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Item Open Access Holistic optimization framework for FPGA accelerators(Colorado State University. Libraries, 2025-09-05) Pouget, Stéphane, author; Lo, Michael, author; Pouchet, Louis-Noël, author; Cong, Jason, author; ACM, publisherCustomized accelerators have revolutionized modern computing by delivering substantial gains in energy efficiency and performance through hardware specialization. Field-Programmable Gate Arrays (FPGAs) play a crucial role in this paradigm, offering unparalleled flexibility and high-performance potential. High-Level Synthesis (HLS) and source-to-source compilers have simplified FPGA development by translating high-level programming languages into hardware descriptions enriched with directives. However, achieving high Quality of Results (QoR) remains a significant challenge, requiring intricate code transformations, strategic directive placement, and optimized data communication. This article presents Prometheus, a holistic optimization framework that integrates key optimizations - including task fusion, tiling, loop permutation, computation-communication overlap, and concurrent task execution-into a unified design space. By leveraging Non-Linear Programming (NLP) methodologies, Prometheus explores the optimization space under strict resource constraints, enabling automatic bitstream generation. Unlike existing frameworks, Prometheus considers interdependent transformations and dynamically balances computation and memory access. We evaluate Prometheus across multiple benchmarks, demonstrating its ability to maximize parallelism, minimize execution stalls, and optimize data movement. The results showcase its superior performance compared to state-of-the-art FPGA optimization frameworks, highlighting its effectiveness in delivering high QoR while reducing manual tuning efforts.Item Open Access The importance of cueing while visually searching a 360 degree environment for multiple targets in the presence of distractors(Colorado State University. Libraries, 2025-11-12) Kelley, Brendan, author; McMahan, Ryan P., author; Wickens, Christopher D., author; Clegg, Benjamin A., author; Ortega, Francisco R., author; ACM, publisherVisually searching for objects is an everyday task. In many contexts, people must visually search for multiple objects at the same time while avoiding distractor objects, such as triage during a mass casualty incident. While many prior augmented reality (AR) and virtual reality (VR) studies have investigated cues to aid in visual search tasks, few have investigated cues in contexts involving multiple targets and distractors with a full 360° effective field of regard (EFOR). Individually, multiple targets, distractors, and a full 360° EFOR each add complexity to visual search; when combined, they compound the difficulty even further. In this paper, we present such a study that compares three common types of visual cues (2D Wedge, 3D Arrow, and Gaze Line) to a baseline condition with no cueing for a 360° visual search task. Our results reinforce the importance of providing some type of cue, with the Gaze Line design being particularly beneficial. We discuss the potential implications of these findings for designing cues specifically for such complex visual search tasks.Item Open Access LLM tuning: neural language persistence through adaptive mixture(Colorado State University. Libraries, 2025-12-09) Banik, Mridul, author; ACM, publisherThis paper presents a novel architectural paradigm addressing knowledge degradation in large language models during continual fine-tuning. The framework leverages a Mixture-of-Experts-style approach, integrating multiple low-rank adapters governed by an intelligent routing mechanism. By freezing core model parameters and dynamically allocating task-specific expertise, this method preserves inherent world knowledge while enhancing performance across diverse downstream applications. The proposed Dynamic LoRA-Experts with Prototype-Ensemble Matching (DLEPM) framework demonstrates superior performance on sequential NLP benchmarks, achieving 89.2% average accuracy with only 5.4% forgetting—outperforming existing continual learning methods. Empirical evaluations validate the framework's efficacy in maintaining large language model fidelity during continuous adaptation.Item Open Access Addressing OSS community managers' challenges in contributor retention(Colorado State University. Libraries, 2025-09-09) Feng, Zixuan, author; Kimura, Katie, author; Trinkenreich, Bianca, author; Steinmacher, Igor, author; Gerosa, Marco, author; Sarma, Anita, author; ACM, publisherOpen-source software (OSS) community managers face significant challenges in retaining contributors, as they must monitor activity and engagement while navigating complex dynamics of collaboration. Current tools designed for managing contributor retention (e.g., dashboards) fall short by providing retrospective rather than predictive