Dave Towey

• PhD
• Professor (Full) at University of Nottingham Ningbo China

Metamorphic testing (MT) is an effective software quality assurance method; it uses metamorphic relations (MRs) to examine the inputs and outputs of multiple test cases. Metamorphic exploration (ME) and metamorphic robustness testing (MRT) are advanced additions to the MT literature: ME can enable better understanding, and thus testing, of systems;...

Although Convolutional Neural Networks (CNNs) have achieved remarkable success in image classification, most CNNs use image datasets in the Red-Green-Blue (RGB) color space (one of the most commonly used color spaces). The existing literature regarding the influence of color space use on the performance of CNNs is limited. This paper explores the i...

The rapid changes in technology available for teaching and learning have led to a wide variety of potential tools that can be deployed to support a student's education experience. This paper examines the learning interfaces for pedagogical virtual reality (VR) environments, including immersive VR (iVR). It also looks at how microlearning (ML) can b...

As one of the most popular software applications, a web application is a program, accessible through the web, to dynamically generate content based on user interactions or contextual data, for example, online shopping platforms, social networking sites, and financial services. Web applications operate in diverse environments and leverage web techno...

Metamorphic testing has become one mainstream technique to address the notorious oracle problem in software testing, thanks to its great successes in revealing real-life bugs in a wide variety of software systems. Metamorphic relations, the core component of metamorphic testing, have continuously attracted research interests from both academia and...

Metamorphic testing (MT) is effective in detecting software failures; it detects failures by examining the metamorphic relations (MRs) among source test cases (STCs), follow‐up test cases (FTCs) and their respective outputs. The STCs together with the corresponding FTCs, considered as a whole, are called metamorphic groups (MGs). MT performance rel...

The interaction between Ribonucleic Acids (RNAs) and proteins, also called RNA Protein Interaction (RPI), plays an important role in the life activities of organisms, including in various regulatory processes, such as gene splicing, gene localization, and disease pathogenesis. RPI Prediction (RPIP) predicts the interactions between RNAs and protein...

When selecting services from a cloud center to build applications, the quality of service (QoS) is an important nonfunctional attribute to be considered. However, in actual application scenarios, the QoS details for many services may not be available. This has led to a situation where prediction of the missing QoS records for services has become a...

This paper explores the educational and practical impacts of integrating metamorphic testing (MT) into a software engineering project conducted by an intercultural group of students. The students designed a Steer-by-Wire (SBW) system to control the steering of a model vehicle and tested using a hybrid approach that combined unit testing and MT. Fou...

Short-Term Electricity-Load Forecasting (STELF) refers to the prediction of the immediate demand (in the next few hours to several days) for the power system. Various external factors, such as weather changes and the emergence of new electricity consumption scenarios, can impact electricity demand, causing load data to fluctuate and become non-line...

Software developers can only obtain a very small amount of information from the individual failure-causing inputs, which makes debugging difficult. Therefore, it is necessary to explore additional failure-causing inputs (failure regions) using the known failure-causing inputs. In order to accurately and efficiently identify the failure region, we p...

Purpose This study aims to examine the effects on student motivation and perception of technological interventions within undergraduate mechanical engineering and product design and manufacture programs at a Sino-foreign international university. The authors use an augmented reality game application within a class on Design for Manufacturing and As...

The proliferation of driver‐assistance features in vehicles has resulted in a growing interest among the public in fully autonomous driving systems (ADSs). However, the integration of software and hardware in these complex systems presents significant testing challenges, particularly with respect to ensuring passenger safety. To address these chall...

This study introduces a website serving as an Open Educational Resource (OER), dedicated to Metamorphic Testing (MT) and Metamorphic Relation (MR) generation, with a specific focus on Autonomous Driving Systems (ADSs). It offers a comprehensive introduction to MT and ADSs, and presents a specially designed scenario template that simplifies the MR g...

This paper presents a pilot study that examines the capacity of novice testers to generate Metamorphic Relations (MRs) for autonomous driving systems (ADSs), specifically fo-cusing on parking functions. By comparing MRs generated by human participants with those generated by artificial intelligence (AI), we seek to understand the variances in quali...

