Review
Computer Science, Artificial Intelligence
Moataz Chouchen, Ali Ouni, Mohamed Wiem Mkaouer, Raula Gaikovina Kula, Katsuro Inoue
Summary: In contemporary software development, code review is a crucial practice to ensure software quality. Peer code review is widely adopted, but the manual selection of peer reviewers can be time-consuming and inefficient, leading to increased development costs and time to market. A multi-objective search-based approach, called WhoReview, has been introduced to optimize the selection of peer reviewers for code changes, showing improved results compared to existing approaches.
APPLIED SOFT COMPUTING
(2021)
Review
Computer Science, Software Engineering
Nicole Davila, Ingrid Nunes
Summary: Modern Code Review (MCR) is a widely recognized practice in software quality assurance, with research categorized into foundational studies, proposals, and evaluations. Foundational studies focus on understanding the motivations, challenges, and benefits of adopting MCR, while proposals often involve code reviewer recommendation and code checking support. Evaluations are primarily done offline without human subjects. Five main research gaps have been identified for future work in this area.
JOURNAL OF SYSTEMS AND SOFTWARE
(2021)
Review
Engineering, Aerospace
Xi Chen, Lei Dong, Hong-Chang Li, Xin-Peng Yao, Peng Wang, Shuang Yao
Summary: Defects and errors in code pose a potential risk to software operation and require a proper code review process, especially for safety-critical software. The traditional manual review method is no longer sufficient due to the increasing size and variety of code. Deep Reviewer is a flexible framework that automatically detects code defects and correlates review comments. It achieves high precision and F1 scores and outperforms other methods in multi-classification tasks.
Review
Computer Science, Interdisciplinary Applications
Satnam Kaur, Lalit K. Awasthi, A. L. Sangal
Summary: This study proposes a multi-objective optimization technique to generate software refactoring solutions that maximize software quality, the use of smell severity, and consistency with class importance. Experimental results show that the performance of this method is significantly better than other algorithms when class importance and code smell severity scores are considered.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2021)
Review
Computer Science, Software Engineering
Amine Abbad-Andaloussi
Summary: This paper discusses the relationship between source-code metrics and cognitive load in software development tasks. Previous studies have not been able to establish a clear relationship between most source-code metrics and cognitive load. However, the literature contains hundreds of other metrics that have not been fully explored. To address this gap, this paper presents a Systematic Tertiary Review (STR) that covers the full spectrum of source-code metrics, studying their properties and investigating their potential relationship to cognitive load. The outcome of this STR aims to guide practitioners in choosing appropriate metrics and raise new research challenges for the future.
JOURNAL OF SYSTEMS AND SOFTWARE
(2023)
Article
Computer Science, Information Systems
Ruchin Gupta, Sandeep Kumar Singh
Summary: This paper proposes a novel metric-based method and tool for detecting temporary field code smell. Results from testing on ten open-source Java projects demonstrate a strong correlation between the presence of temporary field code smell and the number of non-cohesive classes.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Automation & Control Systems
Bruno Sotto-Mayor, Amir Elmishali, Meir Kalech, Rui Abreu
Summary: This paper studies the performance of defect prediction models and compares models using Design code smells, Traditional smells, and a combination of both. The results show that models trained with both Design code smells and Traditional smells performed the best.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Review
Computer Science, Software Engineering
Patanamon Thongtanunam, Ahmed E. Hassan
Summary: The study reveals that the evaluation decisions of reviewers in modern code review processes are influenced by visible information, including feedback from prior reviewers. The likelihood of reviewers providing positive votes is highly associated with the amount of prior feedback and the cooperation frequency with the patch author. However, the associations of these review dynamics are not as strong as the confounding factors such as patch characteristics and overall reviewing activities.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2021)
Review
Computer Science, Theory & Methods
Morteza Zakeri-Nasrabadi, Saeed Parsa, Ehsan Esmaili, Fabio Palomba
Summary: The accuracy of code smell-detecting tools varies depending on the dataset used for evaluation. The adequacy of a dataset highly depends on relevant properties such as size, severity level, project types, and the number of each type of smell. Existing datasets often suffer from imbalanced samples, lack of severity level support, and restriction to Java language.