insights to identify potential disengagement early. Without understanding how to anticipate and prevent disengagement, new solutions risk burdening community managers rather than supporting retention management. Following the Design Science Research paradigm, we employed a mixed-methods approach for problem identification and solution design to address contributor retention. To identify the challenges hindering retention management in OSS, we conducted semi-structured interviews, a multi-vocal literature review, and community surveys. Then through an iterative build-evaluate cycle, we developed and refined strategies for diagnosing retention risks and informing engagement efforts. We operationalized these strategies into a web-based prototype, incorporating feedback from 100+ OSS practitioners, and conducted an in situ evaluation across two OSS communities. Our study offers (1) empirical insights into the challenges of contributor retention management in OSS, (2) actionable strategies that support OSS community managers’ retention efforts, and (3) a practical framework for future research in developing or validating theories about OSS sustainability.Item Open Access Novel tensor norm optimization for neural network training acceleration(Colorado State University. Libraries, 2025-12-09) Banik, Mridul, author; ACM, publisherThis paper introduces an advanced optimization algorithm designed to enhance the training efficiency of neural networks, particularly focusing on the intricate weight matrices prevalent in large language models. Diverging from prior spectral norm-based approaches, our method leverages the nuclear norm to formulate a novel update rule, yielding a distinct optimization technique called Neon. We provide rigorous theoretical guarantees concerning its convergence properties through convex optimization and Karush-Kuhn-Tucker conditions. Performance evaluations across multilayer perceptrons, convolutional neural networks, and generative models such as NanoGPT demonstrate computational advantages over existing optimizers including Muon and AdamW. The Frobenius-based Neon variant achieves comparable or superior convergence while maintaining significantly lower per-iteration overhead of O(mn) FLOPs compared to Muon's O(mn · min {m, n}) for m x n matrices. This work advances more robust and faster training methodologies for complex AI systems.Item Open Access Five-day research-in-the-wild observation of notifications on smartglasses: a double edged sword(Colorado State University. Libraries, 2025-11-12) Plabst, Lucas, author; Plabst, Lena, author; Niebling, Florian, author; Ortega, Francisco R., author; ACM, publisherNotifications are a fundamental aspect of daily computing, whether on desktops, laptops, smartphones, or smartwatches. On average, adults receive around 200 notifications per day—approximately one every five minutes during waking hours. As Extended Reality (XR) headsets advance, they may become the primary medium for digital interactions, making notification management a crucial factor in their usability. While notifications are known to be disruptive on smartphones, their impact could be even more pronounced on head-worn devices. To investigate this, we conducted an exploratory five-day study with eight participants wearing display-equipped smartglasses that delivered notifications from their smartphones. Participants used the glasses throughout their day for at least 2 hours receiving on average 62% of all notifications on the glasses, submitted daily journal entries, and participated in post-study interviews. We also logged notification sources and timestamps throughout the study. Our findings reveal both practical advantages and significant challenges of head-worn notification delivery. While participants appreciated the convenience and immediacy of glanceable alerts, concerns about privacy, social acceptability, and distraction emerged as key barriers to adoption.Item Open Access TerraMAE: learning spatial-spectral representations from hyperspectral Earth observation data via adaptive masked autoencoders(Colorado State University. Libraries, 2025-12-12) Faruk, Tanjim Bin, author; Matin, Abdul, author; Pallickara, Shrideep, author; Pallickara, Sangmi Lee, author; ACM, publisherMasked Autoencoders struggle with hyperspectral satellite imagery containing 200+ spectral bands, as uniform masking across all channels obscures critical spatial-spectral relationships. We introduce TerraMAE, which employs an adaptive channel grouping strategy to organize bands into statistically coherent groups with independent masking. Together with a customized loss function, this data-driven grouping strategy enables TerraMAE to learn robust spatial-spectral representations from unlabeled HSI. Experiments demonstrate that TerraMAE significantly outperforms baseline Masked Autoencoder and supervised ResNet-50 on soil texture prediction, achieving 15.7% and 6.6% lower error, respectively.Item