Non-formal techniques for requirements elicitation, modeling, and early assessment for services

Designing systems for multiple stakeholders requires frequent collaboration with multiple stakeholders from the start. In many cases at least some stakeholders lack a professional habit of formal modeling. We report observations from two case studies of stakeholder-involvement in early design where non-formal techniques supported strong collaboration resulting in deep understanding of requirements and of the feasibility of solutions.

Systematizing requirements elicitation technique selection

Context: This research deals with requirements elicitation technique selection for software product requirements and the overselection of open interviews. Objectives: This paper proposes and validates a framework to help requirements engineers select the most adequate elicitation techniques at any time. Method: We have explored both the existing underlying theory and the results of empirical research to build the framework. Based on this, we have deduced and put together justified proposals about the framework components. We have also had to add information not found in theoretical or empirical sources. In these cases, we drew on our own experience and expertise. Results: A new validated approach for requirements technique selection. This new approach selects tech- niques other than open interview, offers a wider range of possible techniques and captures more require- ments information. Conclusions: The framework is easily extensible and changeable. Whenever any theoretical or empirical evidence for an attribute, technique or adequacy value is unearthed, the information can be easily added to the framework.

Elicitation techniques for the evaluation of speech under stress: Towards a framework for use in a controlled environment

Existing work in Computer Science and Electronic Engineering demonstrates that Digital Signal Processing techniques can effectively identify the presence of stress in the speech signal. These techniques use datasets containing real or actual stress samples i.e. real-life stress such as 911 calls and so on. Studies that use simulated or laboratory-induced stress have been less successful and inconsistent. Pervasive, ubiquitous computing is increasingly moving towards voice-activated and voice-controlled systems and devices. Speech recognition and speaker identification algorithms will have to improve and take emotional speech into account. Modelling the influence of stress on speech and voice is of interest to researchers from many different disciplines including security, telecommunications, psychology, speech science, forensics and Human Computer Interaction (HCI). The aim of this work is to assess the impact of moderate stress on the speech signal. In order to do this, a dataset of laboratory-induced stress is required. While attempting to build this dataset it became apparent that reliably inducing measurable stress in a controlled environment, when speech is a requirement, is a challenging task. This work focuses on the use of a variety of stressors to elicit a stress response during tasks that involve speech content. Biosignal analysis (commercial Brain Computer Interfaces, eye tracking and skin resistance) is used to verify and quantify the stress response, if any. This thesis explains the basis of the author’s hypotheses on the elicitation of affectively-toned speech and presents the results of several studies carried out throughout the PhD research period. These results show that the elicitation of stress, particularly the induction of affectively-toned speech, is not a simple matter and that many modulating factors influence the stress response process. A model is proposed to reflect the author’s hypothesis on the emotional response pathways relating to the elicitation of stress with a required speech content. Finally the author provides guidelines and recommendations for future research on speech under stress. Further research paths are identified and a roadmap for future research in this area is defined.

Identifying Moderator Variables Through Requirements Elicitation Experiments Limitations

Interviews are the most widely used elicitation technique in Requirements Engineering (RE). Despite its importance, research in interviews is quite limited, in particular from an experimental perspective. We have performed a series of experiments exploring the relative effectiveness of structured and unstructured interviews. This line of research has been active in Information Systems in the past years, so that our experiments can be aggregated together with existing ones to obtain guidelines for practice. Experimental aggregation is a demanding task. It requires not only a large number of experiments, but also considering the influence of the existing moderators. However, in the current state of the practice in RE, those moderators are unknown. We believe that analyzing the threats to validity in interviewing experiments may give insight about how to improve further replications and the corresponding aggregations. It is likely that this strategy may be applied in other Software Engineering areas as well.

Lean principles and techniques for improving the quality and productivity of software development projects: a case study

Software product development is recognised as difficult due to the intangible nature of the product, requirements elicitation, effective progress measurement, and so forth. In this paper, we describe some of the challenges of software product development and how the challenges are being met by lean management principles and techniques. Specifically, we examine lean principles and techniques that were devised by Toyota and other manufacturers over the last 50 years. Applying lean principles to software development projects has been advocated for over ten years and it will be shown that the extensive lean literature is a valuable source of ideas for software development. A case study with a software development organisation, Timberline Inc., will demonstrate that lean principles and techniques can be successfully applied to software product development.

