Software Requirements Engineering Research Articles

Learning complex action models with quantifiers and logical implications

Automated planning requires action models described using languages such as the Planning Domain Definition Language (PDDL) as input, but building action models from scratch is a very difficult and time-consuming task, even for experts. This is because it is difficult to formally describe all conditions and changes, reflected in the preconditions and effects of action models. In the past, there have been algorithms that can automatically learn simple action models from plan traces. However, there are many cases in the real world where we need more complicated expressions based on universal and existential quantifiers, as well as logical implications in action models to precisely describe the underlying mechanisms of the actions. Such complex action models cannot be learned using many previous algorithms. In this article, we present a novel algorithm called LAMP ( Learning Action Models from Plan traces), to learn action models with quantifiers and logical implications from a set of observed plan traces with only partially observed intermediate state information. The LAMP algorithm generates candidate formulas that are passed to a Markov Logic Network (MLN) for selecting the most likely subsets of candidate formulas. The selected subset of formulas is then transformed into learned action models, which can then be tweaked by domain experts to arrive at the final models. We evaluate our approach in four planning domains to demonstrate that LAMP is effective in learning complex action models. We also analyze the human effort saved by using LAMP in helping to create action models through a user study. Finally, we apply LAMP to a real-world application domain for software requirement engineering to help the engineers acquire software requirements and show that LAMP can indeed help experts a great deal in real-world knowledge-engineering applications.

Use case modeling approach for early aspect acquisition

In the recent years, use cases have been widely applied in software requirement engineering, and use cases have proven particularly valuable as part of the requirements activities of the software process. Use cases play more and more important roles in some modern software processes and methods. Early aspects are defined as crosscutting concerns in the early life cycle phases including the requirements analysis, domain analysis and architecture design phases. Use case modeling approach which supports the acquisition of early aspects is proposed. It accepted the increment and iteration development ideas of Unified Process. The process of use case modeling is divided by five iterative stages which are called initial use case, basic use case, detailed use case, advanced use case and extend use case. The approach supports the early aspects acquisition at requirements level, and early aspect will be captured by analysis the use case properties with aspect features. Modeling processes of this kind of approach is discussed and applying the approach to a case study and analysis are given. We argue that identification of early aspects supports effective determination of their mapping and influence of artifacts at later development stages.

Astrolabe: A Collaborative Multiperspective Goal-Oriented Risk Analysis Methodology

The intention of this paper is to introduce a risk analysis methodology called Astrolabe. Astrolabe is based on causal analysis of systems risks. It allows the analysts to both align the current standpoint of the system with its intentions and identify any vulnerabilities or hazards that threaten the systems stability. Astrolabe adopts concepts from organizational theory and software requirement engineering. The aim of Astrolabe is to guide risk analysis through its phases so that a near complete investigation of system risks is performed. The concepts and methods driving the Astrolabe methodology have been clearly explained in this paper.

Ontology (Science)

AbstractIncreasingly, in data-intensive areas of the life sciences, experimental results are being described in algorithmically useful ways with the help of ontologies. Such ontologies are authored and maintained by scientists to support the retrieval, integration and analysis of their data. The proposition to be defended here is that ontologies of this type – the Gene Ontology (GO) being the most conspicuous example – are a part of science. Initial evidence for the truth of this proposition (which some will find self-evident) is the increasing recognition of the importance of empirically-based methods of evaluation to the ontology develop¬ment work being undertaken in support of scientific research. Ontologies created by scientists must, of course, be associated with implementations satisfying the requirements of software engineering. But the ontologies are not themselves engineering artifacts, and to conceive them as such brings grievous consequences. Rather, ontologies such as the GO are in different respects comparable to scientific theories, to scientific databases, and to scientific journal publications. Such a view implies a new conception of what is involved in the author¬ing, maintenance and application of ontologies in scientific contexts, and therewith also a new approach to the evaluation of ontologies and to the training of ontologists.

Iberoamerican workshop on requirements engineering and software environments, ideas 2008 [special issue introduction

This special issue contains a selection of the best papers presented at the XI Iberoamerican Workshop on Requirements Engineering and Software Environments (IDEAS'08), that was held in Recife, Pernambuco, Brazil, on 11-15 February 2008. The papers included here provide some good examples of the research being currently conducted in Iberoamerica, Spain and Portugal in the context of Software Enginerering and Requirements Engineering.

