Automated diagnosis of feature model configurations

Software product-lines (SPLs) are software platforms that can be readily reconfigured for different project requirements. A key part of an SPL is a model that captures the rules for reconfiguring the software. SPLs commonly use feature models to capture SPL configuration rules. Each SPL configuration is represented as a selection of features from the feature model. Invalid SPL configurations can be created due to feature conflicts introduced via staged or parallel configuration or changes to the constraints in a feature model. When invalid configurations are created, a method is needed to automate the diagnosis of the errors and repair the feature selections.This paper provides two contributions to research on automated configuration of SPLs. First, it shows how configurations and feature models can be transformed into constraint satisfaction problems to automatically diagnose errors and repair invalid feature selections. Second, it presents empirical results from diagnosing configuration errors in feature models ranging in size from 100 to 5,000 features. The results of our experiments show that our CSP-based diagnostic technique can scale up to models with thousands of features.     

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%.     

Managing the requirements flow from strategy to release in large-scale agile development: a case study at Ericsson

In a large organization, informal communication and simple backlogs are not sufficient for the management of requirements and development work. Many large organizations are struggling to successfully adopt agile methods, but there is still little scientific knowledge on requirements management in large-scale agile development organizations. We present an in-depth study of an Ericsson telecommunications node development organization which employs a large scale agile method to develop telecommunications system software. We describe how the requirements flow from strategy to release, and related benefits and problems. Data was collected by 43 interviews, which were analyzed qualitatively. The requirements management was done in three different processes, each of which had a different process model, purpose and planning horizon. The release project management process was plan-driven, feature development process was continuous and implementation management process was agile. The perceived benefits included reduced development lead time, increased flexibility, increased planning efficiency, increased developer motivation and improved communication effectiveness. The recognized problems included difficulties in balancing planning effort, overcommitment, insufficient understanding of the development team autonomy, defining the product owner role, balancing team specialization, organizing system-level work and growing technical debt. The study indicates that agile development methods can be successfully employed in organizations where the higher level planning processes are not agile. Combining agile methods with a flexible feature development process can bring many benefits, but large-scale software development seems to require specialist roles and significant coordination effort.     

Feature-Oriented Nonfunctional Requirement Analysis for Software Product Line

Domain analysis in software product line (SPL) development provides a basis for core assets design and implementation by a systematic and comprehensive commonality/variability analysis. In feature-oriented SPL methods, products of the domain analysis are domain feature models and corresponding feature decision models to facilitate application-oriented customization. As in requirement analysis for a single system, the domain analysis in the SPL development should consider both functional and nonfunctional domain requirements. However, the nonfunctional requirements (NFRs) are often neglected in the existing domain analysis methods. In this paper, we propose a context-based method of the NFR analysis for the SPL development. In the method, NFRs are materialized by connecting nonfunctional goals with real-world context, thus NFR elicitation and variability analysis can be performed by context analysis for the whole domain with the assistance of NFR templates and NFR graphs. After the variability analysis, our method integrates both functional and nonfunctional perspectives by incorporating the nonfunctional goals and operationalizations into an initial functional feature model. NFR-related constraints are also elicited and integrated. Finally, a decision model with both functional and nonfunctional perspectives is constructed to facilitate application-oriented feature model customization. A computer-aided grading system (CAGS) product line is employed to demonstrate the method throughout the paper. This work is supported by the National Natural Science Foundation of China under Grant Nos. 60703092 and 90818009, the National High Technology Research and Development 863 Program of China under Grant No. 2007AA01Z125.     

Adding semantic modules to improve goal-oriented analysis of data warehouses using I-star

The success rate of data warehouse (DW) development is improved by performing a requirements elicitation stage in which the users’ needs are modeled. Currently, among the different proposals for modeling requirements, there is a special focus on goal-oriented models, and in particular on the i* framework. In order to adapt this framework for DW development, we previously developed a UML profile for DWs. However, as the general i* framework, the proposal lacks modularity. This has a specially negative impact for DW development, since DW requirement models tend to include a huge number of elements with crossed relationships between them. In turn, the readability of the models is decreased, harming their utility and increasing the error rate and development time. In this paper, we propose an extension of our i* profile for DWs considering the modularization of goals. We provide a set of guidelines in order to correctly apply our proposal. Furthermore, we have performed an experiment in order to assess the validity our proposal. The benefits of our proposal are an increase in the modularity and scalability of the models which, in turn, increases the error correction capability, and makes complex models easier to understand by DW developers and non expert users.     

