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Searching for clues, gathering evidence, and reviewing case files are all techniques used by criminal investigators to draw sound conclusions and avoid wrongful convictions. Similarly, in software engineering (SE) research, we can develop…

Software Engineering · Computer Science 2023-09-19 Marvin Muñoz Barón , Marvin Wyrich , Daniel Graziotin , Stefan Wagner

Test-Driven Development (TDD) has been claimed to increase external software quality. However, the extent to which TDD increases external quality has been seldom studied in industrial experiments. We conduct four industrial experiments in…

Software Engineering · Computer Science 2018-07-23 Adrian Santos , Janne Jarvinen , Jari Partanen , Markku Oivo , Natalia Juristo

Results of simulation studies evaluating the performance of statistical methods are often considered actionable and thus can have a major impact on the way empirical research is implemented. However, so far there is limited evidence about…

Many research fields are currently reckoning with issues of poor levels of reproducibility. Some label it a "crisis", and research employing or building Machine Learning (ML) models is no exception. Issues including lack of transparency,…

Software Engineering · Computer Science 2025-02-27 Harald Semmelrock , Tony Ross-Hellauer , Simone Kopeinik , Dieter Theiler , Armin Haberl , Stefan Thalmann , Dominik Kowald

Software repositories are an essential source of information for software engineering research on topics such as project evolution and developer collaboration. Appropriate mining tools and analysis pipelines are therefore an indispensable…

Software Engineering · Computer Science 2025-01-28 Nicole Hoess , Carlos Paradis , Rick Kazman , Wolfgang Mauerer

Although reproducibility is a core tenet of the scientific method, it remains challenging to reproduce many results. Surprisingly, this also holds true for computational results in domains such as systems biology where there have been…

Quantitative Methods · Quantitative Biology 2021-04-13 Michael L. Blinov , John H. Gennari , Jonathan R. Karr , Ion I. Moraru , David P. Nickerson , Herbert M. Sauro

Over the past few years, deep learning methods have been applied for a wide range of Software Engineering (SE) tasks, including in particular for the important task of automatically predicting and localizing faults in software. With the…

Software Engineering · Computer Science 2024-02-09 Adil Mukhtar , Dietmar Jannach , Franz Wotawa

Over the recent years the importance of numerical experiments has gradually been more recognized. Nonetheless, sufficient documentation of how computational results have been obtained is often not available. Especially in the scientific…

Mathematical Software · Computer Science 2021-05-10 Jörg Fehr , Jan Heiland , Christian Himpe , Jens Saak

In this paper we formally analyze the software methodology called (iterated) Test Driven Development (TDD). We formally define Specification, Software, Testing, Equivalence Partitions, Coupling, to argue about the nature of the software…

Software Engineering · Computer Science 2024-07-19 Hemil Ruparel , Nabarun Mondal

Background: Many decisions made in Software Engineering practices are intertemporal choices: trade-offs in time between closer options with potential short-term benefit and future options with potential long-term benefit. However, how…

Background. There are some publications in software engineering research that aim at guiding researchers in assessing validity threats to their studies. Still, many researchers fail to address many aspects of validity that are essential to…

Software Engineering · Computer Science 2018-09-07 Lucas Gren

[Background] Recent investigations into the effects of Test-Driven Development (TDD) have been contradictory and inconclusive. This hinders development teams to use research results as the basis for deciding whether and how to apply TDD.…

Software Engineering · Computer Science 2020-07-21 Mohammad Ghafari , Timm Gross , Davide Fucci , Michael Felderer

To encourage the development of methods with reproducible and robust training behavior, we propose a challenge paradigm where competitors are evaluated directly on the performance of their learning procedures rather than pre-trained agents.…

Background: Many published machine learning studies are irreproducible. Issues with methodology and not properly accounting for variation introduced by the algorithm themselves or their implementations are attributed as the main…

Machine Learning · Computer Science 2023-04-17 Odd Erik Gundersen , Kevin Coakley , Christine Kirkpatrick , Yolanda Gil

Objective: In this study, we aim to replicate an artefact-based study on software testing to address the gap. We focus on (a) providing a step by step guide of the replication, reflecting on challenges when replicating artefact-based…

Software Engineering · Computer Science 2022-04-14 Nasir Mehmood Minhas , Mohsin Irshad , Kai Petersen , Jürgen Börstler

Building deep reinforcement learning (RL) agents that find a good policy with few samples has proven notoriously challenging. To achieve sample efficiency, recent work has explored updating neural networks with large numbers of gradient…

Machine Learning · Computer Science 2025-04-04 Claas A Voelcker , Marcel Hussing , Eric Eaton , Amir-massoud Farahmand , Igor Gilitschenski

Software systems should be explainable, that is, they should help us to answer questions while exploring, developing or using them. Textual documentation is a very weak form of explanation, since it is not causally connected to the code, so…

Software Engineering · Computer Science 2024-09-04 Oscar Nierstrasz , Andrei Chiş , Tudor Gîrba

Automatic test generation aims to save developers time and effort by producing test suites with reasonably high coverage and fault detection. However, the focus of search-based generation tools in maximizing coverage leaves other…

Software Engineering · Computer Science 2025-04-11 Geraldine Galindo-Gutierrez

Evaluating Software testability can assist software managers in optimizing testing budgets and identifying opportunities for refactoring. In this paper, we abandon the traditional approach of pursuing testability measurements based on the…

Software Engineering · Computer Science 2021-02-23 Luca Guglielmo , Andrea Riboni , Giovanni Denaro

Reproducibility is a key requirement for scientific progress. It allows the reproduction of the works of others, and, as a consequence, to fully trust the reported claims and results. In this work, we argue that, by facilitating…

Information Retrieval · Computer Science 2021-02-02 Alejandro Bellogín , Alan Said