Open Access Repurposing audio playback tools to test human localization with 6DoF sound(Colorado State University. Libraries, 2025-09-28) Rehberg, Daniel, author; Williams, Adam S., author; Batmaz, Anil Ufuk, author; Ortega, Francisco R., author; ACM, publisherSix-degree-of-freedom audio is a growing interest in interactive software, but it does not easily conform to object-based rendering when achieved with arrays of ambisonics microphones. Prior studies rely on subjective metrics also, which do not clearly indicate how this additional audio interaction might aid a human in a localization task – an indication of enhanced spatial awareness of a sound event. In this paper, we propose an alternative recording and playback technique to achieve six-degree-of-freedom audio to minimize recording overhead, yield object-based rendering, and verify enhanced spatialization through objective testing. The approach taken in this paper utilizes existing audio playback tools in the Unity game engine, and can be redeployed quickly to allow researchers outside of audio engineering exploration in six-degree-of-freedom audio applications. Two studies were conducted within a group of participants using a Microsoft Hololens 2 – testing for interpretation of directional sound cues in a stationary position, and testing the proposed technique in a mobile task. Participants were able to discern additional information within the front-facing "blind spots" and were effectively perfect in a localization task with the proposed audio technique. Participants did not achieve the same performance level with a head-related transfer function alone – indicating meaningful cueing with six-degree-of-freedom sound.Item Open Access Modular construction and optimization of the UZP sparse format for SpMV on CPUs(Colorado State University. Libraries, 2025-06-10) Rodríguez-Iglesias, Alonso, author; Tongli, Santoshkumar T., author; Tucker, Emily, author; Pouchet, Louis-Noël, author; Rodríguez, Gabriel, author; Touriño, Juan, author; ACM, publisherSparse data structures are ubiquitous in modern computing, and numerous formats have been designed to represent them. These formats may exploit specific sparsity patterns, aiming to achieve higher performance for key numerical computations than more general-purpose formats such as CSR and COO. In this work we present UZP, a new sparse format based on polyhedral sets of integer points. UZP is a flexible format that subsumes CSR, COO, DIA, BCSR, etc., by raising them to a common mathematical abstraction: a union of integer polyhedra, each intersected with an affine lattice. We present a modular approach to building and optimizing UZP: it captures equivalence classes for the sparse structure, enabling the tuning of the representation for target-specific and application-specific performance considerations. UZP is built from any input sparse structure using integer coordinates, and is interoperable with existing software using CSR and COO data layout. We provide detailed performance evaluation of UZP on 200+ matrices from SuiteSparse, demonstrating how simple and mostly unoptimized generic executors for UZP can already achieve solid performance by exploiting Z-polyhedra structures.Item Open Access "It only needs to work for one of us": rethinking DIY deaf tech through situated co-design(Colorado State University. Libraries, 2025-10-26) Huffman, Shuxu, author; Angelini, Robin, author; Kushalnagar, Raja, author; Spiel, Katta, author; ACM, publisherThis experience report presents a real-world case in which a Deaf open water swimmer and their hearing kayak partner designed and developed a vibration-based system for attention signaling during long-distance swims. When mainstream accessibility tools failed to meet their needs, they built a lightweight, context-specific solution grounded in Deaf cultural practices and embodied knowledge. Through in-situ use and reflective practice, we examine how this do-it-yourself (DIY) tool emerged from relational design and Deaf-centered philosophy. Rather than offering a generalized solution, this work highlights the value of culturally grounded, small-scale technologies shaped by the lived experience of a Deaf swimmer and their collaboration with a hearing ally. We conclude with a call for research approaches and design platforms that empower Deaf communities to create technologies rooted in their own values, environments, and ways of being.Item Open Access Walking in an urban environment and a virtual reality replica: comparisons of physical activity duration and intensity(Colorado State University. Libraries, 2025) Spitzer, Amanda N., author; Ramey, Matea R., author; Yu, Yiqing "Skylar", author; Oselinsky, Katrina M., author; McMahon, Katie, author; Kelley, Brendan, author; Rojas-Rueda, David, author; Dean, Daniel, author; LoTemplio, Sara B., author; Ortega, Francisco R., author; Graham, Dan J., authorIncreasing walking behavior is desirable from public health, environmental, and