Semi-formal transformation of secure business processes into analysis class and use case models: An MDA approach

ContextModel-Driven Development (MDD) is an alternative approach for information systems development. The basic underlying concept of this approach is the definition of abstract models that can be transformed to obtain models near implementation. One fairly widespread proposal in this sphere is that of Model Driven Architecture (MDA). Business process models are abstract models which additionally contain key information about the tasks that are being carried out to achieve the company’s goals, and two notations currently exist for modelling business processes: the Unified Modelling Language (UML), through activity diagrams, and the Business Process Modelling Notation (BPMN).ObjectiveOur research is particularly focused on security requirements, in such a way that security is modelled along with the other aspects that are included in a business process. To this end, in earlier works we have defined a metamodel called secure business process (SBP), which may assist in the process of developing software as a source of highly valuable requirements (including very abstract security requirements), which are transformed into models with a lower abstraction level, such as analysis class diagrams and use case diagrams through the approach presented in this paper.MethodWe have defined all the transformation rules necessary to obtain analysis class diagrams and use case diagrams from SBP, and refined them through the characteristic iterative process of the action-research method.ResultsWe have obtained a set of rules and a checklist that make it possible to automatically obtain a set of UML analysis classes and use cases, starting from SBP models. Our approach has additionally been applied in a real environment in the area of the payment of electrical energy consumption.ConclusionsThe application of our proposal shows that our semi-automatic process can be used to obtain a set of useful artifacts for software development processes.     

Automating feature model refactoring: A Model transformation approach

Context: Feature model is an appropriate and indispensable tool for modeling similarities and differences among products of the Software Product Line (SPL). It not only exposes the validity of the products’ configurations in an SPL but also changes in the course of time to support new requirements of the SPL. Modifications made on the feature model in the course of time raise a number of issues. Useless enlargements of the feature model, the existence of dead features, and violated constraints in the feature model are some of the key problems that make its maintenance difficult.Objective: The initial approach to dealing with the above-mentioned problems and improving maintainability of the feature model is refactoring. Refactoring modifies software artifacts in a way that their externally visible behavior does not change.Method: We introduce a method for defining refactoring rules and executing them on the feature model. We use the ATL model transformation language to define the refactoring rules. Moreover, we provide an Alloy model to check the feature model and the safety of the refactorings that are performed on it.Results: In this research, we propose a safe framework for refactoring a feature model. This framework enables users to perform automatic and semi-automatic refactoring on the feature model.Conclusions: Automated tool support for refactoring is a key issue for adopting approaches such as utilizing feature models and integrating them into the software development process of companies. In this work, we define some of the important refactoring rules on the feature model and provide tools that enable users to add new rules using the ATL M2M language. Our framework assesses the correctness of the refactorings using the Alloy language.     

Model-based pairwise testing for feature interaction coverage in software product line engineering

Testing software product lines (SPLs) is very challenging due to a high degree of variability leading to an enormous number of possible products. The vast majority of today??s testing approaches for SPLs validate products individually using different kinds of reuse techniques for testing. Because of their reusability and adaptability capabilities, model-based approaches are suitable to describe variability and are therefore frequently used for implementation and testing purposes of SPLs. Due to the enormous number of possible products, individual product testing becomes more and more infeasible. Pairwise testing offers one possibility to test a subset of all possible products. However, according to the best of our knowledge, there is no contribution discussing and rating this approach in the SPL context. In this contribution, we provide a mapping between feature models describing the common and variable parts of an SPL and a reusable test model in the form of statecharts. Thereby, we interrelate feature model-based coverage criteria and test model-based coverage criteria such as control and data flow coverage and are therefore able to discuss the potentials and limitations of pairwise testing. We pay particular attention to test requirements for feature interactions constituting a major challenge in SPL engineering. We give a concise definition of feature dependencies and feature interactions from a testing point of view, and we discuss adequacy criteria for SPL coverage under pairwise feature interaction testing and give a generalization to the T-wise case. The concept and implementation of our approach are evaluated by means of a case study from the automotive domain.     

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.     

Evolving feature model configurations in software product lines

The increasing complexity and cost of software-intensive systems has led developers to seek ways of reusing software components across development projects. One approach to increasing software reusability is to develop a software product-line (SPL), which is a software architecture that can be reconfigured and reused across projects. Rather than developing software from scratch for a new project, a new configuration of the SPL is produced. It is hard, however, to find a configuration of an SPL that meets an arbitrary requirement set and does not violate any configuration constraints in the SPL.Existing research has focused on techniques that produce a configuration of an SPL in a single step. Budgetary constraints or other restrictions, however, may require multi-step configuration processes. For example, an aircraft manufacturer may want to produce a series of configurations of a plane over a span of years without exceeding a yearly budget to add features.This paper provides three contributions to the study of multi-step configuration for SPLs. First, we present a formal model of multi-step SPL configuration and map this model to constraint satisfaction problems (CSPs). Second, we show how solutions to these SPL configuration problems can be automatically derived with a constraint solver by mapping them to CSPs. Moreover, we show how feature model changes can be mapped to our approach in a multi-step scenario by using feature model drift. Third, we present empirical results demonstrating that our CSP-based reasoning technique can scale to SPL models with hundreds of features and multiple configuration steps.     