ACM COMPUTING SURVEYS
(2023)
Review
Computer Science, Software Engineering
Enrico Fregnan, Fernando Petrulio, Alberto Bacchelli
Summary: Code review is a software engineering practice aimed at improving the quality of code through manual inspection and proposed changes. This study analyzes the changes that occur during the review process and expands our understanding of code review outcomes. The majority of changes identified are related to evolvability concerns, with a strong focus on documentation and structure changes. Interestingly, it is found that most review changes are not triggered by reviewers' comments.
EMPIRICAL SOFTWARE ENGINEERING
(2022)
Article
Computer Science, Software Engineering
Ifeanyi G. Ndukwe, Sherlock A. Licorish, Amjed Tahir, Stephen G. MacDonell
Summary: There is ongoing debate and uncertainty about software quality and its measurement. A current catalogue of software quality views is necessary, and understanding views on code quality is important for developers. The lack of suitable quality models may result in relaxed or inappropriate views on software quality.
JOURNAL OF SYSTEMS AND SOFTWARE
(2023)
Article
Computer Science, Software Engineering
Enrico Fregnan, Josua Froehlich, Davide Spadini, Alberto Bacchelli
Summary: This paper presents a new visualization approach to support developers in understanding code review changes. The authors implemented the approach in a tool called ReviewVis and conducted surveys to assess its benefits. The collected feedback showed that developers perceived ReviewVis as helpful in navigating and understanding review changes.
JOURNAL OF SYSTEMS AND SOFTWARE
(2023)
Article
Computer Science, Software Engineering
Alexander Trautsch, Steffen Herbold, Jens Grabowski
Summary: Automated Static Analysis Tools (ASATs) are an integral part of software development and can warn developers about potential code problems. However, ASATs often have false positive warnings that need to be inspected and ignored by developers. This article examines the measurable impact of ASATs on external software quality using the example of PMD for Java. The research finds that there is little difference in the warning density between bug inducing files and other files.
EMPIRICAL SOFTWARE ENGINEERING
(2023)
Article
Computer Science, Software Engineering
Alexander Trautsch, Johannes Erbel, Steffen Herbold, Jens Grabowski
Summary: Software metrics are used to evaluate aspects related to software quality, such as size, complexity, and coupling. However, the relationship between quality and software metrics is not well understood, and complexity metrics may not be reliable indicators of code understandability. In this study, developers' intent in improving code quality is leveraged to analyze the differences in size and static source code metrics between quality-improving changes and unrelated changes. The results show that quality-improving commits are smaller and perfective changes have a positive impact on static source code metrics, while corrective changes tend to add complexity.
EMPIRICAL SOFTWARE ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Zijie Huang, Huiqun Yu, Guisheng Fan, Zhiqing Shao, Mingchen Li, Yuguo Liang
Summary: Explainable Artificial Intelligence (XAI) provides explanations for black-box models, but it may produce unreasonable explanations for software defect prediction. To address this issue, researchers evaluated XAI for code smell prioritization and found that features adapted to developers' expectations can improve explanation coverage without negative impact on accuracy and complexity.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Software Engineering
Hammam M. AlGhamdi, Cor-Paul Bezemer, Weiyi Shang, Ahmed E. Hassan, Parminder Flora
Summary: Load testing of large-scale systems is crucial but time-consuming. Previous work has successfully reduced execution time but missed important information by ignoring combinations of performance metrics. In this paper, a new approach is proposed to detect when new combinations of observed performance metrics are no longer exercised, thereby reducing the execution time of load tests.
JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS
(2023)
Article
Chemistry, Analytical
Ahmed Saad Elkorany, Alyaa Nehru Mousa, Sarosh Ahmad, Demyana Adel Saleeb, Adnan Ghaffar, Mohammad Soruri, Mariana Dalarsson, Mohammad Alibakhshikenari, Ernesto Limiti
Summary: In this paper, a planar patch antenna for mobile communication applications operating at multiple frequencies is proposed. The antenna demonstrates good performance and can be utilized in various mobile applications such as digital communication systems, WiMAX, and WLAN.
