Supporting software maintenance with non-functional information

The paper highlights the role of non functional information (about efficiency, reliability and other software attributes) of software components in software maintenance, focusing in the component programming framework. Non functional information is encapsulated in modules bound to both definitions and implementations of software components and it is written as expressions in a classical programming language. It is shown with an example how this notation supports software maintenance, with the help of an algorithm which is able to select the best implementation of a software component in its context of use, meaning byPeer ReviewedPostprint (published version

Stakeholder identification in the requirements engineering process

Adequate, timely and effective consultation of relevant stakeholders is of paramount importance in the requirements engineering process. However, the thorny issue of making sure that all relevant stakeholders are consulted has received less attention than other areas which depend on it, such as scenario-based requirements, involving users in development, negotiating between different viewpoints and so on. The literature suggests examples of stakeholders, and categories of stakeholder, but does not provide help in identifying stakeholders for a specific system. In this paper, we discuss current work in stakeholder identification, propose an approach to identifying relevant stakeholders for a specific system, and propose future directions for the work

Integrated Photonic Sensing

Loss is a critical roadblock to achieving photonic quantum-enhanced technologies. We explore a modular platform for implementing integrated photonics experiments and consider the effects of loss at different stages of these experiments, including state preparation, manipulation and measurement. We frame our discussion mainly in the context of quantum sensing and focus particularly on the use of loss-tolerant Holland-Burnett states for optical phase estimation. In particular, we discuss spontaneous four-wave mixing in standard birefringent fibre as a source of pure, heralded single photons and present methods of optimising such sources. We also outline a route to programmable circuits which allow the control of photonic interactions even in the presence of fabrication imperfections and describe a ratiometric characterisation method for beam splitters which allows the characterisation of complex circuits without the need for full process tomography. Finally, we present a framework for performing state tomography on heralded states using lossy measurement devices. This is motivated by a calculation of the effects of fabrication imperfections on precision measurement using Holland-Burnett states.Comment: 19 pages, 7 figure

Engineering simulations for cancer systems biology

Computer simulation can be used to inform in vivo and in vitro experimentation, enabling rapid, low-cost hypothesis generation and directing experimental design in order to test those hypotheses. In this way, in silico models become a scientific instrument for investigation, and so should be developed to high standards, be carefully calibrated and their findings presented in such that they may be reproduced. Here, we outline a framework that supports developing simulations as scientific instruments, and we select cancer systems biology as an exemplar domain, with a particular focus on cellular signalling models. We consider the challenges of lack of data, incomplete knowledge and modelling in the context of a rapidly changing knowledge base. Our framework comprises a process to clearly separate scientific and engineering concerns in model and simulation development, and an argumentation approach to documenting models for rigorous way of recording assumptions and knowledge gaps. We propose interactive, dynamic visualisation tools to enable the biological community to interact with cellular signalling models directly for experimental design. There is a mismatch in scale between these cellular models and tissue structures that are affected by tumours, and bridging this gap requires substantial computational resource. We present concurrent programming as a technology to link scales without losing important details through model simplification. We discuss the value of combining this technology, interactive visualisation, argumentation and model separation to support development of multi-scale models that represent biologically plausible cells arranged in biologically plausible structures that model cell behaviour, interactions and response to therapeutic interventions

Content-based Video Retrieval

no abstract

Case Studies in Industry: What We Have Learnt

Case study research has become an important research methodology for exploring phenomena in their natural contexts. Case studies have earned a distinct role in the empirical analysis of software engineering phenomena which are difficult to capture in isolation. Such phenomena often appear in the context of methods and development processes for which it is difficult to run large, controlled experiments as they usually have to reduce the scale in several respects and, hence, are detached from the reality of industrial software development. The other side of the medal is that the realistic socio-economic environments where we conduct case studies -- with real-life cases and realistic conditions -- also pose a plethora of practical challenges to planning and conducting case studies. In this experience report, we discuss such practical challenges and the lessons we learnt in conducting case studies in industry. Our goal is to help especially inexperienced researchers facing their first case studies in industry by increasing their awareness for typical obstacles they might face and practical ways to deal with those obstacles.Comment: Proceedings of the 4th International Workshop on Conducting Empirical Studies in Industry, co-located with ICSE, 201

Identifying the time profile of everyday activities in the home using smart meter data

Activities are a descriptive term for the common ways households spend their time. Examples include cooking, doing laundry, or socialising. Smart meter data can be used to generate time profiles of activities that are meaningful to households’ own lived experience. Activities are therefore a lens through which energy feedback to households can be made salient and understandable. This paper demonstrates a multi-step methodology for inferring hourly time profiles of ten household activities using smart meter data, supplemented by individual appliance plug monitors and environmental sensors. First, household interviews, video ethnography, and technology surveys are used to identify appliances and devices in the home, and their roles in specific activities. Second, ‘ontologies’ are developed to map out the relationships between activities and technologies in the home. One or more technologies may indicate the occurrence of certain activities. Third, data from smart meters, plug monitors and sensor data are collected. Smart meter data measuring aggregate electricity use are disaggregated and processed together with the plug monitor and sensor data to identify when and for how long different activities are occurring. Sensor data are particularly useful for activities that are not always associated with an energy-using device. Fourth, the ontologies are applied to the disaggregated data to make inferences on hourly time profiles of ten everyday activities. These include washing, doing laundry, watching TV (reliably inferred), and cleaning, socialising, working (inferred with uncertainties). Fifth, activity time diaries and structured interviews are used to validate both the ontologies and the inferred activity time profiles. Two case study homes are used to illustrate the methodology using data collected as part of a UK trial of smart home technologies. The methodology is demonstrated to produce reliable time profiles of a range of domestic activities that are meaningful to households. The methodology also emphasises the value of integrating coded interview and video ethnography data into both the development of the activity inference process

Assessing digital preservation frameworks: the approach of the SHAMAN project

How can we deliver infrastructure capable of supporting the preservation of digital objects, as well as the services that can be applied to those digital objects, in ways that future unknown systems will understand? A critical problem in developing systems is the process of validating whether the delivered solution effectively reflects the validated requirements. This is a challenge also for the EU-funded SHAMAN project, which aims to develop an integrated preservation framework using grid-technologies for distributed networks of digital preservation systems, for managing the storage, access, presentation, and manipulation of digital objects over time. Recognising this, the project team ensured that alongside the user requirements an assessment framework was developed. This paper presents the assessment of the SHAMAN demonstrators for the memory institution, industrial design and engineering and eScience domains, from the point of view of user’s needs and fitness for purpose. An innovative synergistic use of TRAC criteria, DRAMBORA risk registry and mitigation strategies, iRODS rules and information system models requirements has been designed, with the underlying goal to define associated policies, rules and state information, and make them wherever possible machine-encodable and enforceable. The described assessment framework can be valuable not only for the implementers of this project preservation framework, but for the wider digital preservation community, because it provides a holistic approach to assessing and validating the preservation of digital libraries, digital repositories and data centres