Mohamed Abdelrazek

A domain-specific visual modeling language for testing environment emulation

Software integration testing plays an increasingly important role as the software industry has experienced a major change from isolated applications to highly distributed computing environments. Conducting integration testing is a challenging task because it is often very difficult to replicate a real enterprise environment. Emulating testing environment is one of the key solutions to this problem. However, existing specification-based emulation techniques require manual coding of their message processing engines, therefore incurring high development cost. In this paper, we present a suite of domain-specific visual modeling languages to describe emulated testing enviroements at a high abstraction level. Our solution allows domain experts to model a testing environment from abstract interface layers. These layer models are then transformed to runtime environment for application testing. Our user study shows that our visual languages are easy to use, yet with sufficient expressive power to model complex testing applications.

Visualising melbourne pedestrian count

We present a visualisation of Melbourne pedestrian count data and a visual metaphor for representing hour-level temporal dimension in this context. The pedestrian count data is captured from sensors located around the city. A visualisation web application is implemented that incorporates a thematic map of these sensor locations with a 24-hour clocklike polygon that shows pedestrian counts at every hour, and alongside a display of daily temperature. Our visualisation allows users to analyse how the city is used by pedestrians. Moreover, the design of our visualisation was driven by the type of analysis tasks carried out by city planners. The visualisation would help city planners better understand the dynamics of pedestrian activity within the city and aid them in urban management and design policy recommendation.

Supporting diverse challenges of ageing with digital enhanced living solutions

By the 2050, it is estimated that the proportion of people over the age of 80 will have risen from 3.9% to 9.1% of population of Organisation for Economic Cooperation and Development countries. A large proportion of these people will need significant help to manage various chronic illnesses, including dementia, heart disease, diabetes, limited physical movement and many others. Current approaches typically focus on acute episodes of illness and are not well designed to provide adequately for daily living care support. In our rapidly ageing society, a critical need exists for effective, affordable, scalable and safe in-home and in-residential care solutions leveraging a range of current and emerging sensor, interaction and integration technologies. Key aims are to support the ageing to live longer in their own homes; make daily challenges associated with ageing less limiting through use of technology supports; better support carers - both professional and family - in providing monitoring, proactive intervention, and community connectedness; enable in-home and in-residential care organisations to scale their support services and better use their workforces; and ultimately provide better quality of life. Deakin University researchers have been investigating a range of emerging technologies and platforms to realise this vision, which we in broad terms coin Digital Enhanced Living, in the ageing space but also supporting those with anxiety and depression, sleep disorders, various chronic diseases, recovery from injury, and various predictive analytics. A Smart Home solution, carried out in conjunction with a local start-up, has produced and trialled a novel sensor, interaction, and AI-based technology. Virtual Reality (VR) solutions have been used to support carers in the set-up of dementia-friendly homes, in conjunction with Alzheimers Australia. Activity and nutrition solutions, including the use of conversational agents, have been used to build dialogue to engage and change behaviour. Predictive analytics, in conjunction with major hospitals, have been applied to large medical datasets to better support professionals making judgements around discharge outcomes. A set of lessons have been learned from the design, deployment and trialing of these diverse solutions and new development approaches have been crafted to address the challenges faced. In particular, we found that there is a need to consider user emotional expectations as first-class citizens and create methodologies that consider the user needs during the creation of the software solutions. We find that quality and emotional aspects have to be engineered into the solution, rather than added after a technical solution is deployed.

Testing Environment Emulation - A Model-based Approach.

Modern enterprise software systems often need to interact with a large number of distributed and heterogeneous systems. As a result, integration testing has become a critical step in their software development lifecycle. Service virtualization is an emerging technique for creating testing environments with realistic executable models of server side production-like behaviours. However, building models in existing service virtualization approaches is very challenging, requiring either significant human effort or the availability of interactive tracing records. In this paper, we present a domain-specific modeling approach to generate complex, virtualized testing environments. Our approach allows domain experts to use a suite of domain-specific visual modeling languages to model key interface layers of applications at a high level of abstraction. These layered models are then transformed into a testing runtime environment for applicationion. These layered models are then transformed into a testing runtime environment for application integration testing. We have conducted a technical comparison with two other existing approaches and also carried out a user study. The user study demonstrated the acceptance of our new testing environment emulation approach from software testing experts and developers.

Technical debt interest assessment: from issues to project

The interest of Technical Debt (TD) is difficult to calculate, especially on a project level. Current approaches are based on fine-grain issue assessment, but there is no evidence about how TD is assessed on a project level. A few tools use an aggregation function that sum the TD issues on a project level. We conducted a multiple case-study on four different projects. We asked the project teams to assess the TD both on an issue level and on a project level. We also asked the product manager and a senior developer to assess the TD on a project level. We found that the function mapping the interest of TD to a project overall is not the sum of issue-level TD. We report the quantitative results of the performed experiment and we also developed a qualitative explanation of the results based on interviews with the development team. This paper represents a first step towards assessing the interest of TD at a project level.