Ontology (Science)

AbstractIncreasingly, in data-intensive areas of the life sciences, experimental results are being described in algorithmically useful ways with the help of ontologies. Such ontologies are authored and maintained by scientists to support the retrieval, integration and analysis of their data. The proposition to be defended here is that ontologies of this type – the Gene Ontology (GO) being the most conspicuous example – are a part of science. Initial evidence for the truth of this proposition (which some will find self-evident) is the increasing recognition of the importance of empirically-based methods of evaluation to the ontology development work being undertaken in support of scientific research. The ontologies created by scientists must, of course, be associated with implementations satisfying the requirements of software engineering. But these ontologies are not themselves engineering artifacts, and to conceive them as such brings grievous consequences. Rather, we shall argue, ontologies such as the GO are comparable to scientific theories, to scientific databases, or to scientific journal publications. Such a view implies a radically new conception of what is involved in the authoring, maintenance and application of ontologies in scientific contexts, and therewith also a radically new approach to the evaluation of ontologies and to the training of ontologists.

Special issue on applications and advances in problem frames

Special issue on applications and advances in problem frames

Information behavior in requirements engineering: An initial review of the research

AbstractThis paper provides an overview of the existing research on information behavior (IB) in the practice of software requirements engineering (RE) and the research which, although it does not refer to IB or to RE by name, addresses the concepts and theories of one within the framework of the other. The paper begins with operational definitions of the terms “requirements,” “requirements engineering,” “information behavior,” and “information behavior in requirements engineering” to set the framework for this analysis. A number of authors have written extensively on theories of IB. Similarly, although perhaps less well known to those in the Library and Information Science (LIS) community, many terms exist for the field and practices of software requirements elicitation, documentation and maintenance, herein referred to as RE. Although RE is still a relatively young field, having emerged from computer science and software engineering in only the past 20‐30 years, research in the field is diverse and growing. However, little research has taken place specifically on IB in RE. In some cases, research on IB and RE progresses on parallel paths, even utilizing the same terminology, without a recognition of the other community's work. The paper follows the operational definitions with a review of the collective set of literature covering IB in RE and that which reflects IB in RE but does not label it as such. The next section includes a discussion of what the reviewed literature reveals about the state of research and practice in this area, and the paper concludes with suggestions for future research.

By students, for students: a production-quality multimedia library and its application to game-based teaching.

The attractive idea of using game development for teaching programming can only meet student expectations and modern software engineering requirements if it uses advanced multimedia technology, at the level of the best commercial solutions. In implementing novel pedagogical techniques, we have developed a powerful multimedia library, with major contributions from students, and used it to offer games as course projects. More than 150 games have been developed, many of very high quality, and publicly available for everyone’s enjoyment. This experience combines advanced software development with student participation, strong O-O software engineering principles, and the excitement of one of the coolest areas of technology.

Investigating the use of software requirements engineering techniques in simulation modelling

The utility and benefits of a well-defined requirements engineering process are cited in many articles describing software engineering research and similar industry studies. In this paper, we consider to what extent the modelling and simulation (M&S) community employs software requirements engineering (SRE) in the model development process and, based on our observations, suggest the inclusion of several SRE activities within an M&S life-cycle model. We motivate the desirability of having an SRE component by first outlining current SRE models and their touted benefits. To help formulate a reasoned conclusion, we examined several recent M&S books and three M&S life-cycle models for references to requirements in the M&S activities. Our findings, also outlined in this paper, indicate that the use of any formal SRE activities within M&S development and analysis is minimal, with the possible exception of military and government projects. Nonetheless, our investigation has also uncovered some recent changes that point to a rise in the awareness of the need for a more formal well-defined approach to SRE in the M&S model development process. We build on that awareness by suggesting a refined M&S life-cycle model that incorporates several of the more prominent SRE activities. The potential benefits of and additional opportunities for increased SRE use are also discussed.

