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Context: Researchers from different groups and institutions are collaborating on building groups of experiments by means of replication (i.e., conducting groups of replications). Disparate aggregation techniques are being applied to analyze…

Software Engineering · Computer Science 2020-04-14 Adrian Santos , Sira Vegas , Markku Oivo , Natalia Juristo

Replicability and reproducibility of experimental results are primary concerns in all the areas of science and IR is not an exception. Besides the problem of moving the field towards more reproducible experimental practices and protocols,…

Information Retrieval · Computer Science 2020-10-27 Timo Breuer , Nicola Ferro , Norbert Fuhr , Maria Maistro , Tetsuya Sakai , Philipp Schaer , Ian Soboroff

Recent studies have shown that the majority of published computational models in systems biology and physiology are not repeatable or reproducible. There are a variety of reasons for this. One of the most likely reasons is that given how…

Other Quantitative Biology · Quantitative Biology 2021-07-13 Herbert M. Sauro

Conducting empirical research in software engineering industry is a process, and as such, it should be generalizable. The aim of this paper is to discuss how academic researchers may address some of the challenges they encounter during…

Software Engineering · Computer Science 2020-03-17 Katarzyna Biesialska , Xavier Franch , Victor Muntés-Mulero

University research groups in Computational Science and Engineering (CSE) generally lack dedicated funding and personnel for Research Software Engineering (RSE), which, combined with the pressure to maximize the number of scientific…

In recent years, the research community, but also the general public, has raised serious questions about the reproducibility and replicability of scientific work. Since many studies include some kind of computational work, these issues are…

Software Engineering · Computer Science 2025-03-14 Lázaro Costa , Susana Barbosa , Jácome Cunha

Reproducibility is a fundamental requirement of the scientific process since it enables outcomes to be replicated and verified. Computational scientific experiments can benefit from improved reproducibility for many reasons, including…

Databases · Computer Science 2019-09-04 Maria Luiza Mondelli , A. Townsend Peterson , Luiz M. R. Gadelha

Reproducibility remains a central challenge in computational social science, where complex workflows, evolving software ecosystems, and inconsistent documentation hinder researchers ability to re-execute published methods. This study…

Human-Computer Interaction · Computer Science 2026-03-04 Fakhri Momeni , Sarah Sajid , Johannes Kiesel

University research groups in Computational Science and Engineering (CSE) generally lack dedicated funding and personnel for Research Software Engineering (RSE), which, combined with the pressure to maximize the number of scientific…

Beyond sharing datasets or simulations, we believe the Recommender Systems (RS) community should share Task Environments. In this work, we propose a high-level logical architecture that will help to reason about the core components of a RS…

Information Retrieval · Computer Science 2019-09-17 Andrea Barraza-Urbina , Mathieu d'Aquin

Ascertaining the feasibility of independent falsification or repetition of published results is vital to the scientific process, and replication or reproduction experiments are routinely performed in many disciplines. Unfortunately, such…

Databases · Computer Science 2020-09-11 Dimitri Braininger , Wolfgang Mauerer , Stefanie Scherzinger

Large-scale replication studies like the Reproducibility Project: Psychology (RP:P) provide invaluable systematic data on scientific replicability, but most analyses and interpretations of the data fail to agree on the definition of…

Methodology · Statistics 2022-03-08 Kenneth Hung , William Fithian

A common concern in experimental research is the auditability and reproducibility of experiments. Experiments are usually designed, provisioned, managed, and analyzed by diverse teams of specialists (e.g., researchers, technicians and…

The potential disconnect between research and practice in software engineering (SE) means that the uptake of research outcomes has at times been limited. In this paper we seek to identify research approaches that are rigorous in terms of…

Software Engineering · Computer Science 2021-01-12 Petteri Kaskenpalo , Stephen G. MacDonell

Computer science is also an experimental science. This is particularly the case for parallel computing, which is in a total state of flux, and where experiments are necessary to substantiate, complement, and challenge theoretical modeling…

Distributed, Parallel, and Cluster Computing · Computer Science 2013-08-19 Sascha Hunold , Jesper Larsson Träff

The software engineering research community is productive, yet it faces a constellation of challenges: swamped review processes, metric-driven incentives, distorted publication practices, and increasing pressures from AI, scale, and…

Software Engineering · Computer Science 2026-01-26 Mary Shaw , Mary Lou Maher , Keith Webster

Context: Empirical Software Engineering (ESE) drives innovation in SE through qualitative and quantitative studies. However, concerns about the correct application of empirical methodologies have existed since the 2006 Dagstuhl seminar on…

Experimentation with software prototypes plays a fundamental role in software engineering research. In contrast to many other scientific disciplines, however, explicit support for this key activity in software engineering is relatively…

Software Engineering · Computer Science 2021-10-26 Klaus Schmid , Sascha El-Sharkawy , Christian Kröher

This report synthesizes findings from the November 2024 Community Workshop on Practical Reproducibility in HPC, which convened researchers, artifact authors, reviewers, and chairs of reproducibility initiatives to address the critical…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-06 Kate Keahey , Marc Richardson , Rafael Tolosana Calasanz , Sascha Hunold , Jay Lofstead , Tanu Malik , Christian Perez

Deep learning (DL) techniques have gained significant popularity among software engineering (SE) researchers in recent years. This is because they can often solve many SE challenges without enormous manual feature engineering effort and…

Software Engineering · Computer Science 2024-12-10 Chao Liu , Cuiyun Gao , Xin Xia , David Lo , John Grundy , Xiaohu Yang