Cloud adoption:prioritizing obstacles and obstacles resolution tactics using AHP

The enormous potential of cloud computing for improved and cost-effective service has generated unprecedented interest in its adoption. However, a potential cloud user faces numerous risks regarding service requirements, cost implications of failure and uncertainty about cloud providers' ability to meet service level agreements. These risks hinder the adoption of cloud. We extend the work on goal-oriented requirements engineering (GORE) and obstacles for informing the adoption process. We argue that obstacles prioritisation and their resolution is core to mitigating risks in the adoption process. We propose a novel systematic method for prioritising obstacles and their resolution tactics using Analytical Hierarchy Process (AHP). We provide an example to demonstrate the applicability and effectiveness of the approach. To assess the AHP choice of the resolution tactics we support the method by stability and sensitivity analysis. Copyright 2014 ACM.

How the web of things challenges requirements engineering

As a subset of the Internet of Things (IoT), the Web of Things (WoT) shares many characteristics with wireless sensor and actuator networks (WSANs) and ubiquitous computing systems (Ubicomp). Yet to a far greater degree than the IoT, WSANs or Ubicomp, the WoT will integrate physical and information objects, necessitating a means to model and reason about a range of context types that have hitherto received little or no attention from the RE community. RE practice is only now developing the means to support WSANs and Ubicomp system development, including faltering first steps in the representation of context. We argue that these techniques will need to be developed further, with a particular focus on rich context types, if RE is to support WoT application development. © 2012 Springer-Verlag.

Revisiting goal-oriented models for self-aware systems-of-systems

Systems-of-systems (SoS) are systems resulted from the interaction among other independent constituent systems that collaborate to offer new functionalities towards accomplishing global missions. Each of these constituent systems accomplishes its individual missions and is able to contribute to the achievement of the global missions of the SoS, both being viewed as a set of associated goals. In the perspective of self-aware systems, SoS need to exhibit goal-awareness, i.e., They need to be aware of their own goals and of how their constituent systems contribute to their accomplishment. In this paper, we revisit goal-oriented concepts aiming at identifying and modeling goals at both SoS level and the constituent systems level. Moreover, we take advantage of such goal-oriented models to express the relationship among goals at these levels as well as to define how each constituent system can contribute to the accomplishment of global goals of an SoS. In addition, we shed light on important issues related to goal modeling in self-aware SoS to be addressed in future research.

A goal-based modeling approach to develop requirements of an adaptive system with environmental uncertainty

Dynamically adaptive systems (DASs) are intended to monitor the execution environment and then dynamically adapt their behavior in response to changing environmental conditions. The uncertainty of the execution environment is a major motivation for dynamic adaptation; it is impossible to know at development time all of the possible combinations of environmental conditions that will be encountered. To date, the work performed in requirements engineering for a DAS includes requirements monitoring and reasoning about the correctness of adaptations, where the DAS requirements are assumed to exist. This paper introduces a goal-based modeling approach to develop the requirements for a DAS, while explicitly factoring uncertainty into the process and resulting requirements. We introduce a variation of threat modeling to identify sources of uncertainty and demonstrate how the RELAX specification language can be used to specify more flexible requirements within a goal model to handle the uncertainty. © 2009 Springer Berlin Heidelberg.

Supporting decision-making for self-adaptive systems:from goal models to dynamic decision networks

Context/Motivation - Different modeling techniques have been used to model requirements and decision-making of self-adaptive systems (SASs). Specifically, goal models have been prolific in supporting decision-making depending on partial and total fulfilment of functional (goals) and non-functional requirements (softgoals). Different goalrealization strategies can have different effects on softgoals which are specified with weighted contribution-links. The final decision about what strategy to use is based, among other reasons, on a utility function that takes into account the weighted sum of the different effects on softgoals. Questions/Problems - One of the main challenges about decisionmaking in self-adaptive systems is to deal with uncertainty during runtime. New techniques are needed to systematically revise the current model when empirical evidence becomes available from the deployment. Principal ideas/results - In this paper we enrich the decision-making supported by goal models by using Dynamic Decision Networks (DDNs). Goal realization strategies and their impact on softgoals have a correspondence with decision alternatives and conditional probabilities and expected utilities in the DDNs respectively. Our novel approach allows the specification of preferences over the softgoals and supports reasoning about partial satisfaction of softgoals using probabilities. We report results of the application of the approach on two different cases. Our early results suggest the decision-making process of SASs can be improved by using DDNs. © 2013 Springer-Verlag.