Metamorphic testing has become one mainstream technique to address the notorious oracle problem in software testing, thanks to its great successes in revealing real-life bugs in a wide variety of software systems. Metamorphic relations, the core component of metamorphic testing, have continuously attracted research interests from both academia and...

Low-contrast medical image segmentation is a challenging task that requires full use of local details and global context. However, existing convolutional neural networks (CNNs) cannot fully exploit global information due to limited receptive fields and local weight sharing. On the other hand, the transformer effectively establishes long-range depen...

Artificial intelligence (AI) has revolutionized software engineering (SE) by enhancing software development efficiency. The advent of pre-trained models (PTMs) leveraging transfer learning has significantly advanced AI for SE. However, existing PTMs that operate on individual code tokens suffer from several limitations: They are costly to train and...

Although many of today's object detectors (ODs) are fairly powerful and advanced, most of them still suffer from high detection failure rates. To address this issue, we have developed an innovative, multiple-object detection validation method using a complex-network-community-based relevance metric. This metric aims to measure the relevance of mult...

The testing of web forms is an essential activity for ensuring the quality of web applications, which mainly involves evaluating the interactions between users and forms. Automated test-case generation remains a challenge for web-form testing: Due to the complex, multi-level structure of web pages, it can be difficult to automatically capture their...

italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Adaptive Random Testing (ART) enhances the testing effectiveness (including fault-detection capability) of Random Testing (RT) by increasing the diversity of the random test cases throughout the input domain. Many ART algorithms have been investigate...

Future airspace is expected to become more congested with additional in-service cargo and commercial flights. Pilots will face additional burdens in such an environment, given the increasing number of factors that they must simultaneously consider while completing their work activities. Therefore, care and attention must be paid to the mental workl...

The recent release of the Apple Vision Pro has reignited interest in the metaverse, showcasing the intensified efforts of technology giants in developing platforms and devices to facilitate its growth. As the metaverse continues to proliferate, it is foreseeable that everyday environments will become increasingly saturated with its presence. Conseq...

Distributed systems have been widely used in many safety‐critical areas. Any abnormalities (e.g., service interruption or service quality degradation) could lead to application crashes or decrease user satisfaction. These things may cause serious economic losses. Among the various quality assurance approaches for distributed systems, log‐based anom...

Purpose Currently, owners find it difficult to manage their assets throughout their project life cycle. The fact that asset information models (AIMs) are mandatory as deliverables for building information modeling-driven projects makes it a key requirement for the client to understand in detail those factors affecting asset operation. Hence, becaus...

Software quality evaluation is a challenging task in software engineering. A new group decision-making evaluation model is presented in this work. The new model is based on the Vlsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) technique, in which a group regret measurement and a group satisfaction measurement are provided to increase the...

Robust and accurate segmentation for elongated physiological structures is challenging, especially in the ambiguous region, such as the corneal endothelium microscope image with uneven illumination or the fundus image with disease interference. In this paper, we present a spatial and scale uncertainty-aware network (SSU-Net) that fully uses both sp...

The segmentation of blurred cell boundaries in cornea endothelium microscope images is challenging, which affects the clinical parameter estimation accuracy. Existing deep learning methods only consider pixel-wise classification accuracy and lack of utilization of cell structure knowledge. Therefore, the segmentation of the blurred cell boundary is...

This chapter examines the current use of innovative learning approaches (such as microlearning, gamification, and immersive learning) for design and engineering education in the Bachelor of Engineering in Product Design and Manufacture (PDM) programme at University of Nottingham Ningbo China, an English Medium Instruction Sino-foreign Higher Educat...

The COVID-19 pandemic of 2020–2023 caught many teachers unprepared for remote and hybrid learning; as educators, we had to quickly adapt our teaching methods to the new context. The lessons learned remain relevant as the pandemic fades into history. We have also recognized that our software-engineering (SE) experience and skills (including working...

This paper reports on a pilot study of using ChatGPT, a language model based on GPT-3.5 architecture, for automatic generation of metamorphic relations (MRs), in the context of testing of autonomous driving systems (ADSs). The oracle problem is a major challenge in testing such systems, where it is difficult to determine whether or not the output o...