Consistency maintenance for evolving feature models

Software product line (SPL) techniques handle the construction of customized systems. One of the most common representations of the decisions a customer can make in SPLs is feature models (FMs). An FM represents the relationships among common and variable features in an SPL. Features are a representation of the characteristics in a system that are relevant to customers.FMs are subject to change since the set of features and their relationships can change along an SPL lifecycle. Due to this evolution, the consistency of FMs may be compromised. There exist some approaches to detect and explain inconsistencies in FMs, however this process can take a long time for large FMs.In this paper we present a complementary approach to dealing with inconsistencies in FM evolution scenarios that improves the performance for existing approaches reducing the impact of change to the smallest part of an FM that changes. To achieve our goal, we formalize FMs from an ontological perspective and define constraints that must be satisfied in FMs to be consistent. We define a set of primitive operations that modify FMs and which are responsible for the FM evolution, analyzing their impact on the FM consistency. We propose a set of predefined strategies to keep the consistency for error-prone operations.As a proof-of-concept we present the results of our experiments, where we check for the effectiveness and efficiency of our approach in FMs with thousands of features. Although our approach is limited by the kinds of consistency constraints and the primitive operations we define, the experiments present a significant improvement in performance results in those cases where they are applicable.     

Agile requirements engineering via paraconsistent reasoning

Innovative companies need an agile approach towards product and service requirements, to rapidly respond to and exploit changing conditions. The agile approach to requirements must nonetheless be systematic, especially with respect to accommodating legal and non-functional requirements. This paper examines how to support lightweight, agile requirements processes which can still be systematically modeled, analyzed and changed. We propose a framework, RE-KOMBINE, which is based on a propositional language for requirements modeling called Techne. We define operations on Techne models which tolerate the presence of inconsistencies. This paraconsistent reasoning is vital for supporting delayed commitment to particular design solutions. We evaluate these operations with an industry case study using two well-known formal analysis tools. Our evaluations show that the proposed framework scales to industry-sized requirements model, while still retaining (via propositional logic) the informality that is so useful during early requirements analysis.     

Flexible feature binding in software product lines

A software product line (SPL) is a family of programs that share assets from a common code base. The programs of an SPL can be distinguished in terms of features, which represent units of program functionality that satisfy stakeholders’ requirements. The features of an SPL can be bound either statically at program compile time or dynamically at run time. Both binding times are used in SPL development and have different advantages. For example, dynamic binding provides high flexibility whereas static binding supports fine-grained customizability without any impact on performance (e.g., for use on embedded systems). However, contemporary techniques for implementing SPLs force a programmer to choose the binding time already when designing an SPL and to mix different implementation techniques when multiple binding times are needed. We present an approach that integrates static and dynamic feature binding seamlessly. It allows a programmer to implement an SPL once and to decide per feature at deployment time whether it should be bound statically or dynamically. Dynamic binding usually introduces an overhead regarding resource consumption and performance. We reduce this overhead by statically merging features that are used together into dynamic binding units. A program can be configured at run time by composing binding units on demand. We use feature models to ensure that only valid feature combinations can be selected at compile and at run time. We provide a compiler and evaluate our approach on the basis of two non-trivial SPLs.     

Ontology-based automated support for goal–use case model analysis

Combining goal-oriented and use case modeling has been proven to be an effective method in requirements elicitation and elaboration. To ensure the quality of such modeled artifacts, a detailed model analysis needs to be performed. However, current requirements engineering approaches generally lack reliable support for automated analysis of consistency, correctness and completeness (3Cs problems) between and within goal models and use case models. In this paper, we present a goal–use case integration framework with tool support to automatically identify such 3Cs problems. Our new framework relies on the use of ontologies of domain knowledge and semantics and our goal–use case integration meta-model. Moreover, functional grammar is employed to enable the semiautomated transformation of natural language specifications into Manchester OWL Syntax for automated reasoning. The evaluation of our tool support shows that for representative example requirements, our approach achieves over 85 % soundness and completeness rates and detects more problems than the benchmark applications.     

Software product line scoping and requirements engineering in a small and medium-sized enterprise: An industrial case study

Software product line (SPL) engineering has been applied in several domains, especially in large-scale software development. Given the benefits experienced and reported, SPL engineering has increasingly garnered interest from small to medium-sized companies. It is possible to find a wide range of studies reporting on the challenges of running a SPL project in large companies. However, very little reports exist that consider the situation for small to medium-sized enterprises and these studies try develop universal truths for SPL without lessons learned from empirical evidence need to be contextualized. This study is a step towards bridging this gap in contextual evidence by characterizing the weaknesses discovered in the scoping (SC) and requirements (RE) disciplines of SPL. Moreover, in this study we conducted a case study in a small to medium sized enterprises (SMEs) to justify the use of agile methods when introducing the SPL SC and RE disciplines through the characterization of their bottlenecks. The results of the characterization indicated that ineffective communication and collaboration, long iteration cycles, and the absence of adaptability and flexibility can increase the effort and reduce motivation during project development. These issues can be mitigated by agile methods.     