Adaptive Security for Software Systems

With continuously changing operational and business needs, system security is one of the key system capabilities that need to be updated as well. Most security engineering efforts focus on engineering security requirements of software systems at design time and existing adaptive security engineering efforts require complex design-time preparation. In this chapter we discuss the needs for adaptive software security, and key efforts in this area. We then introduce a new runtime adaptive security engineering approach, which enables adapting software security capabilities at runtime based on new security objectives, risks/threats, requirements as well as newly reported vulnerabilities. We categorize the source of adaptation in terms of manual adaptation (managed by end users), and automated adaption (automatically triggered by the platform). The new platform makes use of new ideas we built for vulnerability analysis, security engineering using aspect-oriented programming, and model-driven engineering techniques.

PedaViz: Visualising Hour-Level Pedestrian Activity

Effective visualisation plays a vital role in generating insights from data. The selection of graph types however, is highly dependent on the analysis tasks and data types at hand. For example, spatio-temporal visualisations encode changes in data over time and space. Although they have the potential of revealing overall tendencies and movement patterns, building effective spatio-temporal visualisations is challenging because it requires encoding all three attributes of spatio-temporal data i.e. thematic (values of attributes), temporal and spatial in a single visualisation. In this application design study, we present PedaViz for representing hour-level spatio-temporal attributes within a single visualisation; a 24-hour radial visual metaphor that encodes hour-level temporal and daily temperature attributes while utilising a thematic map display to present spatial attributes. The design was applied on city planning domain using Melbournes pedestrian count and temperature data. Results of our preliminary user evaluation suggest that our visualisation is easily understandable by users; and supports users in carrying out selected analysis tasks.

Vision: mobile ehealth learning and intervention platform

Face-to-face health educational and intervention programs are helpful in addressing mental and physical illness challenges in focused groups. However, these programs are expensive, resource-intensive and struggle with scalability and reachability, leading to limited take-up and short-term impact. Digital Health Intervention (DHI) programs incorporate the use of technology - mobile, web, wearables, virtual and augmented reality - to address these limitations while being more cost-effective. DHIs have shown major success in improving physical and mental health outcomes for the general public as well as reducing adverse outcomes or high-risk groups. However, it is still very challenging and expensive to design and run high quality mobile-based DHI programs, in part due to the lack of technical skills of researchers in this field. Our proposed mobile eHealth Learning and Intervention Platform (eHeLP) aims to address these challenges with a novel approach that allows health researchers to focus on their studies, and participants to have access to multiple health programs that meet their needs. The platform caters for identified stakeholders in the DHI field and encourages the development of a new health-tech industry. We present our vision eHeLP, why this idea is worth further research, risks we perceive, and next steps.

Understanding the Impact of Emotions on Software: A Case Study in Requirements Gathering and Evaluation

Abstract Smart home technology has received growing interest in recent years with a focus on automation and assistance, for example, Alexa, Google Home, Apple HomePod, and many cheap IoT devices. Better supporting elderly people to continue live in their home using smart home technology is a key target application. However, most of the existing smart home solutions for the elderly are not designed with people’s emotional goals in mind, leading to lack of adoption, lack of engagement, and failure of the technology. In this paper, we introduce an emotion-oriented requirements engineering approach to help identifying, modeling and evaluating emotional goals. We also explain how we used this technique to help us develop SofiHub - a new smart home platform for elderly people. SofiHub comprises a range of devices and software for sensing, interaction, passive monitoring, and emergency assistance. We have conducted multiple trials including initial field trials for elderly people in real houses. We have used our emotion-oriented requirements techniques to evaluate the participants’ emotional reactions before, during, and after trials to understand the impact of such technology on elderly people’s emotions to the SofiHub solution. Our analysis shows that SofiHub successfully alleviates their loneliness, makes them feel safer and cared about. We also found that the trial participants developed a strong relation with the system and hence, felt frustrated when SofiHub did not respond in ways expected or desired. We reflect on the lessons learned from the trials related to our emotion-oriented design and evaluation experimental approach, including refining our set of evaluation tools.

Identifying Drawbacks in Malicious PDF Detectors.

Despite the continuous countermeasuring efforts, embedding malware in PDF documents and using it as a malware distribution mechanism is still a threat. This is due to its popularity as a document exchange format, the lack of user awareness of its dangers, as well as its ability to carry and execute malware. Several malicious PDF detection tools have been proposed by the academic community to address the PDF threat. All of which suffer some drawbacks that limit its utility. In this paper, we present the drawbacks of the current state of the art malicious PDF detectors. This was achieved by undertaking a survey of all recent malicious PDF detectors, followed by a comparative evaluation of the available tools. Our results show that Concept drifts is major drawback to the detectors, despite the fact that many detectors use machine learning approaches.