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.     

An intelligent assistant for requirements validation

The process of determining user requirements for software systems is often plagued with uncertainty, ambiguity, and inconsistency. Rapid prototyping offers an iterative approach to requirements engineering that can be used to alleviate some of the problems with communication and understanding. Since the systems development process is characterized by changing requirements and assumptions, involving multiple stakeholders with often differing viewpoints, it is beneficial to capture the justifications for the decisions in the development process in a structured manner. Thisdesign rationale captured during requirements engineering can be used in conjunction with the rapid prototyping process to support various stakeholders involved in systems development. CAPS (the Computer Aided Prototyping System) has been built to help software engineers rapidly construct prototypes of proposed software systems. REMAP (Representation and MAintenance of Process knowledge) provides a conceptual model and mechanisms to represent and reason with (design) rationale knowledge. In this paper, we describe how in the context of evolving requirements, the CAPS system augmented with REMAP helps firm up software requirements through iterative negotiations via examination of executable prototypes and reasoning with design rationale knowledge.     

Past and future of software architectural decisions – A systematic mapping study

ContextThe software architecture of a system is the result of a set of architectural decisions. The topic of architectural decisions in software engineering has received significant attention in recent years. However, no systematic overview exists on the state of research on architectural decisions.ObjectiveThe goal of this study is to provide a systematic overview of the state of research on architectural decisions. Such an overview helps researchers reflect on previous research and plan future research. Furthermore, such an overview helps practitioners understand the state of research, and how research results can help practitioners in their architectural decision-making.MethodWe conducted a systematic mapping study, covering studies published between January 2002 and January 2012. We defined six research questions. We queried six reference databases and obtained an initial result set of 28,895 papers. We followed a search and filtering process that resulted in 144 relevant papers.ResultsAfter classifying the 144 relevant papers for each research question, we found that current research focuses on documenting architectural decisions. We found that only several studies describe architectural decisions from the industry. We identified potential future research topics: domain-specific architectural decisions (such as mobile), achieving specific quality attributes (such as reliability or scalability), uncertainty in decision-making, and group architectural decisions. Regarding empirical evaluations of the papers, around half of the papers use systematic empirical evaluation approaches (such as surveys, or case studies). Still, few papers on architectural decisions use experiments.ConclusionOur study confirms the increasing interest in the topic of architectural decisions. This study helps the community reflect on the past ten years of research on architectural decisions. Researchers are offered a number of promising future research directions, while practitioners learn what existing papers offer.     

Extending enterprise architecture modeling languages for domain specificity and collaboration: application to telecommunication service design

The competitive market forces organizations to be agile and flexible so as to react robustly to complex events. Modeling helps managing this complexity. However, in order to model an enterprise, many stakeholders, with different expertise, must work together and take decisions. These decisions and their rationale are not always captured explicitly, in a standard, formal manner. The main problem is to persuade stakeholders to capture them. This article synthesizes an approach for capturing and using the rationale behind enterprise modeling decisions. The approach is implemented through a domain-specific modeling language, defined as an extension of a standard enterprise architecture modeling language. It promotes coordination, enables presenting different stakeholders’ points of view, facilities participation and collaboration in modeling activities—activities focused here on enterprise architecture viewpoints. To present its benefits, such as rapid prototyping, the approach is applied to large organizations in the context of telecommunication service design. It is exemplified on modeling and capturing decisions on a conference service.     

Rationale-Based Use Case Specification

The requirements specification – as outcome of the requirements engineering process – falls short of capturing other useful information generated during this process, such as the justification for selected requirements, trade-offs negotiated by stakeholders and alternative requirements that were discarded. In the context of evolving systems and distributed development, this information is essential. Rationale methods focus on capturing and structuring this missing information. In this paper, we propose an integrated process with dedicated guidance for capturing requirements and their rationale, discuss its tool support and describe the experiences we made during several case studies with students. Although the idea of integrating rationale methods with requirements engineering is not new, few research projects so far have focused on smooth integration, dedicated tool support and detailed guidance for such methods.     

Participatory floodplain management in the Red River Basin, Canada

Floodplain management is a subject in which everyone in the floodplain is a stakeholder. Real participation only takes place when stakeholders are part of the decision-making process. This can occur directly when local communities come together to make floodplain management choices or if democratically elected or otherwise accountable agencies or groups can represent stakeholders. Real participation is more than consultation and requires that stakeholders at all levels of the social structure have an impact on decisions at different levels of floodplain management. A participatory approach is the only means for achieving long-lasting consensus and common agreement. However, for this to occur, stakeholders and officials from water management agencies have to recognize that the sustainability of floodplain management decisions is a common problem and that all parties are going to have to sacrifice some desires for the common good. There is common responsibility for making participation possible. This involves (a) the creation of mechanisms for stakeholder consultation at various scales (from local, over watershed to national) and (b) the creation of participatory capacity, particularly amongst marginalized social groups. This may include awareness raising, confidence building and education, as well as the provision of the economic resources needed to facilitate participation and the establishment of good and transparent sources of information.