urban planning perspectives. Virtual reality (VR) has the potential to improve the design of walkable environments. However, the current research is necessary to determine whether walking decisions in VR mirror those in the real world (RW). Participants completed two study sessions: walking in a VR simulation of a historic district (VR session) and walking in the real-life district (RW session). During each session, participants were asked to complete three tasks (e.g., find a restaurant) and stop walking following task completion. Heart rate (HR) data contained a high degree of missingness, so no HR analyses are reported. Nevertheless, walking intensity is addressed through exploratory negative binomial and Poisson regression models predicting duration in light and moderate-to-vigorous physical activity using accelerometry. These models indicated no relationship between physical activity intensity in VR and the RW. Additionally, a paired t-test and mixed effects model indicated that walking duration was significantly longer in VR than the RW. However, exploratory analyses suggested order effects: those who walked first in the RW walked similar durations in both settings, but those that walked first in VR walked for about five minutes longer in VR (17.8) than in the RW (13.0). In conclusion, walking intensity in VR may not mimic walking intensity in the RW, but depending on order of conditions, walking decisions in VR may resemble RW decisions. Possible explanations for the observed order effects include history effects, VR navigation and skill transfer, and participant motivation.Item Open Access "Bring your own device!": adaptive IoT device-type fingerprinting using automatic behavior extraction(Colorado State University. Libraries, 2025-07-25) Bar-on, Maxwel, author; Patterson, Katherine, author; Bezawada, Bruhadeshwar, author; Ray, Indrakshi, author; Ray, Indrajit, author; ACM, publisherInternet-of-Things (IoT) is playing a key role in modern society by offering enhanced functionalities and services. As IoT devices may introduce new security risks to the network, network administrators profile the behavior of IoT devices using device fingerprinting. Device fingerprinting typically involves training a machine learning model using the network behavioral data of existing devices. If a new device is added, the network becomes vulnerable to attacks until the time that the machine learning model is trained and updated to integrate the new device. Furthermore, if many devices are regularly added to the network, the cost of adapting the machine learning model can be significant. To address the challenges of security and scalability in fingerprinting, we create a collection of observed behaviors of IoT devices from existing devices and use this collection to construct a fingerprint for a new device. In our approach, we design a bi-component neural network architecture consisting of a transformer-based behavior-extractor (BE) and a fingerprinting interpreter. We perform a one-time training of the BE to extract behaviors from known devices. We use the generated BE for (a) fingerprinting existing devices and (b) adapting the existing fingerprinting model to new device data. In our experiments on 22 diverse IoT devices, we show that our model can identify newly introduced devices as well as known devices with a high identification rate. Our approach improves the time to adapt a model by a factor of 78.3× with no loss of accuracy, achieving recall over 98%.Item Open Access Safety analysis in the NGAC model(Colorado State University. Libraries, 2025-07-07) Tan, Brian, author; Davies, Ewan S. D., author; Ray, Indrakshi, author; Abdelgawad, Mahmoud A., author; ACM, publisherWe study the safety problem for the next-generation access control (NGAC) model. We show that under mild assumptions it is coNP-complete, and under further realistic assumptions we give an algorithm for the safety problem that significantly outperforms naive brute force search. We also show that real-world examples of mutually exclusive attributes lead to nearly worst-case behavior of our algorithm.Item Open Access SPEAR: security posture evaluation using AI planner-reasoning on attack-connectivity(Colorado State University. Libraries, 2025-07-07) Podder, Rakesh, author; Caglar, Turgay, author; Bashir, Shadaab Kawnain, author; Sreedharan, Sarath, author; Ray, Indrajit, author; Ray, Indrakshi, author; ACM, publisherGraph-based frameworks are often used in network hardening to help a cyber defender understand how a network can be attacked and how the best defenses can be deployed. However, incorporating network connectivity parameters in the attack graph, reasoning about the attack graph when we do not have access to complete information, providing system administrator suggestions in an understandable format, and allowing them to do what-if analysis on various scenarios and attacker motives is still missing. We fill this gap by presenting