Related papers: Comparing Techniques for Aggregating Interrelated …

Controlled experiments are a core research method in software engineering (SE) for validating causal claims. However, recruiting a sample of participants that represents the intended target population is often difficult or expensive, which…

In collaborative learning, learners coordinate to enhance each of their learning performances. From the perspective of any learner, a critical challenge is to filter out unqualified collaborators. We propose a framework named meta…

In this paper, computational aspects of the panel aggregation problem are addressed. Motivated primarily by applications of risk assessment, an algorithm is developed for aggregating large corpora of internally incoherent probability…

Retrieval-Augmented Generation (RAG) improves the accuracy and relevance of large language model outputs by incorporating knowledge retrieval. However, implementing RAG in enterprises poses challenges around data security, accuracy,…

Bayesian experimental design (BED) for complex physical systems is often limited by the nested inference required to estimate the expected information gain (EIG) or its gradients. Each outer sample induces a different posterior, creating a…

Context: Experiment replications play a central role in the scientific method. Although software engineering experimentation has matured a great deal, the number of experiment replications is still relatively small. Software engineering…

This paper describes a novel approach to software engineering derived from the "SP Theory of Intelligence" and its realisation in the "SP Computer Model". Despite superficial appearances, it is shown that many of the key ideas in software…

Modern Sequential Recommendation (SR) models commonly utilize modality features to represent items, motivated in large part by recent advancements in language and vision modeling. To do so, several works completely replace ID embeddings…

For more than thirty years, it has been claimed that a way to improve software developers' productivity and software quality is to focus on people. The underlying assumption seems to be that "happy and satisfied software developers perform…

Across various domains, the growing advocacy for open science and open-source machine learning has made an increasing number of models publicly available. These models allow practitioners to integrate them into their own contexts, reducing…

Independently trained machine learning models tend to learn similar features. Given an ensemble of independently trained models, this results in correlated predictions and common failure modes. Previous attempts focusing on decorrelation of…

A computer simulation, such as a genetic algorithm, that uses IEEE standard floating-point arithmetic may not produce exactly the same results in two different runs, even if it is rerun on the same computer with the same input and random…

Aggregated relational data is widely collected to study social networks, in fields such as sociology, public health and economics. Many of the successes of ARD inference have been driven by increasingly complex Bayesian models, which…

Although agile software development methods have caught the attention of software engineers and researchers worldwide, scientific research still remains quite scarce. The aim of this study is to order and make sense of the different agile…

Computational models of complex systems are usually elaborate and sensitive to implementation details, characteristics which often affect their verification and validation. Model replication is a possible solution to this issue. It avoids…

Context: The need of replicating empirical studies in Computer Science (CS) is widely recognized among the research community to consolidate acquired knowledge generalizing results. It is essential to report the changes of each replication…

Context. GenAI tools are being increasingly adopted by practitioners in SE, promising support for several SE activities. Despite increasing adoption, we still lack empirical evidence on how GenAI is used in practice, the benefits it…

Existing sequential generalized estimating equation methodology for longitudinal and group-correlated data focuses on narrow hypotheses concerning treatment efficacy and often makes modeling assumptions that impede the desirable robustness…

Background: Collaboration among software engineers through face-to-face discussions in teams has been promoted since the adoption of agile methods. However, these discussions might demote the contribution of software engineers who are…

The integration of real-world data (RWD) and randomized controlled trials (RCT) is increasingly important for advancing causal inference in scientific research. This combination holds great promise for enhancing the efficiency of causal…