Research projects

Autolink: Automated unobtrusive techniques for LINKing requirements and testing in agile software development (2022-2023)

oftware practitioners struggle with specifying requirements and testing, especially in agile development settings, where the short and frequent iterations motivate developers in taking shortcuts to allow for timely releases. A common outcome is low-quality software. Some researchers already cry out for an urgent need to change, arguing that the poor software quality nowadays is a sign of the "coming software apocalypse". As a concrete step toward high-software quality, the AUTOLINK project explores the synergies between requirements engineering and software testing and aims at their seemingly integration into agile contexts. Requirements engineering and software testing are currently two largely distinct communities; combining them is an important step to tackle software quality problems. AUTOLINK will propose techniques that assist practitioners in increasing the quality of their software by testing it against the requirements, in an unobtrusive manner and with low cost and effort.

Supported by: NWO.
Participating CS members: Tanja Vos.

FALCON: Formal Analysis of Legacy COde domaiNs (2021-2025)

Supported by: DARPA.
Participating CS members: Freek Verbeek.

QPED: Quality-focused Programming EDucation (2020-2022)

Software should function correctly, be maintained and, be robust. Unfortunately, this is far from reality. To remedy this, we need to redesign the curriculum for software engineering and general computer science studies, and put more focus on quality assurance and software testing early on. The Erasmus+ Project QPED (Quality-focused Programming Education) will create new course material and a toolkit to achieve this.

Supported by: Erasmus+.
Participating CS members: Harrie Passier, Tanja Vos.
project website

Luce: LLVM with formal memory Usage CErtificates (2020-??)

The Luce project is an investigation into how to automatically reason about memory corruption-related weird machines. To achieve this goal, we are exploring algorithmic techniques that, at compile-time, compute a class of memory corruption-related, unintended emergent behaviors that are formally proven accurate. While the term Luce is an acronym, standing for "LLVM with formal memory usage certificates", it is also Latin and Italian for light and is pronounced as such.

Supported by: DARPA.
Participating CS members: Freek Verbeek, Nico Naus.
project website

Active4Life; optimization of use and effects of eHealth (2019-2023)

This project focuses on the optimization of use and effects of already proven eHealth interventions meant to stimulate adults and the elderly (diseased and healthy) to have an active lifestyle. There is an explicit focus on vulnerable populations, such as people with low education, low digital and health skills as they are most deprived with regard to both their health as well as their physical activity. Researchers from the department of computer science develop and apply new machine learning methods to able to analyse 8 large-scale existing datasets from proven effective online interventions to determine which factors are relevant to increase physical activity among (healthy and diseased) adults.

Supported by: NWO ZonMw.
Participating CS members: Simone Tummers, Arjen Hommersom.

IVVES: Industrial-grade Verification and Validation of Evolving Systems (2019-2022)

The use of AI and complex, evolving systems (ES), i.e. systems that rapidly change, either due to fast iteration cycles in development or due to their capability to self-adapt and learn, will grow significantly in automation, computation and novel digital services. Targeting the challenges in verification and validation of AI and evolving systems, IVVES will systematically develop Artificial Intelligence approaches for robust and comprehensive, industrial-grade V&V of "embedded AI", i.e. machine-learning for control of complex, mission-critical evolving systems and services covering the major industrial domains in Europe.

Supported by: Eureka ITEA3.
Participating CS members: Olivia Rodríguez Valdés, Pekka Aho, Tanja Vos.
project website

Future-proofing File Carving (2018-2022)

Het reconstrueren van verwijderde bestanden, file carving, vormt een cruciaal onderdeel van digitaal forensisch werk, veelal betreffende kinderporno. De explosieve datagroei maakt file carving steeds tijdsintensiever en dus ongeschikter, waardoor bewijsmateriaal verborgen blijft. File carving is nog per device en per app apart opgezet resulterend in een aanzienlijke vertraging om telkens voor nieuwe apps file carving te ontwikkelen. Onderzocht gaat worden hoe door abstractie en generalisatie het app-specifieke deel zo klein mogelijk gemaakt kan worden. Spin-off zal een breed toepasbaar, modulair, onderhoudbaar en uitbreidbaar framework zijn met bijbehorende benchmark om de resultaten van nieuwe technieken met elkaar te kunnen vergelijken.

Supported by: NWO Lerarenbeurs.
Participating CS members: Vincent van der Meer, Hugo Jonker, Marko van Eekelen.

Making computers work harder (2019-2021)

Moderne computerhardware kan meerdere berekeningen gelijktijdig verwerken. Echter, moderne computersoftware is vaak gelimiteerd tot één berekening tegelijk. Om de resulterende processoronderbenutting te verlichten, ontwikkelt de onderzoeker innovatieve programmeer- en testtechnieken die het coördineren van gelijktijdige berekeningen versimpelen.

Supported by: NWO Veni.
Participating CS members: Sung-Shik Jongmans.

Cyberweerbaarheid in Limburg (2019-2021)

Digitalisering is ook voor de Limburgse MKB ondernemingen een steeds belangrijker onderdeel van hun bedrijfsvoering. Daarmee nemen hun kwetsbaarheden als gevolg van cybercriminaliteit toe, waarbij uit onderzoek van het Platform Veilig Ondernemen blijkt, dat het bewustzijn rond dit onderwerp nog zeer beperkt is. Het project Cyberweerbaarheid in Limburg wil dat veranderen door een actieve community tot stand te brengen waarin ondernemers en andere maatschappelijke organisaties zich kunnen informeren over cybersecurity, verbindingen kunnen leggen met andere bedrijven en ICT dienstverleners, inzicht krijgen in hun individuele situatie door weerbaarheidscans en zelfevaluaties, maar ook met e-learning modules zichzelf en hun medewerkers kunnen trainen.

Supported by: RVO.
Participating CS members: Hugo Jonker.
project website

IMPRESS: Improving Engagement of Students in Software Engineering Courses through Gamification (2018-2021)

While our society increasingly depends on software for more and more aspects of civic, commercial and social life, software engineers struggle to ensure that software achieves the necessary high quality this requires. Although the discipline of software engineering offers different techniques and strategies to ensure quality, programmers in practice are reluctant to engage with them, with detrimental effects on software quality. A root cause of this situation lies in how software developers are educated: Software engineering education generally tends to focus more on the creative aspects of design and coding, whereas the more laborious and less entertaining activities are neglected; this disengagement with software quality assurance techniques carries over to practice. We therefore need a fundamental change in how software engineering is taught and perceived. Tomorrow's software engineers need to be raised with an appreciation of software quality, and quality assurance techniques need to become a natural aspect of software development, rather than a niche topic. To achieve this attitudinal change, the IMPRESS project will explore the use of gamification, i.e., the application of game-design elements and game principles in non-gaming contexts, which has seen successful applications in other domains.

Supported by: Erasmus+.
Participating CS members: Tanja Vos, Stefano Schivo.
project website

Dagobert: Design, Application and Governance Of a Botnet dEtection and pRofiling sysTem (2018-2020)

The Dagobert-project aims at improving internet security. It addresses the fight against botnets, which are networks of computers infected with malicious software that subsequently can be controlled remotely by cybercriminals to perform malicious activities. Cybercrime due to botnets imposes a major threat with large economical and societal impact. The goal of the Dagobert-project is to develop and evaluate an automated system that accurately detects botnets at a national scale by real-time analysis of high-volume streams of real-life network traffic (in particular DNS) at internet infrastructure providers such as domain name registries and ISPs. We intend to achieve this by applying advanced machine learning and deep learning techniques on monitored network data to derive profiles of both known and unknown botnets. Besides these technical aspects, the Dagobert-project also looks into governance aspects when integrating and applying the botnet profiling and detection system in the operational environments of internet infrastructure providers. These governance aspects address how risk management and strategic processes in these organisations are impacted, what measures are required to handle this impact, and how law enforcement is involved.

Supported by: OU LIRS (Learning and Innovation in Resilient Systems); SURFnet, Tesorion, SIDN Labs.
Participating CS members: Harald Vranken, Hassan Alizadeh.
project website

Fearfighter 2018-2020

In dit project wordt een app ontwikkeld die burgers helpt om conclusies te trekken over de veiligheid in hun stad. FearFighter baseert zich op feiten en niet op de onjuiste indrukken en mythes die vaak het gevolg zijn van angst of onwetendheid. FearFighter is een project in het kader van het nieuwe OU onderzoeksprogramma 'De Veilige Stad: veiligheid in stedelijke omgevingen'.

Supported by: OU De Veilige Stad.
Participating CS members: Harald Vranken.

SERF: Structured Exercise Repository with Feedback (2018-2021)

De Open Universiteit (OU) en Technische Universiteit Eindhoven (TU/e) willen een open en online opgavenbank voor programmeeronderwijs in Java ontwikkelen. De opgavenbank is gestructureerd door middel van een voorkennisgraaf die het mogelijk maakt voor diverse onderwijsinstellingen de opgaven eenvoudig in te passen in hun huidige onderwijs. De leermaterialen worden ondersteund met tools voor het automatisch nakijken en het geven van directe feedback over de kwaliteit van de uitwerkingen van studenten.

Supported by: Ministry of OCW: Open en Online Onderwijs.
Participating CS members: Harrie Passier, Tanja Vos, Stefano Schivo.

Testomat (2017-2020)

Nowadays, quality software has come to mean "easy to adapt" because of the constant pressure to change. Consequently, modern software teams seek a delicate balance between two opposing forces: striving for reliability and striving for agility. The TESTOMAT project will support software teams to strike the right balance by increasing the development speed without sacrificing quality. The project will ultimately result in a Test Automation Improvement Model, which will define key improvement areas in test automation, with the focus on measurable improvement steps.

Supported by: ITEA3.
Participating CS members: Pekka Aho, Tanja Vos.
project website

Training for Smart Services (2018-2020)

Er is een groeiend tekort aan IT-personeel in de regio Vlaanderen - Nederland. Brightlands Smart Services Campus, Corda Campus, Fontys Hogeschool Eindhoven, Hogeschool PXL, Artesis Plantijn Hogeschool Antwerpen, Gemeente Heerlen, Open Universiteit en Zuyd Hogeschool brengen hierin verandering. Zij slaan de handen ineen en ontwikkelen samen met bedrijven in de regio een uniek traineeship.