SPEAR, a formal framework with tool support for security posture evaluation and analysis that keeps humanin- the-loop. SPEAR uses the causal formalism of AI planning to model vulnerabilities and configurations in a networked system. It automatically converts network configurations and vulnerability descriptions into planning models expressed in the Planning Domain Definition Language (PDDL). SPEAR identifies a set of diverse security hardening strategies that can be presented in a manner understandable to the domain expert. These allow the administrator to explore the network hardening solution space in a systematic fashion and help evaluate the impact and compare the different solutions.Item Open Access Proof of compliance (PoC): a consensus mechanism to verify the compliance with informed consent policy in healthcare(Colorado State University. Libraries, 2025-06-04) Amin, Md Al, author; Tummala, Hemanth, author; Shah, Rushabh, author; Ray, Indrajit, author; ACM, publisherHealthcare industries are subject to various laws and regulatory oversight, just like other industries, such as pharmaceuticals, telecommunications, education, and financial services. Compliance with these regulations is essential for the organization's operation and growth. To help organizations detect early non-compliance issues, this paper proposes a consensus mechanism, Proof of Compliance (PoC), where a set of distributed, decentralized, and independent auditor nodes perform audit operations to determine the compliance status of any logical operations or accesses that have already been approved, granted, or executed in the system. The Proof of Compliance consensus mechanism helps organizations minimize compliance challenges. Organizations can consider PoC outputs to take further actions to reduce non-compliance cases and avoid compliance issues and business losses. The PoC reports do not support final regulatory compliance certification. However, it is possible if one or more multiple audit nodes are deployed and maintained in the consensus mechanism by the corresponding regulatory, government, or compliance authority.Item Open Access Dramatically faster Partition Crossover for the traveling salesman problem(Colorado State University. Libraries, 2025-07-13) de Carvalho, Ozéas Quevedo, author; Whitley, Darrell, author; ACM, publisherThe Partition Crossover is a deterministic crossover operator for the Traveling Salesman Problem (TSP). It decomposes the union graph of two TSP solutions, A and B, into connected components known as AB-cycles, from which the lower-cost edges are selected and recombined to produce offspring. The operator finds the best offspring within a search space of 2k solutions in linear time, where k is the number of recombining components. We introduce Generalized Partition Crossover 3 (GPX3), a new implementation of Partition Crossover. GPX3 features a new algorithm to quickly find AB-cycles in the union graph. It also identifies additional recombining AB-cycles, expanding the reachable search space. We show that GPX3 runs in O(n) time and is more efficient and effective than previous implementations of Partition Crossover for the TSP.Item Open Access How Partition Crossover exposes parallel lattices and the fractal structure of k-bounded functions(Colorado State University. Libraries, 2025-07-13) Whitley, Darrell, author; Ochoa, Gabriela, author; Chicano, Francisco, author; ACM, publisherA combination of recombination and local search can expose the existence of an exponential number of parallel lattices that span the search space for all classes of k-bounded pseudo-Boolean functions, including MAX-kSAT problems. These "parallel" lattices sometimes have identical evaluations shifted by a constant. We use Partition Crossover to aid in the discovery of lattices, which are sets of 2q possible offspring from recombination events, organized into q-dimensional hypercubes, where q is the number of recombining components given two parents. Finally, we show that recursively embedded subspace lattices display a fractal structure, which can be captured using rewrite rules based on a Lindenmayer system that accurately model how local optima are distributed across different size lattices.Item Open Access Get on the train or be left on the station: using LLMs for software engineering research(Colorado State University. Libraries, 2025-07-28) Trinkenreich, Bianca, author; Calefato, Fabio, author; Hanssen, Geir, author; Blincoe, Kelly, author; Kalinowski, Marcos, author; Pezzè, Mauro, author; Tell, Paolo, author; Storey, Margaret-Anne, author; ACM, publisherThe adoption of Large Language Models (LLMs) is not only transforming software engineering (SE) practice but is also poised to fundamentally disrupt how research is conducted in the field. While perspectives on this transformation range from viewing LLMs as mere productivity tools to considering them revolutionary forces, we argue that the SE research community must