Robust and accurate segmentation for elongated physiological structures is challenging, especially in the ambiguous region, such as the corneal endothelium microscope image with uneven illumination or the fundus image with disease interference. In this paper, we present a spatial and scale uncertainty-aware network (SSU-Net) that fully uses both sp...

Adaptive Random Testing (ART) enhances the testing effectiveness (including fault-detection capability) of Random Testing (RT) by increasing the diversity of the random test cases throughout the input domain. Many ART algorithms have been investigated according to different criteria, such as Fixed-Size-Candidate-Set ART (FSCS) and Restricted Random...

As the complexity of autonomous driving systems (ADSs) increases, the question of how to organize testing in an efficient manner has become a serious issue. This study investi- gates the potential for metamorphic testing (MT) to evaluate the perception-camera module of an open-source autonomous driving system (ADS), namely Baidu’s Apollo ADS. The e...

The recent COVID-19 pandemic has put additional demands on Higher Education institutions around the globe. In January 2020, universities in China were forced to plan for Emergency Remote Teaching (ERT). Many Sino-foreign institutions responded in a proactive way seeing this difficult situation as an opportunity to transform their teaching and learn...

Context Simulation-based testing is essential when developing Advanced Driver-Assistance Systems (ADASs) and autonomous driving (AD) systems, producing fast, high-quality test results, at relatively low cost. However, simulation testing relies on the quality of the ADAS simulation platform: If the simulation platform is faulty, then the simulation...

Purpose-Drawing on the traditions of autoethnography and reflective practice, this paper explores the experiences and reflections of one of the longest serving foreign academics in China's Sino-foreign Higher Education (SfHE) system. He started out at UIC (United International College, a collaboration between Beijing Normal University and Hong Kong...

Purpose-Undergraduate Computer Science (CS) students participate in multiple project-based classes throughout their studies. In our context, the two most significant of these are the optional final year project dissertation, and the compulsory penultimate-year team-based software engineering project. These projects can require levels of independent...

Purpose-University of Nottingham Ningbo China (UNNC) was the first Sino-foreign higher education institution established in China. As a pioneering institution for innovation, UNNC aims to develop engaging pedagogy to stimulate and motivate students. One of these innovations is the virtual reality (VR) Design Movements (DM) experience developed by V...

Delivering high-quality, timely and formative feedback for students’ code-based coursework submissions is a problem faced by Computer Science (CS) educators. Automated Feedback Systems (AFSs) can provide immediate feedback on students’ work, without requiring students to be physically present in the classroom—an increasingly important consideration...

Test case prioritization (TCP) aims at scheduling test case execution so that more important test cases are executed as early as possible. Many TCP techniques have been proposed, according to different concepts and principles, with dissimilarity-based TCP (DTCP) prioritizing tests based on the concept of test case dissimilarity: DTCP chooses the ne...

For universities, COVID-19 made traditional means of providing quality teaching and learning impossible. Nevertheless, students required delivery and assessment to progress or graduate on time. Subjects in Science and Engineering with practical components presented a particular challenge, and this paper assesses institutional means and the perspect...

italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Adaptive random testing (ART) is an enhancement of random testing (RT), and aims to improve the RT failure-detection effectiveness by distributing test cases more evenly in the input domain. Many ART algorithms have been proposed, with fixed-size-ca...

Interdisciplinarity is widely regarded as the future ofIndustry 4.0. It is at the core of the knowledge economy and is key to solving complex real-world problems. Contemporary education therefore must provide students with the skills and understanding to engage in interdisciplinary studies. This paper explores the experiences, attitudes and motivat...

Adaptive Random Testing (ART) is a family of testing techniques that were proposed as an enhancement of random testing (RT). ART achieves better failure-detection capability than RT by more evenly distributing test cases throughout the input domain. However, this process of selecting more diverse test cases incurs a heavy computational cost. In thi...

This paper presents an automated, domain-independent, metamorphic testing platform called MTKeras. In this paper, we report on an investigation demonstrating the effectiveness and usability of MTKeras through five case studies in the four domains of image classification, sentiment analysis, search engines and database management systems. We also re...

