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Despite several deficiencies, the use of spreadsheets in statistics courses is increasingly common. In this paper we discuss many shortcomings resulting from this approach. We suggest a technique integrating a spreadsheet and a dedicated…

Data Analysis, Statistics and Probability · Physics 2007-05-23 Matteo Dell'Omodarme , Giada Valle

Imitation learning field requires expert data to train agents in a task. Most often, this learning approach suffers from the absence of available data, which results in techniques being tested on its dataset. Creating datasets is a…

Machine Learning · Computer Science 2024-03-04 Nathan Gavenski , Michael Luck , Odinaldo Rodrigues

In this paper, we discuss the problem of the software engineering of a class of business spreadsheet models. A methodology for structured software development is proposed, which is based on structured analysis of data, represented as…

Software Engineering · Computer Science 2008-05-29 Brian Knight , David Chadwick , Kamalesen Rajalingham

Identifying and mitigating safety risks is paramount in a number of industries. In addition to guidelines and best practices, many industries already have safety management systems (SMSs) designed to monitor and reinforce good safety…

Applications · Statistics 2022-05-03 Ashutosh Tewari , Antonio R. Paiva

Spreadsheet tools are widely accessible to and commonly used by K-12 students and teachers. They have an important role in data collection and organization. Beyond data organization, spreadsheets also make data visible and easy to interact…

Other Statistics · Statistics 2025-06-05 Oren Tirschwell , Nicholas Jon Horton

Spreadsheet users regularly deal with uncertainty in their data, for example due to errors and estimates. While an insight into data uncertainty can help in making better informed decisions, prior research suggests that people often use…

Human-Computer Interaction · Computer Science 2019-05-31 Judith Borghouts , Andrew D. Gordon , Advait Sarkar , Kenton P. O'Hara , Neil Toronto

We introduce a simple but effective method for managing risk in model-based reinforcement learning with trajectory sampling that involves probabilistic safety constraints and balancing of optimism in the face of epistemic uncertainty and…

Machine Learning · Computer Science 2023-09-12 Marin Vlastelica , Sebastian Blaes , Cristina Pineri , Georg Martius

The objective of this paper is to develop a standardized methodology for software development in the very unique industry and culture of financial markets. The prototyping process we present allows the development team to deliver for review…

Software Engineering · Computer Science 2008-03-10 Andrew Kumiega , Ben Van Vliet

Increasingly, courses on Empirical Software Engineering research methods are being offered in higher education institutes across the world, mostly at the M.Sc. and Ph.D. levels. While the need for such courses is evident and in line with…

Software Engineering · Computer Science 2025-03-17 Paris Avgeriou , Nauman bin Ali , Marcos Kalinowski , Daniel Mendez

The Sarbanes-Oxley Act of 2002 has finally forced corporations to examine the validity of their spreadsheets. They are beginning to understand the spreadsheet error literature, including what it tells them about the need for comprehensive…

Software Engineering · Computer Science 2008-04-08 Raymond R. Panko , Nicholas Ordway

Contemporary spreadsheets are plagued by a profusion of errors, auditing difficulties, lack of uniform development methodologies, and barriers to easy comprehension of the underlying business models they represent. This paper presents a…

Human-Computer Interaction · Computer Science 2008-03-14 Ziv Hellman

Learning with limited labelled data, such as prompting, in-context learning, fine-tuning, meta-learning or few-shot learning, aims to effectively train a model using only a small amount of labelled samples. However, these approaches have…

Machine Learning · Computer Science 2024-12-03 Branislav Pecher , Ivan Srba , Maria Bielikova

Foundation model development attracts a rapidly expanding body of contributors, scientists, and applications. To help shape responsible development practices, we introduce the Foundation Model Development Cheatsheet: a growing collection of…

Software testing has often to be done under severe pressure due to limited resources and a challenging time schedule facing the demand to assure the fulfillment of the software requirements. In addition, testing should unveil those software…

Software Engineering · Computer Science 2019-12-30 Michael Felderer , Ina Schieferdecker

We present a widely-used operations management model used in supply and distribution planning, that is typically embedded in a periodic business process that necessitates model modification and reuse. We consider three alternative…

Software Engineering · Computer Science 2018-02-05 Thomas A. Grossman , Vijay Mehrotra , Mouwafac Sidaoui

This paper describes a framework for a systematic classification of spreadsheet errors. This classification or taxonomy of errors is aimed at facilitating analysis and comprehension of the different types of spreadsheet errors. The taxonomy…

Software Engineering · Computer Science 2024-12-24 Kamalasen Rajalingham , David R. Chadwick , Brian Knight

Software needs to be secure, in particular, when deployed to critical infrastructures. Secure coding guidelines capture practices in industrial software engineering to ensure the security of code. This study aims to assess the level of…

Software Engineering · Computer Science 2021-01-07 Tiago Espinha Gasiba , Ulrike Lechner , Maria Pinto-Albuquerque , Daniel Mendez Fernandez

Achieving the UN Sustainable Development Goals (SDGs) demands adequate levels of awareness and actions to address sustainability challenges. Software systems will play an important role in moving towards these targets. Sustainability skills…

Safe reinforcement learning deals with mitigating or avoiding unsafe situations by reinforcement learning (RL) agents. Safe RL approaches are based on specific risk representations for particular problems or domains. In order to analyze…

Machine Learning · Computer Science 2023-12-11 Leonardo Villalobos-Arias , Derek Martin , Abhijeet Krishnan , Madeleine Gagné , Colin M. Potts , Arnav Jhala

Just like other software, spreadsheets can contain significant faults. Static analysis is an accepted and well-established technique in software engineering known for its capability to discover faults. In recent years, a growing number of…

Software Engineering · Computer Science 2014-01-30 Daniel Kulesz , Jan-Peter Ostberg