Julián Grigera | Searcharxiv

arXiv2026

It's Alive! What a Live Object Environment Changes in Software Engineering Practice

Tools shape our mind. This is why it is important to have extensible and flexible tools for developers to adapt to their needs. Reasoning about programs in the abstract -- by imagining what objects should look like -- can make it harder to grasp the underlying model. In Smalltalk environments like Pharo, developers work closely with their objects, gaining immediate feedback -- not guessing how they will look like but directly interacting with them. This article presents some tools developers use in Pharo: Inspector custom views for defining specific views and navigation for objects, Microcommits for reverting changes without the need to commit and pull, Xtreme TDD that allows developers to code in the debugger, On the Fly Rewriting Deprecations that support API evolution through automated rewriting of deprecated calls, and Object-Centric Breakpoints -- when a problem cannot be efficiently solved with a dummy trace, developers can use break points that will only halt for a given instance. By showcasing these features that evolved alongside Smalltalk, we invite reflection on how other IDEs could rethink some of their features and improve developers' workflows.

cs.SE↗

arXiv2025

A Study on Interaction Complexity and Time

Testing Web User Interfaces (UIs) requires considerable time and effort and resources, most notably participants for user testing. Additionally, the tests results may demand adjustments on the UI, taking further resources and testing. Early tests can make this process less costly with the help of low fidelity prototypes, but it is difficult to conduct user tests on them, and recruiting participants is still necessary. To tackle this issue, there are tools that can predict UI aspects like interaction time, as the well-known KLM model. Another aspect that can be predicted is complexity, and this was achieved by the Big I notation, which can be applied to early UX concepts like lo-fi wireframes. Big I assists developers in estimating the interaction complexity, specified as a function of user steps, which are composed of abstracted user actions. Interaction complexity is expressed in mathematical terms, making the comparison of interaction complexities for various UX concepts easy. However, big I is not able to predict execution time for user actions, which would be very helpful for early assessment of lo-fi prototypes. To address this shortcoming, in this paper we present a study in which we took measurements from real users (n=100) completing tasks in a fictitious website, in order to derive average times per interaction step. Using these results, we were able to study the relationship between interaction complexity and time and ultimately complement big I predictions with time estimates.

cs.HC↗