An Improved Assessment of Personality Traits in Software Engineering

The success or otherwise of Software Engineering (SE) activities depends on the interactions among software engineers. Consequently, effective interactions depend largely on personality traits, which is a consistent and long-lasting tendency in behaviour. In psychology, five major trait factors (The Big Five Factors) have been generally used to assess personality of people. But, these might not be adequate in SE because of the required technical and cognitive skills. In this work, we first present Cognitive Ability as an additional factor that must be measured in order to adequately assess personality in SE. A research survey was conducted in order to capture personality requirements in SE. Based on the result of the survey conducted, we develop a model for assessing personality traits in SE. We then design an assessment technique that is based on responses to some well-structured and deductive on-line questions. The implementation of the model using Visual Basic resulted in a much-needed tool that can guide intending software engineers in choosing area of specialization in SE based on their personality traits.

BUILDING DECISION SUPPORT PROBLEM DOMAIN ONTOLOGY FROM NATURAL LANGUAGE REQUIREMENTS FOR SOFTWARE ASSURANCE

The process of engineering software-intensive systems that comply with their Certification and Accreditation (C&A) requirements involves many critical decision-making activities for the related stakeholders. Considering the exhaustive nature of C&A activities together with the complexity of software-intensive systems, effective decision making relies heavily on the ways to understand and structure the problem domain concepts concerning decision points for interpretation, applicability, scope, evaluation, and impact of the enforced C&A requirements. These decision points are further complicated by natural language specifications of inherently non-functional C&A requirements scattered across multiple regulatory documents with complex interdependencies at different levels of abstractions in the organizational hierarchy, which often result in subjective interpretations and non-standard implementations of the C&A process. To address these issues, we define a systematic methodology using novel techniques from software Requirements Engineering (RE) and knowledge engineering for understanding and structuring the problem domain concepts based on a uniform representation format that promotes common understanding among stakeholders. Specifically, we use advanced ontological engineering techniques driven by theoretical RE foundations to systematically elicit, model, understand, and analyze problem domain concepts concerning significant and difficult decision points throughout the C&A process. We demonstrate the appropriateness of our methodology in creating decision support problem domain ontology using several examples derived from our experiences on automating the Department of Defense Information Technology Security C&A Process (DITSCAP).

Customer Requirement Management in Product Development

Customer requirement management has been wellrecognized as the principal factor for developing a successful product in the marketplace. This has been acknowledged in an exponentially increasing number of publications in the field of customer satisfaction and requirement management, as well as in many endeavors in industrial applications. This research topic shows a multidisciplinary characteristic involving such fields as business studies, marketing research, psychological studies, human factors, software requirement engineering, and of course product and engineering design. In recent times, the importance of these front-end issues has been catalyzed by enormous e-commerce applications. This special issue is dedicated to the recent advances in customer requirement management. While requirement engineering has been intensively studied in the field of software and information systems, the focus of this special issue is given to the design and development of consumer and capital products. Based on the thorough and strict peer reviews, a total of eight papers are selected for publication from 38 submissions. These papers represent a snapshot of the cutting-edge research progress and aim to disseminate information on recent developments in the field of customer requirement management. The article by Jiao, Chen, and Fung, ‘Customer Requirement Management in Product Development: A Review of Research Issues’, provides a comprehensive literature review. It substantially extends this editorial discussion on the status quo of approaches and techniques for customer requirement management in product development. The article discusses the general process of customer requirement management. The emphasis is on a holistic view and system-wide solutions that encompass requirement elicitation, analysis, and specification. In the article, avenues for future research are highlighted along with technical challenges. Henson, Barnes, Livesey, Childs, and Ewart, in their article, ‘Affective Consumer Requirements: A Case Study of Moisturizer Packaging’, apply affective engineering approaches to the elicitation of customers’ subjective requirements. A case study of moisturizer packaging is reported, demonstrating how to recombine stimuli that have been tested separately. The results of focus groups and semantic questionnaires are fine-tuned based on the principal component analysis in order to translate the subjective requirements into values for physical properties of the packaging. The elicited requirements regarding surface textures, shape, and color are validated through the questionnaire responses to prototype packaging. The article by Khalid and Helander, ‘Customer Emotional Needs in Product Design’, emphasizes on the emotional aspect of customer requirements. The characteristics of customer emotions are discussed in detail, along with issues concerning their measurement and evaluation. They present a framework of articulating customer emotions in relation to the designer’s environment. As part of the product development life cycle, the framework enables customer needs and measured emotions to be fed early in the design process, so as to achieve a pleasurable and satisfying product. With focus on the relationships between consumers’ Kansei feelings and products’ formal elements, Chen *Author to whom correspondence should be addressed. E-mail: jiao@pmail.ntu.edu.sg