This work focuses on the methodology for stakeholder participation in floodplain management. Floodplain management problems are characterized by multiple objectives and large number of stakeholders. The solution methodologies adapted for multi-criteria multi participant decision problems are generally based on aggregation of decisions obtained for individual decision makers. This approach seems somewhat inadequate when the number of stakeholders is very large. We have developed a methodology to include the views of multiple stakeholders using fuzzy set theory and fuzzy logic. Three possible different response types: scale (crisp), linguistic (fuzzy), and conditional (fuzzy) are analyzed to obtain the resultant input by using Fuzzy Expected Value. Fuzzy Expected Value input is used with the multi-criteria decision-making tool named Fuzzy Compromise Programming.

The methodology has been applied to floodplain management in the Red River Basin, Canada that faces periodical flooding. We have demonstrated that the empowerment of stakeholders can improve the floodplain management process and provide decisions acceptable to a wider group of stakeholders.     

Decision-making in management information systems research: the utility of policy capturing methodology

Abstract

Although decision-making represents a fundamental issue in management information systems (MIS), obtaining accurate assessments of the factors affecting employees' decisions may be difficult using traditional methods such as ratings and rankings. Policy capturing, a little-used method in MIS, represents a potentially important alternative to more traditional methods. After demonstrating that policy capturing has been underutilized in MIS, the paper illustrates the use of policy capturing in two decision-making contexts—computer training and software selection. These two studies contrast policy capturing results with more traditional methods, and draw implications for research.     

Uncertain Fuzzy Reasoning: A Case Study in Modelling Expert Decision Making

This paper presents a case study in which the introduction of vagueness or uncertainty into the membership functions of a fuzzy system was investigated in order to model the variation exhibited by experts in a medical decision-making context. A conventional (type-1) fuzzy expert system had previously been developed to assess the health of infants immediately after birth by analysis of the biochemical status of blood taken from infants' umbilical cords. Variation in decision making was introduced into the fuzzy expert system by means of membership functions which altered in small, predetermined manners over time. Three types of variation in membership functions were investigated: i) variation in the centre points, ii) variation in the widths, and iii) the addition of "white noise". Different levels (amounts) of uniformly distributed random variation were investigated for each of these types. Monte Carlo simulations were carried out to propagate the variation through the inferencing process in order to determine distributions of the conclusions reached. Interval valued type-2 fuzzy systems were also implemented to investigate the boundaries of variability in decisions. The results obtained were compared to the experts' decisions in order to determine which type and size of membership function variability best matched the experts' variability. The novel reasoning technique introduced in this study is termed nonstationary fuzzy reasoning     

Bridging the gap between software architecture rationale formalisms and actual architecture documents: An ontology-driven approach

Documenting software architecture rationale is essential to reuse and evaluate architectures, and several modeling and documentation guidelines have been proposed in the literature. However, in practice creating and updating these documents rarely is a primary activity in most software projects, and rationale remains hidden in casual and semi-structured records, such as e-mails, meeting notes, wikis, and specialized documents. This paper describes the TREx (Toeska Rationale Extraction) approach to recover, represent and explore rationale information from text documents, combining: (1) pattern-based information extraction to recover rationale; (2) ontology-based representation of rationale and architectural concepts; and (3) facet-based interactive exploration of rationale. Initial results from TREx’s application suggest that some kinds of architecture rationale can be semi-automatically extracted from a project’s unstructured text documents, namely decisions, alternatives and requirements. The approach and some tools are illustrated with a case study of rationale recovery for a financial securities settlement system.     

Learning About Ourselves: A Review of The Mathematics Teacher in the Digital Era

ABSTRACT

Mathematics Education in the Digital Era is a title that implies the ubiquity of digital technology in our everyday lives. In fact, it can be argued that digital technology is already ubiquitous for many stakeholders in mathematics education. Volume 2 of this series is titled The Mathematics Teacher in the Digital Era, which implies an exploration of the mathematics teacher as individual agent or actor in the experience of teaching and learning mathematics. What is exciting is the book editors' potentially unintended insights into teachers' affective sense, their beliefs, and their subsequent decisions for future pedagogical effort.     

架构设计决策管理工具的研究与设计

目前的架构设计决策隐含于最终架构制品中,导致了涉众交流困难、演化代价高、难以复用等问题。针对上述问题,通过分析架构设计决策的属性及决策制定过程,提出一种描述设计决策与其他外部元素之间关系的元模型,在此基础上设计一个结合编码化和人际化的管理策略的架构设计决策管理工具,实现对设计决策的显式编档、管理和复用。     

A systematic literature review of software requirements prioritization research

ContextDuring requirements engineering, prioritization is performed to grade or rank requirements in their order of importance and subsequent implementation releases. It is a major step taken in making crucial decisions so as to increase the economic value of a system.ObjectiveThe purpose of this study is to identify and analyze existing prioritization techniques in the context of the formulated research questions.MethodSearch terms with relevant keywords were used to identify primary studies that relate requirements prioritization classified under journal articles, conference papers, workshops, symposiums, book chapters and IEEE bulletins.Results73 Primary studies were selected from the search processes. Out of these studies; 13 were journal articles, 35 were conference papers and 8 were workshop papers. Furthermore, contributions from symposiums as well as IEEE bulletins were 2 each while the total number of book chapters amounted to 13.ConclusionPrioritization has been significantly discussed in the requirements engineering domain. However, it was generally discovered that, existing prioritization techniques suffer from a number of limitations which includes: lack of scalability, methods of dealing with rank updates during requirements evolution, coordination among stakeholders and requirements dependency issues. Also, the applicability of existing techniques in complex and real setting has not been reported yet.     

