187 research outputs found
Specification-Driven Predictive Business Process Monitoring
Predictive analysis in business process monitoring aims at forecasting the
future information of a running business process. The prediction is typically
made based on the model extracted from historical process execution logs (event
logs). In practice, different business domains might require different kinds of
predictions. Hence, it is important to have a means for properly specifying the
desired prediction tasks, and a mechanism to deal with these various prediction
tasks. Although there have been many studies in this area, they mostly focus on
a specific prediction task. This work introduces a language for specifying the
desired prediction tasks, and this language allows us to express various kinds
of prediction tasks. This work also presents a mechanism for automatically
creating the corresponding prediction model based on the given specification.
Differently from previous studies, instead of focusing on a particular
prediction task, we present an approach to deal with various prediction tasks
based on the given specification of the desired prediction tasks. We also
provide an implementation of the approach which is used to conduct experiments
using real-life event logs.Comment: This article significantly extends the previous work in
https://doi.org/10.1007/978-3-319-91704-7_7 which has a technical report in
arXiv:1804.00617. This article and the previous work have a coauthor in
commo
Energy-Saving Strategies for Mobile Web Apps and their Measurement: Results from a Decade of Research (Preprint)
In 2022, over half of the web traffic was accessed through mobile devices. By
reducing the energy consumption of mobile web apps, we can not only extend the
battery life of our devices, but also make a significant contribution to energy
conservation efforts. For example, if we could save only 5% of the energy used
by web apps, we estimate that it would be enough to shut down one of the
nuclear reactors in Fukushima. This paper presents a comprehensive overview of
energy-saving experiments and related approaches for mobile web apps, relevant
for researchers and practitioners. To achieve this objective, we conducted a
systematic literature review and identified 44 primary studies for inclusion.
Through the mapping and analysis of scientific papers, this work contributes:
(1) an overview of the energy-draining aspects of mobile web apps, (2) a
comprehensive description of the methodology used for the energy-saving
experiments, and (3) a categorization and synthesis of various energy-saving
approaches.Comment: Preprint for 2023 IEEE/ACM 10th International Conference on Mobile
Software Engineering and Systems (MOBILESoft): Energy-Saving Strategies for
Mobile Web Apps and their Measurement: Results from a Decade of Researc
Worlds apart: industrial and academic focus areas in software testing
To determine how industry and academia approach software testing, researchers compared the titles of presentations from selected conferences in each of the two communities. The results shed light on the root cause of low industry-academia collaboration and led to suggestions on how to improve this situation
Closing the gap between software engineering education and industrial needs
According to different reports, many recent software engineering graduates
often face difficulties when beginning their professional careers, due to
misalignment of the skills learnt in their university education with what is
needed in industry. To address that need, many studies have been conducted to
align software engineering education with industry needs. To synthesize that
body of knowledge, we present in this paper a systematic literature review
(SLR) which summarizes the findings of 33 studies in this area. By doing a
meta-analysis of all those studies and using data from 12 countries and over
4,000 data points, this study will enable educators and hiring managers to
adapt their education / hiring efforts to best prepare the software engineering
workforce
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