Software engineering for self-adaptive systems:a research roadmap

The goal of this roadmap paper is to summarize the state-of-the-art and to identify critical challenges for the systematic software engineering of self-adaptive systems. The paper is partitioned into four parts, one for each of the identified essential views of self-adaptation: modelling dimensions, requirements, engineering, and assurances. For each view, we present the state-of-the-art and the challenges that our community must address. This roadmap paper is a result of the Dagstuhl Seminar 08031 on "Software Engineering for Self-Adaptive Systems," which took place in January 2008. © 2009 Springer Berlin Heidelberg.

Requirements-aware systems:a research agenda for RE for self-adaptive systems

Requirements are sensitive to the context in which the system-to-be must operate. Where such context is well-understood and is static or evolves slowly, existing RE techniques can be made to work well. Increasingly, however, development projects are being challenged to build systems to operate in contexts that are volatile over short periods in ways that are imperfectly understood. Such systems need to be able to adapt to new environmental contexts dynamically, but the contextual uncertainty that demands this self-adaptive ability makes it hard to formulate, validate and manage their requirements. Different contexts may demand different requirements trade-offs. Unanticipated contexts may even lead to entirely new requirements. To help counter this uncertainty, we argue that requirements for self-adaptive systems should be run-time entities that can be reasoned over in order to understand the extent to which they are being satisfied and to support adaptation decisions that can take advantage of the systems' self-adaptive machinery. We take our inspiration from the fact that explicit, abstract representations of software architectures used to be considered design-time-only entities but computational reflection showed that architectural concerns could be represented at run-time too, helping systems to dynamically reconfigure themselves according to changing context. We propose to use analogous mechanisms to achieve requirements reflection. In this paper we discuss the ideas that support requirements reflection as a means to articulate some of the outstanding research challenges.

Run-time model evaluation for requirements model-driven self-adaptation

A self-adaptive system adjusts its configuration to tolerate changes in its operating environment. To date, requirements modeling methodologies for self-adaptive systems have necessitated analysis of all potential system configurations, and the circumstances under which each is to be adopted. We argue that, by explicitly capturing and modelling uncertainty in the operating environment, and by verifying and analysing this model at runtime, it is possible for a system to adapt to tolerate some conditions that were not fully considered at design time. We showcase in this paper our tools and research results. © 2012 IEEE.

Foreword:2nd workshop requirements@run.time

The 2nd edition of the Workshop requirements@run.time was held at the 19th International Conference on Requirements Engineering (RE 2011) in the city of Trento, Italy on the 30th of August 2011. It was organized by Nelly Bencomo, Emmanuel Letier, Jon Whittle, Anthony Finkelstein, and Kris Welsh. This foreword presents a digest of the discussions and presentations that took place during the workshop. © 2011 IEEE.

Run-time resolution of uncertainty

Requirements awareness should help optimize requirements satisfaction when factors that were uncertain at design time are resolved at runtime. We use the notion of claims to model assumptions that cannot be verified with confidence at design time. By monitoring claims at runtime, their veracity can be tested. If falsified, the effect of claim negation can be propagated to the system's goal model and an alternative means of goal realization selected automatically, allowing the dynamic adaptation of the system to the prevailing environmental context. © 2011 IEEE.