Enhancing Security Requirements Engineering by Organisational Learning

More and more software projects today are security-related in one way or the other. Requirements engineers often fail to recognise indicators for security problems which is a major source of security problems in practice. Identifying security-relevant requirements is labour-intensive and errorprone. In order to facilitate the security requirements elicitation process, we present an approach supporting organisational learning on security requirements by establishing company-wide experience resources, and a socio-technical network to benefit from them. The approach is based on modelling the flow of requirements and related experiences. Based on those models, we enable people to exchange experiences about security-requirements while they write and discuss project requirements. At the same time, the approach enables participating stakeholders to learn while they write requirements. This can increase security awareness and facilitate learning on both individual and organisational levels. As a basis for our approach, we introduce heuristic assistant tools which support reuse of existing security-related experiences. In particular, they include Bayesian classifiers which issue a warning automatically when new requirements seem to be security-relevant. Our results indicate that this is feasible, in particular if the classifier is trained with domain specific data and documents from previous projects. We show how the ability to identify security-relevant requirements can be improved using this approach. We illustrate our approach by providing a step-by-step example of how we improved the security requirements engineering process at the European Telecommunications Standards Institute (ETSI) and report on experiences made in this application.

Towards executable specification : combining i* and AgentSpeak(L).

Agent-oriented conceptual modelling (AoCM) approaches in Requirements Engineering (RE) have received considerable attention recently. Semi-formal modeling frameworks such as i* assist analysts in requirements elicitation and reasoning of early-phase RE. AgentSpeak(L) is a widely accepted agent programming language. The Strategic Rationale (SR) model of the i* framework naturally lends itself to AgentSpeak(L) programs. Furthermore, the Strategic Dependency (SD) component of the i* framework prescribes the interaction between the agents in a multi-agent environment. This paper proposes a formal methodology for transforming a SR model to an AgentS- peak(L) agent. The constructed AgentSpeak(L) agents will then form the essential components of a multi-agent system, MAS.

Eliciting Expert Knowledge in Conservation Science

Expert knowledge is used widely in the science and practice of conservation because of the complexity of problems, relative lack of data, and the imminent nature of many conservation decisions. Expert knowledge is substantive information on a particular topic that is not widely known by others. An expert is someone who holds this knowledge and who is often deferred to in its interpretation. We refer to predictions by experts of what may happen in a particular context as expert judgments. In general, an expert-elicitation approach consists of five steps: deciding how information will be used, determining what to elicit, designing the elicitation process, performing the elicitation, and translating the elicited information into quantitative statements that can be used in a model or directly to make decisions. This last step is known as encoding. Some of the considerations in eliciting expert knowledge include determining how to work with multiple experts and how to combine multiple judgments, minimizing bias in the elicited information, and verifying the accuracy of expert information. We highlight structured elicitation techniques that, if adopted, will improve the accuracy and information content of expert judgment and ensure uncertainty is captured accurately. We suggest four aspects of an expert elicitation exercise be examined to determine its comprehensiveness and effectiveness: study design and context, elicitation design, elicitation method, and elicitation output. Just as the reliability of empirical data depends on the rigor with which it was acquired so too does that of expert knowledge.

Understanding the academic environments : from field study to design

Ethnographic methods have been widely used for requirements elicitation purposes in systems design, especially when the focus is on understanding users? social, cultural and political contexts. Designing an on-line search engine for peer-reviewed papers could be a challenge considering the diversity of its end users coming from different educational and professional disciplines. This poster describes our exploration of academic research environments based on different in situ methods such as contextual interviews, diary-keeping, job-shadowing, etc. The data generated from these methods is analysed using a qualitative data analysis software and subsequently is used for developing personas that could be used as a requirements specification tool.

