Jaakko Järvi | Searcharxiv

arXiv2026

Why Users Stop at Good Enough: Applying Bounded Rationality to Self-Service Restaurant Display Interactions

This paper investigates user interaction with digital displays in self-service restaurant environments, focusing on the phenomenon where users often settle for good enough interactions rather than optimal. We apply bounded rationality theory to understand how cognitive limitations influence user decisions to engage with displays of varying interaction complexity. Through analysis of two field experiments conducted at a self-service restaurant in Finland, we examine interactive displays that require different levels of cognitive investment: a simple binary choice interface and a multi-step interaction. Our initial findings suggest an "engagement plateau" where increased interaction complexity yields diminishing returns in initial engagement rates, yet users who overcome initial cognitive barriers demonstrate high completion rates. This work contributes to Human-Computer Interaction field by offering an empirically supported theoretical lens for understanding user behavior in Self-Service Restaurant (SSR) environments and providing actionable design principles for public interactive displays that accommodate human cognitive limits.

cs.HC↗

arXiv2022

Revisiting Language Support for Generic Programming: When Genericity Is a Core Design Goal

Context: Generic programming, as defined by Stepanov, is a methodology for writing efficient and reusable algorithms by considering only the required properties of their underlying data types and operations. Generic programming has proven to be an effective means of constructing libraries of reusable software components in languages that support it. Generics-related language design choices play a major role in how conducive generic programming is in practice. Inquiry: Several mainstream programming languages (e.g. Java and C++) were first created without generics; features to support generic programming were added later, gradually. Much of the existing literature on supporting generic programming focuses thus on retrofitting generic programming into existing languages and identifying related implementation challenges. Is the programming experience significantly better, or different when programming with a language designed for generic programming without limitations from prior language design choices? Approach: We examine Magnolia, a language designed to embody generic programming. Magnolia is representative of an approach to language design rooted in algebraic specifications. We repeat a well-known experiment, where we put Magnolia's generic programming facilities under scrutiny by implementing a subset of the Boost Graph Library, and reflect on our development experience. Knowledge: We discover that the idioms identified as key features for supporting Stepanov-style generic programming in the previous studies and work on the topic do not tell a full story. We clarify which of them are more of a means to an end, rather than fundamental features for supporting generic programming. Based on the development experience with Magnolia, we identify variadics as an additional key feature for generic programming and point out limitations and challenges of genericity by property. Grounding: Our work uses a well-known framework for evaluating the generic programming facilities of a language from the literature to evaluate the algebraic approach through Magnolia, and we draw comparisons with well-known programming languages. Importance: This work gives a fresh perspective on generic programming, and clarifies what are fundamental language properties and their trade-offs when considering supporting Stepanov-style generic programming. The understanding of how to set the ground for generic programming will inform future language design.

cs.PL↗