Extracting conceptual models from user stories with Visual Narrator

Extracting conceptual models from natural language requirements can help identify dependencies, redundancies, and conflicts between requirements via a holistic and easy-to-understand view that is generated from lengthy textual specifications. Unfortunately, existing approaches never gained traction in practice, because they either require substantial human involvement or they deliver too low accuracy. In this paper, we propose an automated approach called Visual Narrator based on natural language processing that extracts conceptual models from user story requirements. We choose this notation because of its popularity among (agile) practitioners and its focus on the essential components of a requirement: Who? What? Why? Coupled with a careful selection and tuning of heuristics, we show how Visual Narrator enables generating conceptual models from user stories with high accuracy. Visual Narrator is part of the holistic Grimm method for user story collaboration that ranges from elicitation to the interactive visualization and analysis of requirements.     

Contract-based modeling and verification of timed safety requirements within SysML

In order to cope with the growing complexity of critical real-time embedded systems, systems engineering has adopted a component-based design technique driven by requirements. Yet, such an approach raises several issues since it does not explicitly prescribe how system requirements can be decomposed on components nor how components contribute to the satisfaction of requirements. The envisioned solution is to design, with respect to each requirement and for each involved component, an abstract specification, tractable at each design step, that models how the component is concerned by the satisfaction of the requirement and that can be further refined toward a correct implementation. In this paper, we consider such specifications in the form of contracts. A contract for a component consists in a pair (assumption, guarantee) where the assumption models an abstract behavior of the component’s environment and the guarantee models an abstract behavior of the component given that the environment behaves according to the assumption. Therefore, contracts are a valuable asset for the correct design of systems, but also for mapping and tracing requirements to components, for tracing the evolution of requirements during design and, most importantly, for compositional verification of requirements. The aim of this paper is to introduce contract-based reasoning for the design of critical real-time systems made of reactive components modeled with UML and/or SysML. We propose an extension of UML and SysML languages with a syntax and semantics for contracts and the refinement relations that they must satisfy. The semantics of components and contracts is formalized by a variant of timed input/output automata on top of which we build a formal contract-based theory. We prove that the contract-based theory is sound and can be applied for a relatively large class of SysML system models. Finally, we show on a case study extracted from the automated transfer vehicle (http://www.esa.int/ATV) that our contract-based theory allows to verify requirement satisfaction for previously intractable models.     

Reasoning with contextual requirements: Detecting inconsistency and conflicts

ContextThe environment in which the system operates, its context, is variable. The autonomous ability of a software to adapt to context has to be planned since the requirements analysis stage as a strong mutual influence between requirements and context does exist. On the one hand, context is a main factor to decide whether to activate a requirement, the applicable alternatives to meet an activated requirement as well as their qualities. On the other hand, the system actions to reach requirements could cause changes in the context.ObjectivesModelling the relationship between requirements and context is a complex task and developing error-free models is hard to achieve without an automated support. The main objective of this paper is to develop a set of automated analysis mechanisms to support the requirements engineers to detect and analyze modelling errors in contextual requirements models.MethodWe study the analysis of the contextual goal model which is a requirements model that weaves together the variability of both context and requirements. Goal models are used during the early stages of software development and, thus, our analysis detects errors early in the development process. We develop two analysis mechanisms to detect two kinds of modelling errors. The first mechanism concerns the detection of inconsistent specification of contexts in a goal model. The second concerns the detection of conflicting context changes that arise as a consequence of the actions performed by the system to meet different requirements simultaneously. We support our analysis with a CASE tool and provide a systematic process that guides the construction and analysis of contextual goal models. We illustrate and evaluate our framework via a case study on a smart-home system for supporting the life of people having dementia problems.ResultsThe evaluation showed a significant ability of our analysis mechanisms to detect errors which were not notable by requirements engineers. Moreover, the evaluation showed acceptable performance of these mechanisms when processing up to medium-sized contextual goal models. The modelling constructs which we proposed as an input to enable the analysis were found easy to understand and capture.ConclusionsOur developed analysis for the detection of inconsistency and conflicts in contextual goal models is an essential step for the entire system correctness. It avoids us developing unusable and unwanted functionalities and functionalities which lead to conflicts when they operate together. Further research to improve our analysis to scale with large-sized models and to consider other kinds of errors is still needed.