist) when developing or evaluating a product derivation approach.     

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.     

A systematic mapping study of software product lines testing

Context

In software development, Testing is an important mechanism both to identify defects and assure that completed products work as specified. This is a common practice in single-system development, and continues to hold in Software Product Lines (SPL). Even though extensive research has been done in the SPL Testing field, it is necessary to assess the current state of research and practice, in order to provide practitioners with evidence that enable fostering its further development.

Objective

This paper focuses on Testing in SPL and has the following goals: investigate state-of-the-art testing practices, synthesize available evidence, and identify gaps between required techniques and existing approaches, available in the literature.

Method

A systematic mapping study was conducted with a set of nine research questions, in which 120 studies, dated from 1993 to 2009, were evaluated.

Results

Although several aspects regarding testing have been covered by single-system development approaches, many cannot be directly applied in the SPL context due to specific issues. In addition, particular aspects regarding SPL are not covered by the existing SPL approaches, and when the aspects are covered, the literature just gives brief overviews. This scenario indicates that additional investigation, empirical and practical, should be performed.

Conclusion

The results can help to understand the needs in SPL Testing, by identifying points that still require additional investigation, since important aspects regarding particular points of software product lines have not been addressed yet.     

Improving the management of product lines by performing domain knowledge extraction and cross product line analysis

ContextIncrease in market competition is one of the main reasons for developing and maintaining families of systems, termed Product Lines (PLs). Managing those PLs is challenging, let alone the management of several related PLs. Currently, those PLs are managed separately or their relations are analyzed assuming explicit specification of dependencies or use of an underlying terminology. Such assumptions may not hold when developing the PLs in different departments or companies applying various engineering processes.ObjectiveIn this work we call for utilizing the knowledge gained from developing and maintaining different PLs in the same domain in order to recommend on improvements to the management of PLs.MethodThe suggested approach conducts domain knowledge extraction and cross PL analysis on feature diagrams – the main aid for modeling PL variability. The domain knowledge is extracted by applying similarity metrics, clustering, and mining techniques. Based on the created domain models, the approach performs cross PL analysis that examines relations in the domain models and generates improvement recommendations to existing PLs and overall management recommendations (e.g., merging or splitting PLs).ResultsThe approach outcomes were evaluated by humans in a domain of mobile phones. The evaluation results may provide evidence that the outcomes of the approach in general and its recommendations in particular meet human perception of the given domain.ConclusionWe conclude that through domain knowledge extraction and cross PL analysis the suggested approach may generate recommendations useful to the management of individual PLs, as well as to the overall management of different PLs in the same domain.     

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 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.     

Analyzing evolution of variability in a software product line: From contexts and requirements to features

Context

In the long run, features of a software product line (SPL) evolve with respect to changes in stakeholder requirements and system contexts. Neither domain engineering nor requirements engineering handles such co-evolution of requirements and contexts explicitly, making it especially hard to reason about the impact of co-changes in complex scenarios.

Objective

In this paper, we propose a problem-oriented and value-based analysis method for variability evolution analysis. The method takes into account both kinds of changes (requirements and contexts) during the life of an evolving software product line.

Method

The proposed method extends the core requirements engineering ontology with the notions to represent variability-intensive problem decomposition and evolution. On the basis of problemorientation, the analysis method identifies candidate changes, detects influenced features, and evaluates their contributions to the value of the SPL.

Results and Conclusion

The process of applying the analysis method is illustrated using a concrete case study of an evolving enterprise software system, which has confirmed that tracing back to requirements and contextual changes is an effective way to understand the evolution of variability in the software product line.     

PAxSPL: A feature retrieval process for software product line reengineering

Software product lines (SPLs) are a well-known solution to systematically create reusable software products. Among the approaches to create an SPL, the extractive approach is usually used when the organization already has a set of similar systems. These systems are analyzed to extract, categorize, and group their common and variant features throughout the SPL reengineering process. As there are different scenario variables, such as available artifacts and team experience, the activities and techniques used to perform these tasks may change. This may increase the effort and decrease the quality of retrieved features when users with low experience in SPL reengineering perform such tasks. However, there is a lack of a process supporting these tasks considering different scenarios. Therefore, we specify the P repare, A ssemble, and E x ecute Process for SPL Reengineering (PAxSPL), a process that provides support to prepare, assemble, and execute feature retrieval throughout the analysis of documentation and team experience. To initially evaluate PAxSPL, we conducted and reported an exploratory case study in a real development environment. The results indicated that our proposal helps in the assembly of a feature retrieval process according to user needs. Results were important to identify points for improvement in PAxSPL. We also could use the information gathered to improve the guidelines and provide this information to be used as basis of comparison for future users.     

Process fusion: An industrial case study on agile software product line engineering

This paper presents a case study of a software product company that has successfully integrated practices from software product line engineering and agile software development. We show how practices from the two fields support the company’s strategic and tactical ambitions, respectively. We also discuss how the company integrates strategic, tactical and operational processes to optimize collaboration and consequently improve its ability to meet market needs, opportunities and challenges. The findings from this study are relevant to software product companies seeking ways to balance agility and product management. The findings also contribute to research on industrializing software engineering.     

Managing requirements inter-dependency for software product line derivation

Software Product Line Engineering (SPLE) can reduce software development costs, reduce time to market and improve product quality. A software product line is a set of software products sharing a set of common features but containing variation points. Successful SPLE requires making selection decisions at variation points effectively and efficiently. A significant challenge is how to identify, represent and manage the inter-dependency of selection decisions for requirements. We developed the concept of a meta-model for requirement decision models to bring formalism and consistency to the structure and to model inter-dependencies between requirement selection decisions. Here we present a meta-model for requirement selection decisions that includes inter-dependencies and we use a mobile phone worked example to illustrate our approach. To support our method, we developed two separate tools, V-Define (for domain decision model construction) and V-Resolve (for new product derivation). Finally the results of a metal processing product line case study using the tools are described.

Kumbang: A domain ontology for modelling variability in software product families

Variability is the ability of a system to be efficiently extended, changed, customised or configured for use in a particular context. There is an ever-growing demand for variability of software. Software product families are an important means for implementing software variability. We present a domain ontology called Kumbang for modelling the variability in software product families. Kumbang synthesises previous approaches to modelling variability in software product families. In addition, it incorporates modelling constructs developed in the product configuration domain for modelling the variability in non-software products. The modelling concepts include components and features with compositional structure and attributes, the interfaces of components and connections between them, and constraints. The semantics of Kumbang is rigorously described using natural language and a UML profile. We provide preliminary proof of concept for Kumbang: the domain ontology has been provided with a formal semantics by implementing a translation into a general-purpose knowledge representation language with formal semantics and inference support. A prototype tool for resolving variability has been implemented.     

Evolution support mechanisms for software product line process

Software product family process evolution needs specific support for incremental change. Product line process evolution involves in addition to identifying new requirements the building of a meta-process describing the migration from the old process to the new one. This paper presents basic mechanisms to support software product line process evolution. These mechanisms share four strategies - change identification, change impact, change propagation, and change validation. It also examines three kinds of evolution processes - architecture, product line, and product. In addition, change management mechanisms are identified. Specifically we propose support mechanisms for static local entity evolution and complex entity evolution including transient evolution process. An evolution model prototype based on dependency relationships structure of the various product line artifacts is developed.