Article
Computer Science, Software Engineering
Neelofar Neelofar, Kate Smith-Miles, Mario Andres Munoz, Aldeida Aleti
Summary: Search-based software testing (SBST) is a mature area with techniques developed to tackle the challenging task of software testing. SBST techniques have been successfully applied in the industry to generate test cases for large and complex software systems. However, their effectiveness depends on the problem being addressed. This paper revisits the evaluation of SBST techniques using Instance Space Analysis (ISA) to visualize and assess their strengths and weaknesses across a broad range of problem instances from common benchmark datasets. The paper also examines the diversity and quality of benchmark datasets used in experimental evaluations.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2023)
Article
Green & Sustainable Science & Technology
Sadia Ali, Yaser Hafeez, Mamoona Humayun, N. Z. Jhanjhi, Rania M. Ghoniem
Summary: Component-based software development has gained popularity in recent decades. However, current component delivery only involves interface specifications, making the selection and integration of suitable components for building new systems complicated. This study aims to identify essential attributes and information sources in component-based development and proposes a framework to improve the development process. Experimental results show that the proposed framework enhances component specification and validation, outperforming other methods in terms of accuracy and fault identification rate.
Article
Computer Science, Software Engineering
Ezekiel Soremekun, Sakshi Udeshi, Sudipta Chattopadhyay
Summary: Software often produces biased outputs, especially machine learning-based software when processing discriminatory inputs. To address this issue, we propose a grammar-based fairness testing approach that generates discriminatory inputs to reveal and explain biases in software systems, and improves fairness through fault diagnosis.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2022)
Article
Computer Science, Software Engineering
Anjana Perera, Aldeida Aleti, Burak Turhan, Marcel Bohme
Summary: This paper proposes a new SBST technique called PreMOSA, which combines coverage information with defect prediction information to determine where to increase test coverage in the CUT. Experimental results show that PreMOSA is more effective and efficient than DynaMOSA in detecting bugs, detecting up to 8.3% more bugs on average.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2023)
Article
Computer Science, Information Systems
Onur Kilincceker, Alper Silistre, Fevzi Belli, Moharram Challenger
Summary: The proposed approach introduces a novel way of software testing for graphical user interfaces, aiming to show both the presence and absence of faults. It utilizes positive and negative testing concepts to build a holistic view, modeling GUIs with finite state machines and converting them to regular expressions for test case generation. Test selection and coverage criteria are then used to assess the adequacy and efficiency of the positive tests, while systematically mutating the FSMs for negative tests to model faults and demonstrate their absence.
Review
Computer Science, Information Systems
Mirko Farina, Anna Gorb, Artem Kruglov, Giancarlo Succi
Summary: This study aims to discover technologies for building Goal-Question-Metrics (GQM) based metrics recommender system for software developers. Through a systematic literature review, the study analyzed the components of recommender systems, including data sets, algorithms, and recommendations. The study found that there are currently no recommendation systems developed for processing metrics.
Article
Computer Science, Information Systems
Mutlu Beyazit, Tugkan Tuglular, Dilek Ozturk Kaya
Summary: One way to develop fast, effective, and high-quality software products is to reuse previously developed software components and products. The software product line (SPL) approach can make reuse more effective in the case of a product family. This paper proposes an incremental model-based approach to test products in SPLs by utilizing event-based behavioral models.
Article
Computer Science, Software Engineering
Matteo Biagiola, Paolo Tonella
Summary: This article presents a method to test the plasticity of reinforcement learning-based systems. It quantifies the adaptation and anti-regression capabilities of the system by computing its adaptation frontier in a changed environment. Visualizing the results provides developers with crucial information for deciding whether to enable online learning or not.
ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY
(2022)
Article
Materials Science, Composites
B. V. S. R. N. Santhosi, K. Ramji, N. B. R. Mohan Rao, Dora Nagaraju, M. K. Naidu
Summary: An effective nanocomposite-based microwave absorber made of polyurethane/graphene/glass/epoxy with different weight percentages of graphene (0 to 2.5 wt%) is proposed. Experimental investigation and numerical modeling are conducted to analyze the performance of the absorber. The experimental results show that the absorber has over 90% absorption capability in a broad bandwidth, with maximum reflection loss occurring at 12.1 GHz.
PLASTICS RUBBER AND COMPOSITES
(2023)
Article
Plant Sciences
Chen Gong, Fujun Chen, Can Kang
Summary: An image processing method was used to measure droplet size distributions for different spray pressures and nozzle configurations in oil-based emulsion spray. The measured results validated a theoretical model based on the characteristics of spray sheets, which showed that oil-based emulsion spray forms a web structure constituted by perforations. The proposed theoretical model is based on nozzle exit size, spray sheet angle, and perforation number, and has a good consistency with the measured droplet size distribution.
