A survey of practical software adaptation techniques

Abstract: Software adaptation techniques appear in many disparate areas of research literature, and under many guises. This paper enables a clear and uniform understanding of the related research, in three ways. Firstly, it surveys a broad range of relevant research, describing and contrasting the approaches of each using a uniform terminological and conceptual vocabulary. Secondly, it identifies and discusses three commonly advocated principles within this work: component models, first-class connection and loose coupling. Thirdly, it identifies and compares the various modularisation strategies employed by the surveyed work

Acceptance and Use of a Virtual Learning Environment (VLE): Structural Equations Modeling of the Unified Theory of Acceptance and Use of Technology

UTAUT 2 is a model designed to be a starting point for investigating IT adoption and can be used to identify the factors that influence the intention to use it, as well as to be adopted by an organization. The main objective of this research is to validate the Unified Theory of Acceptance and Use of Technology (UTAUT2) model by applying the questionnaire to students of a university that has gone through the process of implementing a virtual learning environment. The method is the quantitative one, through the survey strategy. As for the time horizon of the survey, a transversal cut was chosen. The techniques and procedures adopted were the modeling of structural equations with partial least squares in the Smart-PLS 3 software. The instrument used in this article is an adaptation of the questionnaire of Venkatesh et al (2012). The results point to evidence of converging and descriminating validity. This research contributes to the Unified Theory of Technology Acceptance and Use (UTAUT) as it is applied in different environments, evidencing characteristics that may allow its generalization. Finally, in the practical scope, it is possible to use this tool to evaluate and plan the acceptance of a new technology in the organizational scope

Enabling Proactive Adaptation through Just-in-time Testing of Conversational Services

Service-based applications (SBAs) will increasingly be composed of third-party services available over the Internet. Reacting to failures of those third-party services by dynamically adapting the SBAs will become a key enabler for ensuring reliability. Determining when to adapt an SBA is especially challenging in the presence of conversational (aka. stateful) services. A conversational service might fail in the middle of an invocation sequence, in which case adapting the SBA might be costly; e.g., due to the necessary state transfer to an alternative service. In this paper we propose just-in-time testing of conversational services as a novel approach to detect potential problems and to proactively trigger adaptations, thereby preventing costly compensation activities. The approach is based on a framework for online testing and a formal test-generation method which guarantees functional correctness for conversational services. The applicability of the approach is discussed with respect to its underlying assumptions and its performance. The benefits of the approach are demonstrated using a realistic example

Taking time to understand: articulating relationships between technologies and organizations

Dynamic relationships between technologies and organizations are investigated through research on digital visualization technologies and their use in the construction sector. Theoretical work highlights mutual adaptation between technologies and organizations but does not explain instances of sustained, sudden, or increasing maladaptation. By focusing on the technological field, I draw attention to hierarchical structuring around inter-dependent levels of technology; technological priorities of diverse groups; power asymmetries and disjunctures between contexts of development and use. For complex technologies, such as digital technologies, I argue these field-level features explain why organizations peripheral to the field may experience difficulty using emerging technology

A formal approach for correct-by-construction system substitution

The substitution of a system with another one may occur in several situations like system adaptation, system failure management, system resilience, system reconfiguration, etc. It consists in replacing a running system by another one when given conditions hold. This contribution summarizes our proposal to define a formal setting for proving the correctness of system substitution. It relies on refinement and on the Event-B method.Comment: EDCC-2014, Student-Forum, System Substitution, state rRecovery, correct-bycorrection, Event-B, refinemen

Requirements for an Adaptive Multimedia Presentation System with Contextual Supplemental Support Media

Investigations into the requirements for a practical adaptive multimedia presentation system have led the writers to propose the use of a video segmentation process that provides contextual supplementary updates produced by users. Supplements consisting of tailored segments are dynamically inserted into previously stored material in response to questions from users. A proposal for the use of this technique is presented in the context of personalisation within a Virtual Learning Environment. During the investigation, a brief survey of advanced adaptive approaches revealed that adaptation may be enhanced by use of manually generated metadata, automated or semi-automated use of metadata by stored context dependent ontology hierarchies that describe the semantics of the learning domain. The use of neural networks or fuzzy logic filtering is a technique for future investigation. A prototype demonstrator is under construction

Next challenges for adaptive learning systems

Learning from evolving streaming data has become a 'hot' research topic in the last decade and many adaptive learning algorithms have been developed. This research was stimulated by rapidly growing amounts of industrial, transactional, sensor and other business data that arrives in real time and needs to be mined in real time. Under such circumstances, constant manual adjustment of models is in-efficient and with increasing amounts of data is becoming infeasible. Nevertheless, adaptive learning models are still rarely employed in business applications in practice. In the light of rapidly growing structurally rich 'big data', new generation of parallel computing solutions and cloud computing services as well as recent advances in portable computing devices, this article aims to identify the current key research directions to be taken to bring the adaptive learning closer to application needs. We identify six forthcoming challenges in designing and building adaptive learning (pre-diction) systems: making adaptive systems scalable, dealing with realistic data, improving usability and trust, integrat-ing expert knowledge, taking into account various application needs, and moving from adaptive algorithms towards adaptive tools. Those challenges are critical for the evolving stream settings, as the process of model building needs to be fully automated and continuous.</jats:p