Picking battles: The impact of trust assumptions on the elaboration of security requirements

This position paper describes work on trust assumptions in the con-text of security requirements. We show how trust assumptions can affect the scope of the analysis, derivation of security requirements, and in some cases how functionality is realized. An example shows how trust assumptions are used by a requirements engineer to help define and limit the scope of analysis and to document the decisions made during the process

Hypermedia support for argumentation-based rationale: 15 years on from gIBIS and QOC

Having developed, used and evaluated some of the early IBIS-based approaches to design rationale (DR) such as gIBIS and QOC in the late 1980s/mid-1990s, we describe the subsequent evolution of the argumentation-based paradigm through software support, and perspectives drawn from modeling and meeting facilitation. Particular attention is given to the challenge of negotiating the overheads of capturing this form of rationale. Our approach has maintained a strong emphasis on keeping the representational scheme as simple as possible to enable real time meeting mediation and capture, attending explicitly to the skills required to use the approach well, particularly for the sort of participatory, multi-stakeholder requirements analysis demanded by many design problems. However, we can then specialize the notation and the way in which the tool is used in the service of specific methodologies, supported by a customizable hypermedia environment, and interoperable with other software tools. After presenting this approach, called Compendium, we present examples to illustrate the capabilities for support security argumentation in requirements engineering, template driven modeling for document generation, and IBIS-based indexing of and navigation around video records of meetings

A systematic review of protocol studies on conceptual design cognition: design as search and exploration

This paper reports findings from the first systematic review of protocol studies focusing specifically on conceptual design cognition, aiming to answer the following research question: What is our current understanding of the cognitive processes involved in conceptual design tasks carried out by individual designers? We reviewed 47 studies on architectural design, engineering design and product design engineering. This paper reports 24 cognitive processes investigated in a subset of 33 studies aligning with two viewpoints on the nature of designing: (V1) design as search (10 processes, 41.7%); and (V2) design as exploration (14 processes, 58.3%). Studies on search focused on solution search and problem structuring, involving: long-term memory retrieval; working memory; operators and reasoning processes. Studies on exploration investigated: co-evolutionary design; visual reasoning; cognitive actions; and unexpected discovery and situated requirements invention. Overall, considerable conceptual and terminological differences were observed among the studies. Nonetheless, a common focus on memory, semantic, associative, visual perceptual and mental imagery processes was observed to an extent. We suggest three challenges for future research to advance the field: (i) developing general models/theories; (ii) testing protocol study findings using objective methods conducive to larger samples and (iii) developing a shared ontology of cognitive processes in design

Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications

Wireless sensor networks monitor dynamic environments that change rapidly over time. This dynamic behavior is either caused by external factors or initiated by the system designers themselves. To adapt to such conditions, sensor networks often adopt machine learning techniques to eliminate the need for unnecessary redesign. Machine learning also inspires many practical solutions that maximize resource utilization and prolong the lifespan of the network. In this paper, we present an extensive literature review over the period 2002-2013 of machine learning methods that were used to address common issues in wireless sensor networks (WSNs). The advantages and disadvantages of each proposed algorithm are evaluated against the corresponding problem. We also provide a comparative guide to aid WSN designers in developing suitable machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial