Alexander Nolte

Jeanette Falk, Yiyi Chen, Janet Rafner et al.

Hackathons have become popular collaborative events for accelerating the development of creative ideas and prototypes. There are several case studies showcasing creative outcomes across domains such as industry, education, and research. However, there are no large-scale studies on creativity in hackathons which can advance theory on how hackathon formats lead to creative outcomes. We conducted a computational analysis of 193,353 hackathon projects. By operationalizing creativity through usefulness and novelty, we refined our dataset to 10,363 projects, allowing us to analyze how participant characteristics, collaboration patterns, and hackathon setups influence the development of creative projects. The contribution of our paper is twofold: We identified means for organizers to foster creativity in hackathons. We also explore the use of large language models (LLMs) to augment the evaluation of creative outcomes and discuss challenges and opportunities of doing this, which has implications for creativity research at large.

Sjoerd Halmans, Lavinia Paganini, Alexander Serebrenik et al.

Hackathons are time-bound collaborative events that often target software creation. Although hackathons have been studied in the past, existing work focused on in-depth case studies limiting our understanding of hackathons as a software engineering activity. To complement the existing body of knowledge, we introduce HackRep, a dataset of 100,356 hackathon GitHub repositories. We illustrate the ways HackRep can benefit software engineering researchers by presenting a preliminary investigation of hackathon project continuation, hackathon team composition, and an estimation of hackathon geography. We further display the opportunities of using this dataset, for instance showing the possibility of estimating hackathon durations based on commit timestamps.

Williams Rizzi, Marco Comuzzi, Chiara Di Francescomarino et al.

Explainability is motivated by the lack of transparency of black-box Machine Learning approaches, which do not foster trust and acceptance of Machine Learning algorithms. This also happens in the Predictive Process Monitoring field, where predictions, obtained by applying Machine Learning techniques, need to be explained to users, so as to gain their trust and acceptance. In this work, we carry on a user evaluation on explanation approaches for Predictive Process Monitoring aiming at investigating whether and how the explanations provided (i) are understandable; (ii) are useful in decision making tasks;(iii) can be further improved for process analysts, with different Machine Learning expertise levels. The results of the user evaluation show that, although explanation plots are overall understandable and useful for decision making tasks for Business Process Management users -- with and without experience in Machine Learning -- differences exist in the comprehension and usage of different plots, as well as in the way users with different Machine Learning expertise understand and use them.

Abasi-amefon Obot Affia, Alexander Nolte, Raimundas Matulevičius

Cybersecurity educators have widely introduced hackathons to facilitate practical knowledge gaining in cybersecurity education. Introducing such events into cybersecurity courses can provide valuable learning experiences for students. The nature of the hackathon format encourages a learning-by-doing approach, and the hackathon outcomes can serve as evidence for students knowledge, capability and learning gains. Prior work on hackathons in education mainly focused on collocated hackathon events in the traditional classroom setting. These hackathon events often took place as a one-off event at the end of the course. However, one-off hackathon events at the end of a course might not be sufficient to improve learning. Instead, we focus on analyzing the integration of a series of online hackathon events into an online cybersecurity course and explore how this integration can address online education issues by encouraging collaboration and developing a practical understanding of the delivered course by solving real-world challenges. We evaluate interventions to foster learning and analyze its effect on collaboration and learning gains for students in the course. Our findings indicate that students attribute learning benefits to the introduced interventions that supported teamwork and collaboration, maintained student participation and interest in the course, and encouraged learning-by-doing.

Kateryna Kubrak, Fredrik Milani, Alexander Nolte et al.

Prescriptive process monitoring methods seek to optimize a business process by recommending interventions at runtime to prevent negative outcomes or poorly performing cases. In recent years, various prescriptive process monitoring methods have been proposed. This paper studies existing methods in this field via a Systematic Literature Review (SLR). In order to structure the field, the paper proposes a framework for characterizing prescriptive process monitoring methods according to their performance objective, performance metrics, intervention types, modeling techniques, data inputs, and intervention policies. The SLR provides insights into challenges and areas for future research that could enhance the usefulness and applicability of prescriptive process monitoring methods. The paper highlights the need to validate existing and new methods in real-world settings, to extend the types of interventions beyond those related to the temporal and cost perspectives, and to design policies that take into account causality and second-order effects.

Ahmed Imam, Tapajit Dey, Alexander Nolte et al.

Background: Hackathons have become popular events for teams to collaborate on projects and develop software prototypes. Most existing research focuses on activities during an event with limited attention to the evolution of the code brought to or created during a hackathon. Aim: We aim to understand the evolution of hackathon-related code, specifically, how much hackathon teams rely on pre-existing code or how much new code they develop during a hackathon. Moreover, we aim to understand if and where that code gets reused, and what factors affect reuse. Method: We collected information about 22,183 hackathon projects from DEVPOST -- a hackathon database -- and obtained related code (blobs), authors, and project characteristics from the World of Code. We investigated if code blobs in hackathon projects were created before, during, or after an event by identifying the original blob creation date and author, and also checked if the original author was a hackathon project member. We tracked code reuse by first identifying all commits containing blobs created during an event before determining all projects that contain those commits. Result: While only approximately 9.14% of the code blobs are created during hackathons, this amount is still significant considering the time and member constraints of such events. Approximately a third of these code blobs get reused in other projects. The number of associated technologies and the number of participants in a project increase reuse probability. Conclusion: Our study demonstrates to what extent pre-existing code is used and new code is created during a hackathon and how much of it is reused elsewhere afterwards. Our findings help to better understand code reuse as a phenomenon and the role of hackathons in this context and can serve as a starting point for further studies in this area.

Abasi-amefon Obot Affia-Jomants, Kiev Gama, James D. Herbsleb et al.

Hackathons and similar time-bounded events are a global phenomenon. Their proliferation in various domains and their usefulness for a variety of goals has led to the emergence of different formats. While there are a multitude of guidelines available on how to prepare and run a hackathon, most of them focus on a particular format that was created for a specific purpose within a domain for a certain type of participant. This makes it difficult, in particular, for novice organizers to decide how to run an event that fits their needs. To address this gap we developed the original version of this planning kit in 2020 which focused on in-person events that were the dominant form of hackathons then. That planning kit was organized around 12 key decisions that organizers need to take when preparing for, running, and following up on a hackathon. Fast forward to 2025, after going through a global pandemic that forced all events to move online, we now see different forms of events - in-person, online, and hybrid - taking place across the globe, and while they can be all valuable, they have different affordances and require different considerations when planning. To account for these differences, we decided to update the original planning kit by adding a section that discusses the affordances and requirements of in-person, online, and hybrid events to each of the 12 decisions. In addition, we modified the original example timelines to include different forms and types of events. We also updated the planning kit in general based on insights we gained through continuing to organize and study hackathons. The main planning kit is available online while this report is meant to be a downloadable and citable resource.

Ei Pa Pa Pe-Than, Alexander Nolte

In hackathons, small teams work together over a specified period of time to complete a project of interest. Such time-bounded hackathon-style events have become increasingly popular across different domains in recent years. Collegiate hackathons, just one of the many variants of hackathons, that are supported by the largest hackathon league (https://mlh.io/) alone attract over 65,000 participants among more than 200 events each year. Variously known as data dives, codefests, hack-days, sprints, edit-a-thons, mapathons, and so on, such events vary depending on different audiences and with divergent aims: for example, whether teams know each other beforehand, whether the event is structured as a competition with prizes, whether the event is open or requires membership or invitations, and whether the desired outcome is primarily a product innovation, learning a new skill, forming a community around a cause, solving a technical problem that requires intensive focus by a group, or just having fun. Taken together, hackathons offer new opportunities and challenges for collaboration by affording explicit, predictable, time-bounded spaces for collaborative work and engaging with new audiences. With the goal of discussing opportunities and challenges surrounding hackathons of different kinds, this one-day workshop brought together researchers, experienced event organizers, and practitioners to share and discuss their practical experiences. Empirical insights from studying these events may help position the CHI community to better study, plan and design hackathon-style events as socio-technical systems that support new modes of production and collaboration.