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Federated learning is an emerging machine learning paradigm that enables multiple devices to train models locally and formulate a global model, without sharing the clients' local data. A federated learning system can be viewed as a…
Competitive programming (CP) has been increasingly integrated into computer science curricula worldwide due to its efficacy in enhancing students' algorithmic reasoning and problem-solving skills. However, existing CP curriculum designs…
Structured prediction is often approached by training a locally normalized model with maximum likelihood and decoding approximately with beam search. This approach leads to mismatches as, during training, the model is not exposed to its…
The purpose of this work is to offer a methodology that allows to construct a standard in Knowledge Management and Technological Innovation which may be used in various organizations in M\'exico to improve the operation of their resources…
Context: Software architecture intensely impacts the software quality. Therefore, the professional assigned to carry out the design, maintenance and evolution of architectures needs to have certain knowledge and skills in order not to…
The research objective is to design a blended learning of system programming for software engineering bachelors. Under blended learning we understand the way of implementing the content of the training, which integrates classroom and…
This study proposes and evaluates the PAnoramic Learning Map (PALM), a learning analytics (LA) dashboard designed to address the scalability challenges of LA by integrating curriculum-level information. Traditional LA research has…
Workplaces of the future require advanced competence profiles from employees, not least due to new options for teleworking and new complex digital tools. The acquisition of advanced competence profiles is to be addressed by formal…
Despite growing global attention to digital accessibility, research from India highlights a significant gap in accessibility training for both computing educators and software professionals. To address this need, we designed and conducted…
While much prior work examines Large Language Models (LLMs) for solo development tasks (e.g., coding), far less is known about how LLMs shape collaborative group work in software engineering. This study focuses on one such collaborative…
Context: Research collaborations between software engineering industry and academia can provide significant benefits to both sides, including improved innovation capacity for industry, and real-world environment for motivating and…
Software architecture has been an active research field for nearly four decades, in which previous studies make significant progress such as creating methods and techniques and building tools to support software architecture practice.…
In this article, an overview of the background, the research approaches and the patterns of practice in the field of collaborative learning are provided. A definition of collaborative learning and an overview of fundamental aspects that…
Model selection is a problem that has occupied machine learning researchers for a long time. Recently, its importance has become evident through applications in deep learning. We propose an agreement-based learning framework that prevents…
The problems caused by the gap between system- and software-level architecting practices, especially in the context of Systems of Systems where the two disciplines inexorably meet, is a well known issue with a disappointingly low amount of…
As the complexity of our neural network models grow, so too do the data and computation requirements for successful training. One proposed solution to this problem is training on a distributed network of computational devices, thus…
In this work, we introduce a Self-Aware Polymorphic Architecture (SAPA) design approach to support emerging context-aware applications and mitigate the programming challenges caused by the ever-increasing complexity and heterogeneity of…
The technological landscape changes daily, making it nearly impossible for a single person to be aware of all trends or available tools that may or may not be suitable for their software project. This makes tool selection and architectural…
An empirical study was conducted to analyse design strategies and knowledge used in object-oriented software design. Eight professional programmers experienced with procedural programming languages and either experienced or not experienced…
Security-constrained unit commitment (SCUC) is a computationally complex process utilized in power system day-ahead scheduling and market clearing. SCUC is run daily and requires state-of-the-art algorithms to speed up the process. The…