Network Management: Current Trends and Future Perspectives

This article analyzes the frameworks employed by existing network management solutions and points out their shortcomings. It also examines the current trends as observed in various commercial solutions in the network management domain. Finally, the paper presents some future perspectives on the concepts/technologies which could be utilized to build the next generation of network management solutions. Ankur Gupta is an Assistant Professor in the Department of Computer Science and Engineering at the Model Institute of Engineering and Technology, Jammu, India. His research interests include P2P networks/computing, network management, software engineering and higher technical education.     

Capturing and reusing knowledge in engineering change management: A case of automobile development

The development of complex products, such as automobiles, involves engineering changes that frequently require redesigning or altering the products. Although it has been found that efficient management of knowledge and collaboration in engineering changes is crucial for the success of new product development, extant systems for engineering changes focus mainly on storing documents related to the engineering changes or simply automating the approval processes, while the knowledge that is generated from collaboration and decision-making processes may not be captured and managed easily. This consequently limits the use of the systems by the participants in engineering change processes. This paper describes a model for knowledge management and collaboration in engineering change processes, and based on the model, builds a prototype system that demonstrates the model’s strengths. We studied a major Korean automobile company to analyze the automobile industry’s unique requirements regarding engineering changes. We also developed domain ontologies from the case to facilitate knowledge sharing in the design process. For achieving efficient retrieval and reuse of past engineering changes, we used a case-based reasoning (CBR) with a concept-based similarity measure.

Model-based incremental conformance checking to enable interactive product configuration

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

Have a look around: the effect of physical environments on risk behaviour in work-related versus non-work related decision-making tasks

Abstract

Due to ubiquitous computing, knowledge workers do not only work in typical work-associated environments (e.g. the office) but also wherever it best suits their schedule or preferences (e.g. the park). In two experiments using laboratory and field methods, we compared decision making in work and non-work environments. We hypothesised that participants make riskier work-related decisions when in work-associated environments and riskier non-work-related decisions in non-work-associated environments. Therefore, if environment (work vs. non-work) and decision-making task (work-related vs. non-work-related) are incongruent, then risk-taking should be lower, as the decision maker might feel the situation is unusual or inappropriate. Although results do not reveal that work-associated environments generally encourage riskier work-related decisions (and likewise for non-work), we found environmental effects on decision making when including mood as a moderator.

Practitioner summary: Mobile workers are required to make decisions in various environments. We assumed that decisions are more risky when they are made in a fitting environment (e.g. work-related decisions in work environments). Results of the two experiments (laboratory and field) only show an environmental effect when mood is included as a moderator.     

Software Engineering Using RATionale

Many decisions have to be made when developing a software system and a successful outcome depends on how well thought out these decisions were. One way that the decisions made, and alternatives considered, can be captured is in the rationale for the system. The rationale goes beyond standard documentation by capturing the developers’ intent and all alternatives considered rather than only those selected. While the potential usefulness of this information is seldom questioned, it typically is not captured in practice. We feel that the key to motivating capture is to provide compelling uses and tool support integrated with the development environment. Here we describe the Software Engineering Using RATionale system which inferences over the rationale to evaluate decision alternatives and perform impact assessment when requirements, development criteria, and assumptions change.     

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

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

A Game-theoretic approach to analyze interacting actors in GRL goal models

Goal-oriented requirements engineering aims to capture desired goals and strategies of relevant stakeholders during early requirements engineering stages, using goal models. Goal-oriented modeling techniques support the analysis of system requirements (especially non-functional ones) from an operationalization perspective, through the evaluation of alternative design options. However, conflicts and undesirable interactions between requirements produced from goals are inevitable, especially as stakeholders often aim for different objectives. In this paper, we propose an approach based on game theory and the Goal-oriented Requirement Language (GRL) to reconcile interacting stakeholders (captured as GRL actors), leading to reasonable trade-offs. This approach consists in building a payoff bimatrix that considers all actor’s valid GRL strategies, and computing its Nash equilibrium. Furthermore, we use two optimization techniques to reduce the size of the payoff bimatrix, hence reducing the computational cost of the Nash equilibrium. The approach goes beyond existing work by supporting nonzero-sum games, multiple alternatives, and inter-actor dependencies. We demonstrate the applicability of our game-theoretic modeling and analysis approach using a running example and two GRL models from the literature, with positive results on feasibility and applicability, including performance results.