proactively engage with and shape the integration of LLMs into research practices, emphasizing human agency in this transformation. As LLMs rapidly become integral to SE research—both as tools that support investigations and as subjects of study—a human-centric perspective is essential. Ensuring human oversight and interpretability is necessary for upholding scientific rigor, fostering ethical responsibility, and driving advancements in the field. Drawing from discussions at the 2nd Copenhagen Symposium on Human-Centered AI in SE, this position paper employs McLuhan's Tetrad of Media Laws to analyze the impact of LLMs on SE research. Through this theoretical lens, we examine how LLMs enhance research capabilities through accelerated ideation and automated processes, make some traditional research practices obsolete, retrieve valuable aspects of historical research approaches, and risk reversal effects when taken to extremes. Our analysis reveals opportunities for innovation and potential pitfalls that require careful consideration. We conclude with a call to action for the SE research community to proactively harness the benefits of LLMs while developing frameworks and guidelines to mitigate their risks, to ensure continued rigor and impact of research in an AI-augmented future.Item Open Access Making software development more diverse and inclusive: key themes, challenges, and future directions(Colorado State University. Libraries, 2025-05-27) Hyrynsalmi, Sonja M., author; Baltes, Sebastian, author; Brown, Chris, author; Prikladnicki, Rafael, author; Rodriguez-Perez, Gema, author; Serebrenik, Alexander, author; Simmonds, Jocelyn, author; Trinkenreich, Bianca, author; Wang, Yi, author; Liebel, Grischa, author; ACM, publisherIntroduction: Digital products increasingly reshape industries, influencing human behavior and decision-making. However, the software development teams developing these systems often lack diversity, which may lead to designs that overlook the needs, equal treatment or safety of diverse user groups. These risks highlight the need for fostering diversity and inclusion in software development to create safer, more equitable technology. Method: This research is based on insights from an academic meeting in June 2023 involving 23 software engineering researchers and practitioners. We used the collaborative discussion method 1-2-4-ALL as a systematic research approach and identified six themes around the theme "challenges and opportunities to improve Software Developer Diversity and Inclusion (SDDI)." We identified benefits, harms, and future research directions for the four main themes. Then, we discuss the remaining two themes, AI & SDDI and AI & Computer Science education, which have a cross-cutting effect on the other themes. Results: This research explores the key challenges and research opportunities for promoting SDDI, providing a roadmap to guide both researchers and practitioners. We underline that research around SDDI requires a constant focus on maximizing benefits while minimizing harms, especially to vulnerable groups. As a research community, we must strike this balance in a responsible way.Item Open Access Exploring the untapped: student perceptions and participation in OSS(Colorado State University. Libraries, 2025-07-28) Santos, Italo, author; Felizardo, Katia Romero, author; Trinkenreich, Bianca, author; German, Daniel M., author; Steinmacher, Igor, author; Gerosa, Marco A., author; ACM, publisherOpen Source Software (OSS) projects offer valuable opportunities to train the next generation of software engineers while benefiting projects and society as a whole. While research has extensively explored student participation in OSS and its use in software engineering education, student participation in OSS is still low, and the perspectives of students who have never contributed remain underexplored. This study aims to investigate the relationship between students' interest in contributing to OSS and their perceptions of barriers and motivational factors. We developed a theoretical model to understand the relationship between students' perceptions of OSS and their interest in contributing. We then surveyed students majoring in computer science and related fields (N=241). Using structural equation modeling techniques, we tested the model and found that intrinsic and internalized extrinsic motivations are positively associated with interest in contributing to OSS projects, while the impact of extrinsic motivation varies by gender. Comparatively, we found no significant relationship between barriers and interest in contributing. Students suggested several ways to make projects more attractive, including increasing awareness of the importance of OSS. Our findings can help communities better prepare to integrate students and encourage educators to enhance interest in OSS by linking participation to specific motivational factors.
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