Abstract
Modern storage systems requirements demand flexible, scalable solutions that address diverse concerns such as data reduction, replication, security, and multi-cloud distribution. Existing solutions often provide these guarantees through monolithic implementations, limiting their adaptability to specific application needs. This paper introduces PolyLayer, a multi-interface, composable and multi-backend storage architecture. It builds on the concept of stackable storage architectures and redesigns these to support commonly used user APIs (e.g., POSIX, Key-value, Object store), while providing support for data persistence across multiple storage backends (i.e., on-premises, cloud services, blockchain). We present the first steps towards the design of such architecture, while implementing a proof-of-concept and evaluating it. Our preliminary results show that the design can effectively be used in real-world scenarios where new functionality is added to a storage system with low overhead over the base system. For instance, we show how anti-tampering mechanisms can be added to a traditional relational database without any change to the database itself or the application using it.

Abstract
We conducted a workshop on ''Addressing Challenges in Recruiting Participants for Human-Centric Computing Research Studies'' at the IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)'24 Conference. In the workshop, we conducted a brainstorming session on ''roadmap development of making participant recruitment easier for human-centric computing studies in both industry and academia''. This article presents 7 stages of participant recruitment and key strategies identified by the authors (workshop participants) during the brainstorming session.

Abstract
Computational reproducibility-the ability to reexecute a scientific experiment using the same code, data, and configuration-should be straightforward. However, researchers often struggle with inconsistencies in documentation, missing dependencies, and environment setup, which undermines the credibility of scientific results. To address this, we propose a conversational, text-based tool that aids researchers in reproducing and packaging computational experiments into a single file. This file can be re-executed with a double-click on any machine, requiring only a single tool. SciConv is designed to support two key scenarios: (i) enabling researchers to prepare their own experiments in a reproducible, shareable format, and (ii) helping other researchers reproduce existing experiments from shared code repositories. In both cases, the tool reduces technical overhead and simplifies environment configuration through conversational interaction. We evaluated the tool through two studies. In the first, we reproduced 15 of 18 published experiments, with most requiring little or no user interaction. In the second, we conducted a user study comparing our tool with a professional platform, using the System Usability Scale (SUS) and NASA Task Load Index (TLX). The results show a statistically significant advantage for our tool in both usability and workload, demonstrating its effectiveness in supporting reproducibility.

Abstract
Reproducibility in computational science is increasingly dependent on the ability to faithfully re-execute experiments involving code, data, and software environments. However, assessing the effectiveness of reproducibility tools is difficult due to the lack of standardized benchmarks. To address this, we collected 38 computational experiments from diverse scientific domains and attempted to reproduce each using 8 different reproducibility tools. From this initial pool, we identified 18 experiments that could be successfully reproduced using at least one tool. These experiments form our curated benchmark dataset, which we release along with reproducibility packages to support ongoing evaluation efforts. This article introduces the curated dataset, incorporating details about software dependencies, execution steps, and configurations necessary for accurate reproduction. The dataset is structured to reflect diverse computational requirements and methodologies, ranging from simple scripts to complex, multi-language workflows, ensuring it presents the wide range of challenges researchers face in reproducing computational studies. It provides a universal benchmark by establishing a standardized dataset for objectively evaluating and comparing the effectiveness of reproducibility tools. Each experiment included in the dataset is carefully documented to ensure ease of use. We added clear instructions following a standard, so each experiment has the same kind of instructions, making it easier for researchers to run each of them with their own reproducibility tool.The utility of the dataset is demonstrated through extensive evaluations using multiple reproducibility tools.

Abstract
User studies are paramount for advancing research in software engineering, particularly when evaluating tools and techniques involving programmers. However, researchers face several barriers when performing them despite the existence of supporting tools. We base our study on a set of tools and researcher-reported barriers identified in prior work on user studies in software engineering. In this work, we study how existing tools and their features cope with previously identified barriers. Moreover, we propose new features for the barriers that lack support. We validated our proposal with 102 researchers, achieving statistically significant positive support for all but one feature. We study the current gap between tools and barriers, using features as the bridge. We show there is a significant lack of support for several barriers, as some have no single tool to support them.

Abstract
Supporting sustainability through modelling and analysis has become an active area of research in Software Engineering. Therefore, it is important and timely to survey the current state of the art in sustainability in Cyber-Physical Systems (CPS), one of the most rapidly evolving classes of complex software systems. This work presents the findings of a Systematic Mapping Study (SMS) that aims to identify key primary studies reporting on CPS modelling approaches that address sustainability over the last 10 years. Our literature search retrieved 2209 papers, of which 104 primary studies were deemed relevant fora detailed characterisation. These studies were analysed based on nine research questions designed to extract information on sustainability attributes, methods, models/meta-models, metrics, processes, and tools used to improve the sustainability of CPS. These questions also aimed to gather data on domain-specific modelling approaches and relevant application domains. The final results report findings for each of our questions, highlight interesting correlations among them, and identify literature gaps worth investigating in the near future.