12,706 research outputs found
Product line architecture recovery with outlier filtering in software families: the Apo-Games case study
Software product line (SPL) approach has been widely adopted to achieve systematic reuse in families of software products. Despite its benefits, developing an SPL from scratch requires high up-front investment. Because of that, organizations commonly create product variants with opportunistic reuse approaches (e.g., copy-and-paste or clone-and-own). However, maintenance and evolution of a large number of product variants is a challenging task. In this context, a family of products developed opportunistically is a good starting point to adopt SPLs, known as extractive approach for SPL adoption. One of the initial phases of the extractive approach is the recovery and definition of a product line architecture (PLA) based on existing software variants, to support variant derivation and also to allow the customization according to customers’ needs. The problem of defining a PLA from existing system variants is that some variants can become highly unrelated to their predecessors, known as outlier variants. The inclusion of outlier variants in the PLA recovery leads to additional effort and noise in the common structure and complicates architectural decisions. In this work, we present an automatic approach to identify and filter outlier variants during the recovery and definition of PLAs. Our approach identifies the minimum subset of cross-product architectural information for an effective PLA recovery. To evaluate our approach, we focus on real-world variants of the Apo-Games family. We recover a PLA taking as input 34 Apo-Game variants developed by using opportunistic reuse. The results provided evidence that our automatic approach is able to identify and filter outlier variants, allowing to eliminate exclusive packages and classes without removing the whole variant. We consider that the recovered PLA can help domain experts to take informed decisions to support SPL adoption.This research was partially funded by INES 2.0; CNPq grants 465614/2014-0 and 408356/2018-9; and FAPESB grants JCB0060/2016 and BOL2443/201
Automatically Detecting Visual Bugs in HTML5 <canvas> Games
The HTML5 is used to display high quality graphics in web
applications such as web games (i.e., games). However, automatically
testing games is not possible with existing web testing techniques and
tools, and manual testing is laborious. Many widely used web testing tools rely
on the Document Object Model (DOM) to drive web test automation, but the
contents of the are not represented in the DOM. The main alternative
approach, snapshot testing, involves comparing oracle snapshot images with
test-time snapshot images using an image similarity metric to catch visual
bugs, i.e., bugs in the graphics of the web application. However, creating and
maintaining oracle snapshot images for games is onerous, defeating the
purpose of test automation. In this paper, we present a novel approach to
automatically detect visual bugs in games. By leveraging an internal
representation of objects on the , we decompose snapshot images into a
set of object images, each of which is compared with a respective oracle asset
(e.g., a sprite) using four similarity metrics: percentage overlap, mean
squared error, structural similarity, and embedding similarity. We evaluate our
approach by injecting 24 visual bugs into a custom game, and find that
our approach achieves an accuracy of 100%, compared to an accuracy of 44.6%
with traditional snapshot testing.Comment: Accepted at ASE 2022 conferenc
Heuristic usability evaluation on games: a modular approach
Heuristic evaluation is the preferred method to assess usability in games when experts conduct this
evaluation. Many heuristics guidelines have been proposed attending to specificities of games but
they only focus on specific subsets of games or platforms. In fact, to date the most used guideline to
evaluate games usability is still Nielsen’s proposal, which is focused on generic software. As a
result, most evaluations do not cover important aspects in games such as mobility, multiplayer
interactions, enjoyability and playability, etc. To promote the usage of new heuristics adapted to
different game and platform aspects we propose a modular approach based on the classification of
existing game heuristics using metadata and a tool, MUSE (Meta-heUristics uSability Evaluation
tool) for games, which allows a rebuild of heuristic guidelines based on metadata selection in order
to obtain a customized list for every real evaluation case. The usage of these new rebuilt heuristic
guidelines allows an explicit attendance to a wide range of usability aspects in games and a better
detection of usability issues. We preliminarily evaluate MUSE with an analysis of two different
games, using both the Nielsen’s heuristics and the customized heuristic lists generated by our tool.Unión Europea PI055-15/E0
Exploring Terms and Taxonomies Relating to the Cyber International Relations Research Field: or are "Cyberspace" and "Cyber Space" the same?
This project has at least two facets to it: (1) advancing the algorithms in the sub-field of bibliometrics often referred to as "text mining" whereby hundreds of thousands of documents (such as journal articles) are scanned and relationships amongst words and phrases are established and (2) applying these tools in support of the Explorations in Cyber International Relations (ECIR) research effort. In international relations, it is important that all the parties understand each other. Although dictionaries, glossaries, and other sources tell you what words/phrases are supposed to mean (somewhat complicated by the fact that they often contradict each other), they do not tell you how people are actually using them.
As an example, when we started, we assumed that "cyberspace" and "cyber space" were essentially the same word with just a minor variation in punctuation (i.e., the space, or lack thereof, between "cyber" and "space") and that the choice of the punctuation was a rather random occurrence. With that assumption in mind, we would expect that the taxonomies that would be constructed by our algorithms using "cyberspace" and "cyber space" as seed terms would be basically the same. As it turned out, they were quite different, both in overall shape and groupings within the taxonomy.
Since the overall field of cyber international relations is so new, understanding the field and how people think about (as evidenced by their actual usage of terminology, and how usage changes over time) is an important goal as part of the overall ECIR project
Educational Technology as Seen Through the Eyes of the Readers
In this paper, I present the evaluation of a novel knowledge domain
visualization of educational technology. The interactive visualization is based
on readership patterns in the online reference management system Mendeley. It
comprises of 13 topic areas, spanning psychological, pedagogical, and
methodological foundations, learning methods and technologies, and social and
technological developments. The visualization was evaluated with (1) a
qualitative comparison to knowledge domain visualizations based on citations,
and (2) expert interviews. The results show that the co-readership
visualization is a recent representation of pedagogical and psychological
research in educational technology. Furthermore, the co-readership analysis
covers more areas than comparable visualizations based on co-citation patterns.
Areas related to computer science, however, are missing from the co-readership
visualization and more research is needed to explore the interpretations of
size and placement of research areas on the map.Comment: Forthcoming article in the International Journal of Technology
Enhanced Learnin
Typical Phone Use Habits: Intense Use Does Not Predict Negative Well-Being
Not all smartphone owners use their device in the same way. In this work, we
uncover broad, latent patterns of mobile phone use behavior. We conducted a
study where, via a dedicated logging app, we collected daily mobile phone
activity data from a sample of 340 participants for a period of four weeks.
Through an unsupervised learning approach and a methodologically rigorous
analysis, we reveal five generic phone use profiles which describe at least 10%
of the participants each: limited use, business use, power use, and
personality- & externally induced problematic use. We provide evidence that
intense mobile phone use alone does not predict negative well-being. Instead,
our approach automatically revealed two groups with tendencies for lower
well-being, which are characterized by nightly phone use sessions.Comment: 10 pages, 6 figures, conference pape
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