Symmetry/Asymmetry in Software Engineering

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: closed (15 April 2024) | Viewed by 1877

Special Issue Editors


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Guest Editor
Research Institute for Future Media Computing, College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China
Interests: multiobjective optimization; evolutionary algorithms; machine learning

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Guest Editor
Department of Computer Science and Engineering, Chung-Ang University, 84 Heukseok-ro, Heukseok-dong, Dongjak-gu, Seoul 06974, Republic of Korea
Interests: artificial intelligence; machine learning; neural architecture design; feature engineering
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School of Computer Science, South-Central Minzu University, Wuhan 430079, China
Interests: UAV networks; algorithm design and analysis; computational intelligence; wireless sensor networks

Special Issue Information

Dear Colleagues,

We are pleased to announce a call for papers for a Special Issue on "Symmetry/Asymmetry in Software Engineering" in Symmetry. Currently, modern AI-based applications and digital economy rely on software systems. Software engineering is challenged with fast changes in project objectives, constraints, or priorities and symmetry/asymmetry aspects should be given considerate focus in the life cycle of software engineering. This Special Issue aims to explore and investigate the role of symmetry and asymmetry in various aspects of software engineering. We invite researchers and practitioners to contribute their original research, case studies, and review articles to shed light on this fascinating and important topic.

Topics of Interest:

This Special Issue welcomes submissions on a wide range of topics related to symmetry and asymmetry in software engineering. Potential areas of interest include, but are not limited to:

  • Software quality assurance and metrics;
  • Software project management and coordination;
  • Software evolution, maintenance, and refactoring;
  • Software analytics and data mining;
  • Software design patterns and architectural styles;
  • Machine learning and computational intelligence models in software engineering;
  • Software testing and test case generation;
  • Automated bug detection and classification;
  • Machine learning for software defect prediction and quality assurance;
  • Case studies and real-world applications of symmetry and asymmetry in software engineering.

Dr. Yu Zhou
Prof. Dr. Jaesung Lee
Dr. Xiao Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (1 paper)

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20 pages, 956 KiB  
Article
Optimizing Prioritization of Crowdsourced Test Reports of Web Applications through Image-to-Text Conversion
by Lei Xiao, Yunhuan Wu, Rongshang Chen and Hanghai Shi
Symmetry 2024, 16(1), 80; https://doi.org/10.3390/sym16010080 - 8 Jan 2024
Cited by 1 | Viewed by 1321
Abstract
Collating vast test reports is a time-consuming and laborious task in crowdsourced testing. Crowdsourced test reports are usually presented in two ways, one as text and the other as images, which have symmetrical content. Researchers have proposed many text- and image-based methods for [...] Read more.
Collating vast test reports is a time-consuming and laborious task in crowdsourced testing. Crowdsourced test reports are usually presented in two ways, one as text and the other as images, which have symmetrical content. Researchers have proposed many text- and image-based methods for prioritizing crowdsourced test reports of mobile applications. However, crowdsourced test reports of web applications typically have clearer textual descriptions of errors but noisier screenshots of errors. This gap motivates us to propose a method for prioritizing crowdsourced test reports of web applications to detect all errors earlier. In this paper, we integrate text and image information from test reports to enhance the analysis process. First, we use the natural language processing (NLP) technique to extract textual features of error descriptions and then symmetrically extract image features of error screenshots, i.e., we use the optical character recognition (OCR) technique to obtain textual information in the screenshots and then also use the NLP technique to extract features. To validate our approach, we conduct experiments on 717 test reports. The experimental results show that our method has a higher APFD (average percentage fault detection) and shorter runtime than state-of-the-art prioritization methods. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Software Engineering)
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