Foreword:first workshop requirements@run.time

The first edition of the Workshop requirements@run.time was held at the Eighteenth International Conference on Requirements Engineering (RE 2010) in the city of Sydney, NSW, Australia on the 28th of September 2010. It was organized by Pete Sawyer, Jon Whittle, Nelly Bencomo, Daniel Berry, and Anthony Finkelstein. This foreword presents a digest of the presentations and discussions that took place during the workshop. © 2010 IEEE.

Self-explanation in adaptive systems based on runtime goal-based models

The behaviour of self adaptive systems can be emergent, which means that the system’s behaviour may be seen as unexpected by its customers and its developers. Therefore, a self-adaptive system needs to garner confidence in its customers and it also needs to resolve any surprise on the part of the developer during testing and maintenance. We believe that these two functions can only be achieved if a self-adaptive system is also capable of self-explanation. We argue a self-adaptive system’s behaviour needs to be explained in terms of satisfaction of its requirements. Since self-adaptive system requirements may themselves be emergent, we propose the use of goal-based requirements models at runtime to offer self-explanation of how a system is meeting its requirements. We demonstrate the analysis of run-time requirements models to yield a self-explanation codified in a domain specific language, and discuss possible future work.

QuantUn:quantification of uncertainty for the reassessment of requirements

Self-adaptive systems (SASs) should be able to adapt to new environmental contexts dynamically. The uncertainty that demands this runtime self-adaptive capability makes it hard to formulate, validate and manage their requirements. QuantUn is part of our longer-term vision of requirements reflection, that is, the ability of a system to dynamically observe and reason about its own requirements. QuantUn's contribution to the achievement of this vision is the development of novel techniques to explicitly quantify uncertainty to support dynamic re-assessment of requirements and therefore improve decision-making for self-adaption. This short paper discusses the research gap we want to fill, present partial results and also the plan we propose to fill the gap.

Disentangle contextual and permanent individual motivations:an application to shopping behavior