4everedit — Team-based Process Documentation Management

The introduction and successful application of engineering processes demands a modern infrastructure that supports efficient and convenient management of the various work products, their life cycle, and their relations to each other. Mostly, work products are realized in the form of electronic documents that can easily be edited, stored, copied and exchanged. However, most infrastructure is fundamentally limited by the fact that the information contained in many documents is not accessible because its semantics is unknown. For example, software engineers often document the design of a software architecture in a rather unstructured way and hence cannot benefit from automatic evaluations such as consistency checks regarding the document itself (is it complete?) or its dependencies to other documents (is there a test specification for each component?). Because most documents are inherently structured as a result of the application of certain methods (such as CRC-Cards for software requirements engineering) and because techniques are available to model and handle structured documents (such as XML), combining both successfully seems to be a small gap to bridge. In this article we present the essential concepts to support team-based editing of structured text-based engineering documents. We report on our experiences from the application of the infrastructure ‘4everedit’ in a large-scale industrial process engineering project. Copyright © 2006 John Wiley & Sons, Ltd.

Inclusive development: Software engineering requirements for universally accessible interactions

The notion of ‘universal access’ reflects the concept of an Information Society in which potentially anyone (i.e. any user) will interact with computing machines, at anytime and anyplace (i.e. in any context of use) and for virtually anything (i.e. for any task). Towards reaching a successful and cost effective realization of this vision, it is critical to ensure that the future interface development tools provide all the necessary instrumentation to support inclusive design, i.e. facilitate inclusive development. In the meantime, it is crucial that both tool developers and interface developers acquire awareness regarding the key development features they should pursue when investigating for the most appropriate software engineering support in addressing such a largely demanding development goal (i.e. universally accessible interactions). This paper discusses a corpus of key development requirements for building universally accessible interactions that has been consolidated from real practice, in the course of six medium-to-large scale research projects, all completed, within a 10 years timeframe.

Algorithms for strong coupling procedures

This paper considers algorithms for computing the response of a coupled problem with a partitioned approach. One important example treated here is fluid–structure interaction (FSI). Often procedures or even software exists to solve each sub-problem separately, and one wants to couple both. This setting seems to allow only the so-called weak coupling which is not sufficient for some problems. The so-called strong coupling is often a totally implicit formulation, where the system components are evaluated at the same time level. This usually requires an iterative procedure. The FSI problem is cast as an abstract differential algebraic equation (DAE), for which the coupling procedures are developed. With the partitioned approach, one simple and frequently used computational procedure is similar to a block-Gauss–Seidel iteration. It is shown why this approach may experience difficulties, and how they may be circumvented with Newton-like methods still staying in the partitioned framework. The functional and software engineering requirements for the simulation interface are described and analysed. Some simple coupled example problems demonstrate how the proposed procedures work.

VISUAL DEBUGGING: A WAY OF ANALYZING, UNDERSTANDING AND COMMUNICATING BOTTOM‐UP SIMULATION MODELS IN ECOLOGY

ABSTRACT. Bottom‐up simulation models, i.e. individual‐based and spatially explicit models, are powerful new tools in ecology and natural resource management. However, they have to be implemented as more or less complex software and are therefore harder to analyze, understand, and communicate than mathematical models. Particularly critical is the problem of communication, which must be solved if bottom‐up models are to be scientifically credible. As a pragmatic solution to this problem, “visual debugging‘ is proposed, which means equipping simulation programs with a graphical user interface that integrates elements of conventional debugging and graphical representations of the model's state variables. The direct benefit of visual debugging is that the attitude of debugging, i.e. performing controlled experiments, is transferred to the overall development and analysis of the model. This facilitates acknowledging the hierarchical organization of ecological systems and using patterns observed in real systems for developing and validating the models. The benefit for communicating bottom‐up models is that peers can download the executable program from the internet and test and analyze the model on their own. Visual debugging is not meant as an exclusive alternative to other approaches of communicating bottom‐up simulation models, i.e. software libraries or general protocols of model description, but should be combined with these approaches. Overall, visual debugging integrates general principles of software engineering and specific requirements for modeling ecological systems and would therefore contribute to establishing an improved culture of analyzing, understanding, and communicating bottom‐up simulation models.

