Tootfinder

Diversity's Double-Edged Sword: Analyzing Race's Effect on Remote Pair Programming Interactions
Shandler A. Mason, Sandeep Kaur Kuttal
https://arxiv.org/abs/2404.07427

Diversity's Double-Edged Sword: Analyzing Race's Effect on Remote Pair Programming Interactions
Remote pair programming is widely used in software development, but no research has examined how race affects these interactions. We embarked on this study due to the historical under representation of Black developers in the tech industry, with White developers comprising the majority. Our study involved 24 experienced developers, forming 12 gender-balanced same- and mixed-race pairs. Pairs collaborated on a programming task using the think-aloud method, followed by individual retrospective in…

This https://arxiv.org/abs/2403.19560 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Exploring Communication Dynamics: Eye-tracking Analysis in Pair Programming of Computer Science Education
Pair programming is widely recognized as an effective educational tool in computer science that promotes collaborative learning and mirrors real-world work dynamics. However, communication breakdowns within pairs significantly challenge this learning process. In this study, we use eye-tracking data recorded during pair programming sessions to study communication dynamics between various pair programming roles across different student, expert, and mixed group cohorts containing 19 participants. …

This https://arxiv.org/abs/2402.01066 has been replaced.
link: https://scholar.google.com/scholar?q=a

On the Hardness of Short and Sign-Compatible Circuit Walks
The circuits of a polyhedron are a superset of its edge directions. Circuit walks, a sequence of steps along circuits, generalize edge walks and are "short" if they have few steps or small total length. Both interpretations of short are relevant to the theory and application of linear programming. We study the hardness of several problems relating to the construction of short circuit walks. We establish that for a pair of vertices of a $0/1$-network-flow polytope, it is NP-complete to determi…

Pair Programming

Exploring Communication Dynamics: Eye-tracking Analysis in Pair Programming of Computer Science Education
Wunmin Jang, Hong Gao, Tilman Michaeli, Enkelejda Kasneci
https://arxiv.org/abs/2403.19560

Exploring Communication Dynamics: Eye-tracking Analysis in Pair Programming of Computer Science Education
Pair programming is widely recognized as an effective educational tool in computer science that promotes collaborative learning and mirrors real-world work dynamics. However, communication breakdowns within pairs significantly challenge this learning process. In this study, we use eye-tracking data recorded during pair programming sessions to study communication dynamics between various pair programming roles across different student, expert, and mixed group cohorts containing 19 participants. …

I'm using LLM since Friday to help me writing a Visual Basic macro. I have 0 knowledge of VBA and Word API in the same time.
While I think I'd be much more efficient having a pair programming with someone who actually knows this technology, still LLM is a nice kick starter for terra-incognita places where I have no clue how to start, where to look and what I need.
Happy to have this tech.

Evolving Benchmark Functions to Compare Evolutionary Algorithms via Genetic Programming
Yifan He, Claus Aranha
https://arxiv.org/abs/2403.14146 https://

Evolving Benchmark Functions to Compare Evolutionary Algorithms via Genetic Programming
In this study, we use Genetic Programming (GP) to compose new optimization benchmark functions. Optimization benchmarks have the important role of showing the differences between evolutionary algorithms, making it possible for further analysis and comparisons. We show that the benchmarks generated by GP are able to differentiate algorithms better than human-made benchmark functions. The fitness measure of the GP is the Wasserstein distance of the solutions found by a pair of optimizers. Additio…

This https://arxiv.org/abs/2311.01020 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Exploring the Problems, their Causes and Solutions of AI Pair Programming: A Study with Practitioners of GitHub Copilot
With the recent advancement of Artificial Intelligence (AI) and Large Language Models (LLMs), AI-based code generation tools become a practical solution for software development. GitHub Copilot, the AI pair programmer, utilizes machine learning models trained on a large corpus of code snippets to generate code suggestions using natural language processing. Despite its popularity in software development, there is limited empirical evidence on the actual experiences of practitioners who work with…

There are a lot of valid criticisms of LLMs, but "they are useless" is definitely not one of them. Just went from "I have no idea how to write tests for this specific project setup I have before me" to "I think I know how to create these tests, let's write a few and ask for feedback" to finally arrive at "oh, there are some really neat convenience features in pytest that make it possible to write this in a significantly cleaner way", all in the space of two hours, by basically pair programming with ChatGPT. As long as you leave your brain turned on while using it, and keep asking good questions, it really can be a force multiplier in learning new things in an area you already have some knowledge in.

This https://arxiv.org/abs/2310.05292 has been replaced.
link: https://scholar.google.com/scholar?q=a

How to Teach Programming in the AI Era? Using LLMs as a Teachable Agent for Debugging
Large Language Models (LLMs) now excel at generative skills and can create content at impeccable speeds. However, they are imperfect and still make various mistakes. In a Computer Science education context, as these models are widely recognized as "AI pair programmers," it becomes increasingly important to train students on evaluating and debugging the LLM-generated code. In this work, we introduce HypoCompass, a novel system to facilitate deliberate practice on debugging, where human novices p…

There are a lot of valid criticisms of LLMs, but "they are useless" is definitely not one of them. Just went from "I have no idea how to write tests for this specific project setup I have before me" to "I think I know how to create these tests, let's write a few and ask for feedback" to finally arrive at "oh, there are some really neat convenience features in pytest that make it possible to write this in a significantly cleaner way", all in the space of two hours, by basically pair programming with ChatGPT. As long as you leave your brain turned on while using it, and keep asking good questions, it really can be a force multiplier in learning new things in an area you already have some knowledge in.

Finding Moving-Band Statistical Arbitrages via Convex-Concave Optimization
Kasper Johansson, Thomas Schmelzer, Stephen Boyd
https://arxiv.org/abs/2402.08108

Finding Moving-Band Statistical Arbitrages via Convex-Concave Optimization
We propose a new method for finding statistical arbitrages that can contain more assets than just the traditional pair. We formulate the problem as seeking a portfolio with the highest volatility, subject to its price remaining in a band and a leverage limit. This optimization problem is not convex, but can be approximately solved using the convex-concave procedure, a specific sequential convex programming method. We show how the method generalizes to finding moving-band statistical arbitrages,…