Past studies resulted in conflicting definitions of consumer motivation. On the one hand, motivations are seen as the consumer’s characteristics that shape her general behavior (motivational trait). On the other hand, they are seen as contextual variables representing the reason why the individual is behaving specific to today’s context (motivational state). The objective of this research is to stress the difference between these two concepts and to understand the impact of each on consumer behavior. We applied our empirical study to shopping motivations; our results show a strong interaction between motivational trait and motivational state. Problem and Hypothesis On the one hand, Westbrook and Black (1985) consider shopping motivations as individual permanent characteristics. This concept is shared by other researchers (Rohm and Swaminathan 2004), which show that some shoppers are functional (they shop for convenience, information seeking, and time saving) while some others are hedonic (they shop for social interaction, bargain hunting and browsing). On the other hand, Kaltcheva and Weitz (2006) define motivations as a contextual orientation changing over time, depending on the situation, and show that contextual shopping motivations have a strong impact on shopping behavior. From our knowledge, no research specifically examined the respective impact of both these shopping motivation types. To deal with this issue, we used the notions of “traits” and “states” that have been largely used in marketing research to designate respectively a permanent characteristic of the individual and a temporary orientation of the consumer (Mowen 2000). The reversal theory (Apter 2001) suggests that two opposite states exist: the telic and the paratelic states. In the telic state, individuals set goals for themselves, must be disciplined to reach these goals, and do not behave in accordance with their personal trait. In the paratelic state, individuals are seeking arousal and enjoyment, do not set rules, and one could postulate that they act in accordance with their natural tendencies. Based on these considerations, we hypothesize the following process: in situations involving paratelic states, hedonic as well as functional individuals should behave according to their natural traits, whereas in situations involving telic states, hedonic people should inhibit their natural propensity to enjoy shopping and behave similarly to functional people. Hence, we postulate the following: Hypothesis: Compared to shoppers with functional motivational trait, shoppers with hedonic motivational trait will a) significantly display more hedonic shopping behavior intentions in a condition of paratelic motivational state, and b) not display more hedonic shopping behavior intentions in a condition a telic motivational state Empirical Research First, 108 participants were asked to fill a multi-items scale about their shopping habits, which actually measured their shopping motivational traits. This questionnaire allowed us to highlight four different dimensions in shopping motivational traits: social interaction, novelty/utility seeking, bargain hunting, and browsing. According to their scores on different items, participants were classified as functional or as hedonic on each of these four dimensions (a single individual may be hedonic on some dimensions and functional on others). Then, participants were then induced to adopt either a telic or a paratelic shopping motivational state while reading an appropriate scenario. Finally, participants were asked for their shopping behavior intentions in response to the shopping context. Four items were developed, corresponding to the four shopping motivational trait dimensions we found with our factor analysis. Results As we found four dimensions in shopping motivational trait, we set up four quasi-experimental designs to capture the entire phenomenon: for each dimension, a 2 (motivational trait) x 2 (motivational state) design was built, where the dependant variable was the shopping behavior element corresponding to the studied dimension. Four 2 x 2 Anovas were performed to assess the interaction between motivational trait and motivational state. Concerning the three dimensions - browsing, novelty/utility seeking, and bargain hunting- , in the paratelic state scenario participants with hedonic motivational trait displayed significantly more hedonic shopping behavior intentions than participants with a functional motivational trait (resp. F = 9.701, p = .003; F = 4.979, p = .03; F = 5.757, p = .02); and in the telic state scenario, there was no significant difference in behavior intentions between participants with hedonic or functional motivation trait. Each time, the interaction effect between motivational state and motivational trait was significant (resp. F = 4.859, p = .03; F = 3.314, p = .07; F = 2.98, p = .08). Concerning the fourth dimension, social interaction, shopping behavior intentions of participants with hedonic and with functional motivational traits were significantly different in the paratelic state scenario (F = 29.898, p <.000) as well as in the telic state scenario (F = 9.559, p = .003). However, the interaction effect showed that this behavioral difference was significantly stronger in the paratelic scenario. All these results support our research hypothesis. Discussion and Implications Our study provides consistent support for our hypotheses saying that there is an interaction effect between shopping motivational states and shopping motivational traits. The generalization of the results is strengthened by the study of four different shopping traits: social interaction, novelty/utility seeking, bargain hunting and browsing. As we proposed, when shopping in a goal-oriented state (telic state), behaviors of hedonic and functional shoppers do not differ significantly. Conversely, when shopping for a recreational reason (paratelic state), hedonic and functional shoppers behave significantly different. These results could explain why some previous studies concluded that shopping motivational traits had no impact on shopping behavior: they did not take into consideration the interaction between motivational trait and motivational state. Moreover, our study shows that marketing surveys performed by store managers to draw the personal profile of their customers must be crossed with contextual motivations in order to accurately forecast shopper behavior. Future Developments Our results can be explained by the self-control process, which pushes hedonic-trait shoppers to behave in a rather functional way in utilitarian situations. However, to be certain that this is the very process that occurs, we plan to add self-control perception scales to our existing measures. This is obviously the next step of this research.

RELAX:a language to address uncertainty in self-adaptive systems requirement

Self-adaptive systems have the capability to autonomously modify their behavior at run-time in response to changes in their environment. Self-adaptation is particularly necessary for applications that must run continuously, even under adverse conditions and changing requirements; sample domains include automotive systems, telecommunications, and environmental monitoring systems. While a few techniques have been developed to support the monitoring and analysis of requirements for adaptive systems, limited attention has been paid to the actual creation and specification of requirements of self-adaptive systems. As a result, self-adaptivity is often constructed in an ad-hoc manner. In order to support the rigorous specification of adaptive systems requirements, this paper introduces RELAX, a new requirements language for self-adaptive systems that explicitly addresses uncertainty inherent in adaptive systems. We present the formal semantics for RELAX in terms of fuzzy logic, thus enabling a rigorous treatment of requirements that include uncertainty. RELAX enables developers to identify uncertainty in the requirements, thereby facilitating the design of systems that are, by definition, more flexible and amenable to adaptation in a systematic fashion. We illustrate the use of RELAX on smart home applications, including an adaptive assisted living system.