Article
Infectious Diseases
Yazeed A. Raouf, Jemma Wadsworth, Abdelghani Bin-Tarif, Ashley R. Gray, Mohammed Habiela, Ameera A. Almutalb, Hanan Yousif, Maysa Ragab, Wefag Alfouz, Nussiba H. Ahmed, Inas Ibrahim, Ahmed M. Hassan, Markos Tibbo, Ahmad M. Almajali, Cornelis van Maanen, Nicholas A. Lyons, Donald P. King, Nick J. Knowles
Summary: This study aims to understand the epidemiological patterns of foot-and-mouth disease (FMD) in Sudan and its connections to neighboring countries by analyzing the genetic sequences of FMD viruses collected from samples in Sudan. The study found that FMDV lineages were maintained within Sudan and showed connections to FMD outbreaks in neighboring countries in East and North Africa. This study highlights the importance of continued FMD surveillance and improving our understanding of epidemiological risks in the region.
TRANSBOUNDARY AND EMERGING DISEASES
(2022)
Article
Biochemical Research Methods
Annie Zhou, Alankrit Tomar, Ahmed M. Hassan, Andrew K. Dunn, Shaun A. Engelmann, Samuel A. Mihelic
Summary: We present a simple and affordable two-photon microscope design that features both galvo-galvo and resonant-galvo scanning capabilities. We quantitatively compare the signal-to-noise ratios and imaging speeds of these two scanning modes in murine neurovascular imaging. Under shot-noise limited detection, both scanning modes perform as expected and achieve comparable signal-to-noise ratios. Resonant-galvo scanning can achieve the desired signal-to-noise ratios in less acquisition time when higher excitation power is used. Under equal excitation power and total pixel dwell time, galvo-galvo scanning outperforms resonant-galvo scanning in image quality when detection deviates from being shot-noise limited.
BIOMEDICAL OPTICS EXPRESS
(2022)
Article
Engineering, Chemical
Mahmoud A. Mossa, Mahmoud K. Abdelhamid, Ahmed A. Hassan, Nicola Bianchi
Summary: The present paper introduces an effective control system to enhance the dynamics of a doubly fed induction generator (DFIG). The control system is evaluated and compared with other control techniques, including stator voltage-oriented control (SVOC), model predictive current control (MPCC), and model predictive direct torque control (MPDTC). The results show that the proposed predictive voltage control (PVC) algorithm outperforms the other techniques in terms of dynamic response, control structure simplicity, and computational burden reduction.
Article
Medicine, General & Internal
Sherif A. El-Kafrawy, Mai M. El-Daly, Ahmed M. Hassan, Steve M. Harakeh, Thamir A. Alandijany, Esam Azhar
Summary: In this study, a rapid, simple, and sensitive RT-LAMP assay for the detection of SARS-CoV-2 in clinical samples was established. The assay is suitable for point of care detection in public hospitals, medical centers in rural areas, and in transportation hubs.
Article
Management
Ahmed Hassan, Mohamed Elmaghrabi, Bruce Burton, Theresa Dunne
Summary: The purpose of this study is to provide a detailed descriptive account and analysis of corporate internet reporting (CIR) practices among non-financial companies listed on the Egyptian Exchange (EGX) at two points in time - December 2010 (pre) and December 2013 (peri) political and social unrest in Egypt. The findings suggest that listed companies in Egypt have embraced internet as a disclosure channel, with significant increase in the extent of these practices over the investigated period. The variations in CIR practices were dependent on changing institutional actors and the time factor was identified as particularly important for inducing diffusion of corporate practices during periods of institutional change.
INTERNATIONAL JOURNAL OF ORGANIZATIONAL ANALYSIS
(2023)
Article
Computer Science, Software Engineering
Jiahuei Lin, Haoxiang Zhang, Bram Adams, Ahmed E. Hassan
Summary: This paper empirically studies how high-severity bugs are fixed in upstream packages for two Linux distributions, Debian and Fedora. The results show that most bugs in Debian do not have explicit information about being fixed, and upstream fixed bugs require users to wait longer and provide more information compared to fixing them locally. Additionally, the number of bug comment links and the similarity score between upstream and distribution bug reports are important factors for the likelihood of a bug being fixed upstream. Traceability tools are needed to make upstream fixes easier and lower the cost of upstream bug management.