The Real-Time Process Algebra (RTPA)

The real-time process algebra (RTPA) is a set of new mathematical notations for formally describing system architectures, and static and dynamic behaviors. It is recognized that the specification of software behaviors is a three-dimensional problem known as: (i) mathematical operations, (ii) event/process timing, and (iii) memory manipulations. Conventional formal methods in software engineering were designed to describe the 1-D (type (i)) or 2-D (types (i) and (iii)) static behaviors of software systems via logic, set and type theories. However, they are inadequate to address the 3-D problems in real-time systems. A new notation system that is capable to describe and specify the 3-D real-time behaviors, the i>real-time process algebra (RTPA), is developed in this paper to meet the fundamental requirements in software engineering. RTPA is designed as a coherent software engineering notation system and a formal engineering method for addressing the 3-D problems in software system specification, refinement, and implementation, particularly for real-time and embedded systems. In this paper, the RTPA meta-processes, algebraic relations, system architectural notations, and a set of fundamental primary and abstract data types are described. On the basis of the RTPA notations, a system specification method and a refinement scheme of RTPA are developed. Then, a case study on a telephone switching system is provided, which demonstrates the expressive power of RTPA on formal specification of both software system architectures and behaviors. RTPA elicits and models 32 algebraic notations, which are the common core of existing formal methods and modern programming languages. The extremely small set of formal notations has been proven sufficient for modeling and specifying real-time systems, their architecture, and static/dynamic behaviors in real-world software engineering environment.

Understanding the requirements for developing open source software systems

This study presents an initial set of findings from an empirical study of social processes, technical system configurations, organisational contexts and interrelationships that give rise to open software. The focus is directed at understanding the requirements for open software development efforts, and how the development of these requirements differs from those traditional to software engineering and requirements engineering. Four open software development communities are described, examined and compared to help discover what these differences may be. Eight kinds of software informalisms are found to play a critical role in the elicitation, analysis, specification, validation and management of requirements for developing open software systems. Subsequently, understanding the roles these software informalisms take in a new formulation of the requirements development process for open source software is the focus of this study. This focus enables the consideration of a reformulation of the requirements engineering process and its associated artefacts, or (in)formalisms, to better account for the requirements for developing open source software systems.

Visual debugging: a way of analyzing, understanding and communicating bottom-up simulation models in ecology

ABSTRACT. Bottom-up simulation models, i.e. individual-based and spatially explicit models, are powerful new tools in ecology and natural resource management. However, they have to be implemented as more or less complex software and are therefore harder to analyze, understand, and communicate than mathematical models. Particularly critical is the problem of communication, which must be solved if bottom-up models are to be scientifically credible. As a pragmatic solution to this problem, “visual debugging‘ is proposed, which means equipping simulation programs with a graphical user interface that integrates elements of conventional debugging and graphical representations of the model's state variables. The direct benefit of visual debugging is that the attitude of debugging, i.e. performing controlled experiments, is transferred to the overall development and analysis of the model. This facilitates acknowledging the hierarchical organization of ecological systems and using patterns observed in real systems for developing and validating the models. The benefit for communicating bottom-up models is that peers can download the executable program from the internet and test and analyze the model on their own. Visual debugging is not meant as an exclusive alternative to other approaches of communicating bottom-up simulation models, i.e. software libraries or general protocols of model description, but should be combined with these approaches. Overall, visual debugging integrates general principles of software engineering and specific requirements for modeling ecological systems and would therefore contribute to establishing an improved culture of analyzing, understanding, and communicating bottom-up simulation models.