Potential uses of Bayesian networks as tools for synthesis of systematic reviews of complex interventions

Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention. Bayesian networks are useful extensions to logic maps when initiating a review or to facilitate synthesis and bridge the gap between evidence acquisition and decision-making. Formal elicitation techniques allow development of BNs on the basis of expert opinion. Such applications are useful alternatives to ‘empty’ reviews, which identify knowledge gaps but fail to support decision-making. Where review evidence exists, it can inform the development of a BN. We illustrate the construction of a BN using a motivating example that demonstrates how BNs can ensure coherence, transparently structure the problem addressed by a complex intervention and assess sensitivity to context, all of which are critical components of robust reviews of complex interventions. We suggest that BNs should be utilised to routinely synthesise reviews of complex interventions or empty reviews where decisions must be made despite poor evidence.

International Workshop for Management and Trade of Caiman yacare, Gainsville, FL, 3-5 October 2002

A workshop was held 3-5 October 2002 in Gainesville, Florida, USA to discuss management, conservation and trade in Caiman yacare. Twenty five official participants represented the four yacare range states (Argentina, Bolivia, Brazil, Paraguay), Venezuela, USA, the meeting sponsors (US Fish and Wildlife Service, CITES Secretariat, Louisiana Fur and Alligator Council), TRAFFIC Sur America and Crocodile Specialist Group. A series of country reports detailing yacare management in the four range states were distributed in Spanish and English prior to the meeting and presentations on these and on general principles of crocodilian harvest, conservation and management provided the basis for the discussions. Three working groups considered: • Requirements and field techniques for field data collection. • Requirements and techniques for regulation of harvest. • Requirements and processes for regulation of trade and export. Written reports of working groups and a plenary drafting session were finalized during the meeting and distributed, with the country reports, to participants. The workshop drafted a framework for caiman management and regulation that could be used as a template and adapted for use in each range state. The meeting agreed to convene an ad-hoc working group of range state representatives to continue discussions on the harmonization of caiman management into the future.

个性化领域知识支持的用户主导需求获取方法

应用软件的需求获取与应用领域的特征密切相关,用户的参与日益受到重视,然而用户对系统的认识通常模糊且不完整,且对于多用户系统,需要拥有局部需求的多用户进行协同,才能得到完整、一致的需求.提出一种用户主导的需求获取方法,根据用户特征及其上下文环境,为用户进行需求定义提供个性化的领域知识支持,包括领域需求资产推荐和对多用户协同需求获取的建议.应用实例说明了该方法的可行性,且对于提高用户参与程度、改进领域知识重用效果,从而最终提高需求获取的质量具有积极意义.

一种用户主导的需求获取与共赢协商方法研究

软件开发的成败与需求的质量有紧密的关系。充分获取和理解用户的目标和需求，并采取有效的方法支持多涉众（用户、项目经理、开发人员等）间通过协商就需求达成共识，对软件开发的成功至关重要。然而，在需求获取和协商的过程中，用户对软件系统的认识通常是模糊且不完整的，难以系统、清晰地描述自己的需求；同时，多涉众由于目标不同，容易导致需求冲突，需要通过协商达成共赢，但怎样确定共赢的协议缺少有效的指导方法。 本文提出一种用户主导的需求获取与共赢协商方法，通过提供个性化的领域知识推荐来促进用户更清晰有效地表达其需求，并引入公平分配的方法来确保涉众在需求协商中的公平共赢。该方法包括基于个性化领域知识的用户主导需求获取阶段和基于公平分配的共赢协商阶段，并提供了相应的支持算法。在基于个性化领域知识的用户主导需求获取阶段，用户以目标和用例的形式定义需求，该方法为用户提供个性化的领域知识推荐，帮助涉众复用相关的领域需求，而用户定义的需求经过领域专家的选择和精化可以用来扩充领域知识库。在基于公平分配的共赢协商阶段，用户与其他涉众就需求进行协商，最终达成公平共赢的协议。作为对该过程的支持，本文提出了一种个性化领域知识推荐算法，以及一种公平共赢需求协商算法。本文最后通过两个软件开发的案例，阐述了该方法的应用，并验证了方法的有效性。 用户主导的需求获取与共赢协商方法能够促进用户在需求获取中的参与，有助于领域知识的积累和复用，并能够确保需求协商中涉众间的公平共赢。该方法有助于提高需求获取的质量，促进涉众间的合作，对于保障软件开发的成功具有积极意义。