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Omitted variable bias occurs when a statistical model leaves out variables that are relevant determinants of the effects under study. This results in the model attributing the missing variables' effect to some of the included variables --…

Software Engineering · Computer Science 2026-04-02 Carlo A. Furia , Richard Torkar

Researchers in empirical software engineering often make claims based on observable data such as defect reports. Unfortunately, in many cases, these claims are generalized beyond the data sets that have been evaluated. Will the researcher's…

Software Engineering · Computer Science 2020-08-10 Abdul Ali Bangash , Hareem Sahar , Abram Hindle , Karim Ali

When making choices in software projects, engineers and other stakeholders engage in decision making that involves uncertain future outcomes. Research in psychology, behavioral economics and neuroscience has questioned many of the classical…

Software Engineering · Computer Science 2017-01-31 Christoph Becker , Dawn Walker , Curtis McCord

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…

Large project overruns and overtime work have been reported in the software industry, resulting in additional expense for companies and personal issues for developers. The present work aims to provide an overview of studies related to time…

Software Engineering · Computer Science 2020-04-23 Miikka Kuutila , Mika Mäntylä , Umar Farooq , Maëlick Claes

The application of Algorithmic Recourse in decision-making is a promising field that offers practical solutions to reverse unfavorable decisions. However, the inability of these methods to consider potential dependencies among variables…

Artificial Intelligence · Computer Science 2024-10-16 Isacco Beretta , Martina Cinquini

In real world, the huge amount of temporal data is to be processed in many application areas such as scientific, financial, network monitoring, sensor data analysis. Data mining techniques are primarily oriented to handle discrete features.…

Databases · Computer Science 2014-02-19 P. Chaudhari , D. P. Rana , R. G. Mehta , N. J. Mistry , M. M. Raghuwanshi

It seems logical to assert that the dynamic nature of software engineering practice would mean that software effort estimation (SEE) modelling should take into account project start and completion dates. That is, we should build models for…

Software Engineering · Computer Science 2020-12-04 Michael Franklin Bosu , Stephen G. MacDonell , Peter Whigham

Bayesian data analysis (BDA) is today used by a multitude of research disciplines. These disciplines use BDA as a way to embrace uncertainty by using multilevel models and making use of all available information at hand. In this chapter, we…

Software Engineering · Computer Science 2020-01-03 Richard Torkar , Robert Feldt , Carlo A. Furia

Technical Debt management decisions always imply a trade-off among outcomes at different points in time. In such intertemporal choices, distant outcomes are often valued lower than close ones, a phenomenon known as temporal discounting.…

Software Engineering · Computer Science 2019-04-03 Christoph Becker , Fabian Fagerholm , Rahul Mohanani , Alexandros Chatzigeorgiou

While logistic regression models are easily accessible to researchers, when applied to network data there are unrealistic assumptions made about the dependence structure of the data. For temporal networks measured in discrete time, recent…

Methodology · Statistics 2020-05-20 Daniel K. Sewell

Temporal data are ubiquitous in the financial services (FS) industry -- traditional data like economic indicators, operational data such as bank account transactions, and modern data sources like website clickstreams -- all of these occur…

Statistical Finance · Quantitative Finance 2020-09-15 Jason Wittenbach , Brian d'Alessandro , C. Bayan Bruss

Reliable empirical models such as those used in software effort estimation or defect prediction are inherently dependent on the data from which they are built. As demands for process and product improvement continue to grow, the quality of…

Software Engineering · Computer Science 2021-06-14 Michael Franklin Bosu , Stephen G. MacDonell

The continuous advances in data collection and storage techniques allow us to observe and record real-life processes in great detail. Examples include financial transaction data, fMRI images, satellite photos, earths pollution distribution…

Methodology · Statistics 2015-02-26 Łukasz Kidziński

Time roots in applying language models for biomedical applications: models are trained on historical data and will be deployed for new or future data, which may vary from training data. While increasing biomedical tasks have employed…

Computation and Language · Computer Science 2024-08-13 Weisi Liu , Zhe He , Xiaolei Huang

Many software engineering research papers rely on time-based data (e.g., commit timestamps, issue report creation/update/close dates, release dates). Like most real-world data however, time-based data is often dirty. To date, there are no…

Software Engineering · Computer Science 2021-03-23 Samuel W. Flint , Jigyasa Chauhan , Robert Dyer

Analysing and improving productivity has been one of the main goals of software engineering research since its beginnings. A plethora of studies has been conducted on various factors that resulted in several models for analysis and…

Software Engineering · Computer Science 2018-01-22 Stefan Wagner , Melanie Ruhe

As software engineering research becomes more concerned with the psychological, sociological and managerial aspects of software development, relevant theories from reference disciplines are increasingly important for understanding the…

Software Engineering · Computer Science 2022-02-16 Tobias Lorey , Paul Ralph , Michael Felderer

Time series are all around in real-world applications. However, unexpected accidents for example broken sensors or missing of the signals will cause missing values in time series, making the data hard to be utilized. It then does harm to…

Machine Learning · Computer Science 2020-11-24 Chenguang Fang , Chen Wang

During the past years, psychological diseases related to unhealthy work environments, such as burnouts, have drawn more and more public attention. One of the known causes of these affective problems is time pressure. In order to form a…

Software Engineering · Computer Science 2017-03-14 Miikka Kuutila , Mika V. Mäntylä , Maëlick Claes , Marko Elovainio
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