Supported by: Interreg Vlaanderen-Nederland.
Participating CS members: Marko van Eekelen, Frank Tempelman.
project website

Open Maths - activating learning mathematics online (2018-2019)

Bèta-opleidingen zoals informatica en ingenieurswetenschappen vereisen een diep wiskundig inzicht en de juiste vaardigheden om problemen op te lossen. Het ontbreekt universitaire studenten echter vaak aan de juiste wiskundige kennis waardoor zij vaak kookboek-achtige recepten te gebruiken om problemen op te lossen. De wiskunde kennis die studenten tijdens hun opleiding opdoen zijn dan ook vaak niet geschikt voor hun latere loopbaan. Open Maths is een nieuwe verzameling van onderwijsmethoden. Het is gebaseerd op de meest recente onderzoeksresultaten uit de neurowetenschappen, psychologie en wiskundige didactiek en op wijdverspreide ervaringen in het onderwijs. Het project Het doel van het project is om deze onderzoeksresultaten innovatief te vertalen naar online onderwijs op universitair niveau. Het project omvat de ontwikkeling, het onderwijs en de evaluatie van een volledige cursus Open Maths aan de Open Universiteit. Het doel van deze (optionele) cursus is om studenten voor te bereiden op het leren van wiskunde. In het bijzonder zullen studenten aan het einde van de cursus in kennis hebben en in staat zijn om het echte wiskundige denken te waarderen en wiskundig te redeneren over logische stappen. En ook online middelen en softwarehulpmiddelen te gebruiken. De student is gestimuleerd om moeilijke onderwerpen te leren en herkent hoe wiskundige probleemoplossing samenwerking in teams kan ondersteunen. Samengevat is het doel: wiskunde open te stellen voor studenten en wiskunde open te stellen voor studenten.

Supported by: NWO Comenius Teaching Fellow.
Participating CS members: Greg Alpár.

Well-being of people in urban environments (2018-2019)

Informatici en psychologen van de Open Universiteit zijn een gezamenlijk onderzoek gestart met als uiteindelijk doel het welzijn van mensen in stedelijke omgevingen te verbeteren. Ze doen dat door enerzijds data te verzamelen over de omgeving en anderzijds te onderzoeken wat mensen van die omgeving vinden en hoe ze zich daarin voelen. Als je weet welke aspecten van een stedelijke omgeving het welzijn van mensen bevorderen, kun je gericht maatregelen nemen om hun welzijn te verbeteren.

Supported by: OU De Veilige Stad.
Participating CS members: Harald Vranken.

Simplifying multicore programming through familiarity-centricity (2017-2019)

Modern computing devices have processors with multiple processing cores, called multicore processors. Curiously, programming concepts used for multicore programming today were invented already decades ago, in a time when processors had only one core. These unsophisticated concepts make multicore programming complex and error-prone. As a result, the majority of software programmed today still uses only one core, leaving the remaining cores structurally underutilized. Such underutilization becomes increasingly problematic in the future (as numbers of cores will only increase), decelerating the technological progress that modern society has become accustomed to. Simplifying multicore programming therefore constitutes a major challenge for today's software industry, providing exciting research opportunities for computer scientists. In this Rubicon project, I aim to develop an innovative programming language to simplify multicore programming, built on a pivotal &emdash; recently discovered &emdash; design principle: familiarity-centricity.

Supported by: NWO Rubicon.
Participating CS members: Sung-Shik Jongmans.

Advise-Me: Automatic Diagnostics with Intermediate Steps in Mathematics Education (2016-2019)

Most digital testing and practicing tools in mathematics education review only a final answer, and do not look at the steps taken to reach the final answer. However, intermediate steps provide essential information for a detailed assessment of student skills. Assessing intermediate steps also corresponds to the pen and paper practice, and is a wish from the mathematics education sector. This project studies the automatic assessment of intermediate steps in mathematics education for domains such as Numbers and Relationships. We develop general feedback and assessment services that can be used by existing digital learning environments. These services give accurate diagnoses of intermediate steps and use these to determine mathematical knowledge, skills, and competences.

Supported by: Erasmus+.
Participating CS members: Bastiaan Heeren.
project website

Strategy-based tutoring systems for programming (2015-2019)

Learning programming is becoming increasingly popular but is also very challenging. Automated tools can support students in learning programming. Tutors that support the stepwise implementation of programs through various strategies and that are easily adaptable by teachers are scarce. In this research we develop technical concepts and solutions for constructing strategy-based and teacher-adaptable tutoring systems for programming. The novelty of our approach is the use of compiler technology to analyse incomplete student solutions to derive feedback and hints. The research will be evaluated by user data analysis of a tutor prototype and a feedback benchmark that we will design ourselves.

Supported by: NWO Lerarenbeurs.
Participating CS members: Hieke Keuning, Bastiaan Heeren.