Software testing is often hindered where it is impossible or impractical to determine the correctness of the behaviour or output of the software under test (SUT), a situation known as the oracle problem. An example of an area facing the oracle problem is automatic image classification, using machine learning to classify an input image as one of a s...

Software testing is often hindered where it is impossible or impractical to determine the correctness of the behaviour or output of the software under test (SUT), a situation known as the oracle problem. An example of an area facing the oracle problem is automatic image classification, using machine learning to classify an input image as one of a s...

Information is indispensable in modern society. People's daily communication and work depend on information transmission. Unsafe storage or transmission of data may result in privacy and security problems. One way to attempt to prevent such issues is to use encryption algorithms to transform information into encrypted forms. Because the encryption...

Awareness of web accessibility issues is necessary for, amongst other things, good website design. Good website design can mean the difference between disabled users being able to access the website content, or not. This paper describes the impact of a student-led project to develop a VR application, as an Open Education Resource (OER), to increase...

Since the popularization of social media, news has entered our lives digitally. While news is spreading broader and faster, fake news is becoming an increasingly popular topic. Fake news detection is therefore important in both social media and research areas. With artificial intelligence technology, software engineers have developed a lot of fake...

In today's digital era, the number of digital artefacts produced by students in universities around the world continues to rise. This paper describes a project that developed a digital artefacts platform to showcase students' projects at an international level, aiming to increase the visibility of students' work to global audiences. Due to the COVI...

Purpose – This paper reports on experiences at the start of a Software Engineering (SE) PhD, where the candidate encountered and overcame multiple challenges setting up his research environment, which included online learning (and supervision) elements. When preparing a replication study, the candidate faced both hardware and software problems as h...

Purpose-Computer Science (CS) has been rapidly growing in popularity, partly due to the great growth of big data (BD) and other new technologies, and the services that support them. BD involves data sets that are too large to be captured, curated, analyzed, or processed (for an acceptable time and cost) using traditional CS techniques. Although BD...

Purpose-The Sino-foreign Higher Education Institutions (SfHEIs) in the People's Republic of China (PRC) grew as an innovative response to a (then) pressing PRC education problem-providing sufficiently high quality and quantity higher education (HE) opportunities. These SFHEIs have also been centres of innovation, with many exciting initiatives bein...

Purpose-Delivering high-quality, timely and formative feedback for students' code-based coursework submissions is a problem faced by Computer Science (CS) educators. Automated Feedback Systems (AFSs) can provide immediate feedback on students' work, without requiring students to be physically present in the classroom-an increasingly important consi...

Purpose-The COVID-19 pandemic has caused enormous pain and suffering, with the impact on health and daily life having been catastrophic. Industry and professions have been severely impacted, with many seeing widespread redundancy and closures. Although there have been silver linings-in the shape of resilience and adaptations, for example-the disrup...

The recent COVID-19 pandemic has presented challenges to post-secondary education, including that campuses have been closed, removing face-to-face instruction options. Meanwhile, this crisis has also presented unique opportunities to create a “tipping point” or conditions that foster innovative teaching practices. In light of such a “danger-opportu...

COVID-19 has caused heart-break and disruption. The People's Republic of China (PRC) was one of the first severely-impacted countries, but also one of the first to attempt to return to normalcy. Education, including Higher Education-the context of this paper-was disrupted, and the impact of these disruptions continues to be felt. A small consolatio...

As an enhanced version of Random Testing (RT), Adaptive Random Testing (ART) aims to improve the failure detection effectiveness of RT by distributing the test cases more evenly in the input domain. Many ART algorithms have been proposed based on different criteria. Among them, the Fixed-Size-Candidate-Set ART (FSCS-ART) is one of the most effectiv...

Adaptive random testing (ART) improves the failure-detection effectiveness of random testing by leveraging properties of the clustering of failure-causing inputs of most faulty programs: ART uses a sampling mechanism that evenly spreads test cases within a software’s input domain. The widely-used Fixed-Sized-Candidate-Set ART (FSCS-ART) sampling st...

Cloud services have become a popular and flexible solution for providing components to build service-based systems. A component’s trustworthiness is a key measure that can guide service requesters when making a service selection decision. Prediction of this trustworthiness, based on the component’s multi-faceted quality of service (QoS) attributes,...