EMPIRICAL SOFTWARE ENGINEERING
(2022)
Article
Virology
Arwa A. Faizo, Fadi S. Qashqari, Sherif A. El-Kafrawy, Osamah Barasheed, Majed N. Almashjary, Mohammed Alfelali, Asma A. Bawazir, Boshra M. Albarakati, Soud A. Khayyat, Ahmed M. Hassan, Thamir A. Alandijany, Esam Azhar
Summary: This study investigated the effectiveness of COVID-19 vaccines in individuals with different degrees of obesity and found a slight reduction in the rate and titer of neutralizing antibodies among obese individuals. This suggests that obesity may affect the effectiveness of COVID-19 vaccines.
JOURNAL OF MEDICAL VIROLOGY
(2023)
Article
Computer Science, Software Engineering
Mahmoud Alfadel, Diego Elias Costa, Emad Shihab, Bram Adams
Summary: The reliance on vulnerable dependencies poses a significant threat to software systems. Many dependency vulnerabilities remain undisclosed for a long time until they are discovered and publicly known. In our large-scale empirical study of 6,546 Node.js applications, we found that the majority of the affected applications rely on undisclosed vulnerabilities, but a significant percentage (4.63%) are exposed to dependencies with public vulnerabilities. The main reason for the exposure to public vulnerabilities is the lack of dependency updates and failure to patch available fixes by application maintainers. Additionally, we found that applications remain affected by public vulnerabilities for an average of 103 days. To address these issues, we developed DepReveal, a tool that helps developers better understand vulnerabilities in their application dependencies and plan project maintenance.
ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY
(2023)
Article
Computer Science, Software Engineering
Armstrong Foundjem, Ellis E. Eghan, Bram Adams
Summary: This paper performs a socio-technical analysis of cross-community collaboration in the OpenStack SECO. The study finds that distributors play a significant role in the sustainability of the SECO, with diversity and synchronization being important aspects.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2023)
Article
Computer Science, Information Systems
Ahmed S. Elkorany, Mohamed Marey, Khaled M. Almustafa, Zeinab F. Elsharkawy
Summary: In this paper, two automated breast cancer classification approaches based on the hybridization of the Whale Optimization Algorithm and Dragonfly Algorithm with Radial Basis Function Kernel Support Vector Machines were proposed. The effectiveness of these approaches was tested on two breast cancer databases and compared to other classifiers. The results showed improved performance compared to previous classification methods.
Article
Chemistry, Physical
Ahmed E. Hassan, Mai S. A. Hussien, Mohamed Hammad Elsayed, Mohamed Gamal Mohamed, Shiao-Wei Kuo, Ho-Hsiu Chou, Ibrahim S. Yahia, Genxinag Wang, Zhenhai Wen
Summary: In this study, a novel type of tridoped g-C3N4 bifunctional photocatalyst was prepared via a simple and low-cost thermal polymerization technique. The photocatalyst exhibited a significant enhancement in photocatalytic redox efficiency for H-2 production and degradation of pollutants under visible light. The study also investigated the influence of Y3+ concentration on the photocatalytic performance and electronic structure of the photocatalyst.
SUSTAINABLE ENERGY & FUELS
(2022)
Article
Construction & Building Technology
Daniel Efurosibina Attoye, Kheira Anissa Tabet Aoul, Ahmed Hassan
Summary: This study investigates the challenges of adopting innovations in buildings and renewable energy technology, highlighting the conflicts between the need for innovation and the financial burden and complex adoption processes. Through interviews with residents in the UAE, the study focuses on the limited adoption of Building Integrated Photovoltaics (BIPV) and identifies multiple barriers to its adoption. The findings also reveal a debate between proponents of mandatory policies for innovation adoption and those who argue that these policies are ineffective due to existing barriers. To address this debate, the study proposes a systematic approach with specific drivers and supporting policies to guide a stakeholder-driven renewable energy transition.
Article
Computer Science, Information Systems
Demyana A. Saleeb, Rehab M. Helmy, Nihal F. F. Areed, Mohamed Marey, Khaled Mohamad Almustafa, Ahmed S. Elkorany
Summary: This paper proposes the use of a circularly polarized patch antenna array and microwave techniques to detect kidney cancer. The method is safe, compact, fast, inexpensive, and non-invasive, with no ionizing radiation during measurement.