FRONTIERS IN PLANT SCIENCE
(2023)
Article
Engineering, Electrical & Electronic
Hamdy Abdelhamid, Amgad El-Deib, Khalil ElKhamisy, Khaled El-Shekh, Zulfiqar Memon
Summary: This paper introduces a simple, compact, and accurate model for PV that takes into account both irradiance and temperature variations. It examines the effect of semiconductor parameters on the model and verifies its accuracy experimentally. An integrated module using Simulink simulation with an error of about 1% compared to experimental results is also introduced.
OPTICAL AND QUANTUM ELECTRONICS
(2022)
Article
Mathematical & Computational Biology
Max Westphal, Antonia Zapf, Werner Brannath
Summary: The study presents a multiple testing framework for disease diagnostic accuracy studies with sensitivity and specificity as co-primary endpoints. It challenges the common recommendation of strict separation between model selection and evaluation, and demonstrates that evaluating multiple promising diagnostic models simultaneously can lead to better final models.
STATISTICS IN MEDICINE
(2022)
Article
Cell Biology
Yingjie Guo, Chenxi Wu, Zhian Yuan, Yansu Wang, Zhen Liang, Yang Wang, Yi Zhang, Lei Xu
Summary: This article introduces a gene-based method to detect gene-gene interactions by adding additive constraints to the model, and experimental results show that this method outperforms previous experiments in detecting gene-gene interactions.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
Article
Computer Science, Information Systems
Malik Muhammad Ali Shahid, Shahida Sulaiman, Mohammed Al-Sarem, Aqeel Ur Rahman, Salman Iqbal, Rab Nawaz Bashir, Arfat Ahmad Khan, Momen M. Alrawi, Rashiq R. Marie, Settawit Poochaya
Summary: Conventionally, web portal reliability is validated using conventional methods, but these methods are not effective. This paper proposes the inclusion of quality factors like usability in addition to conventional testing to improve reliability. Testing profiles, including software operational profile, input space profile, and usability profile, are employed to measure reliability. The proposed scheme is compared with the conventional method and the results show its effectiveness, providing recommendations for testing and measuring reliability in web-based software or applications.
CMC-COMPUTERS MATERIALS & CONTINUA
(2023)
Article
Computer Science, Software Engineering
Christian Birchler, Sajad Khatiri, Bill Bosshard, Alessio Gambi, Sebastiano Panichella
Summary: Simulation platforms are efficient and safe for testing emerging Cyber-Physical Systems like self-driving cars. However, thoroughly testing self-driving cars in simulated environments is challenging due to the large number of test cases. In this paper, we propose an approach called SDC-Scissor that uses machine learning to skip unnecessary test cases and improve cost-effectiveness. Evaluation results show that SDC-Scissor outperforms baseline strategies and can be applied in industrial settings.
EMPIRICAL SOFTWARE ENGINEERING
(2023)
Review
Computer Science, Artificial Intelligence
Paulo Sergio M. Dos Santos, Guilherme H. Travassos
KNOWLEDGE ENGINEERING REVIEW
(2016)
Article
Computer Science, Software Engineering
Marcos Kalinowski, David N. Card, Guilherme H. Travassos
Article
Computer Science, Software Engineering
T. Conte, J. Massolar, E. Mendes, G. H. Travassos
Article
Computer Science, Information Systems
Rodrigo Oliveira Spinola, Guilherme Horta Travassos
INFORMATION AND SOFTWARE TECHNOLOGY
(2012)
Article
Computer Science, Information Systems
Rebeca C. Motta, Kathia M. de Oliveira, Guilherme H. Travassos
INFORMATION AND SOFTWARE TECHNOLOGY
(2019)
Article
Computer Science, Software Engineering
Fabio de A. Farzat, Marcio de O. Barros, Guilherme H. Travassos
Summary: This paper introduces an evolutionary program improvement technique to reduce the size of JavaScript programs, with experimental results showing a relationship between the quality of a program's test suite and its ability to reduce the source code size.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2021)
Article
Computer Science, Software Engineering
Xavier Franch, Daniel Mendez, Andreas Vogelsang, Rogardt Heldal, Eric Knauss, Marc Oriol, Guilherme H. Travassos, Jeffrey C. Carver, Thomas Zimmermann
Summary: Practitioners generally perceive Requirements Engineering (RE) research as essential or worthwhile, but there is still a higher percentage of non-positive ratings. Factors influencing perception of relevance include research's links to industry, research methods, and respondents' roles. Positive perceptions are mainly related to problem relevance and solution soundness, while negative perceptions are more varied.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Cecilia Apa, Martin Solari, Diego Vallespir, Guilherme Horta Travassos
Summary: Technical debt (TD) refers to the lack of internal quality that directly affects software evolution. This paper presents the results of a survey replication in the Uruguayan software industry, which aims to characterize the understanding, perception, and adoption of TD management (TDM) activities among software industry professionals. The results reveal different levels of awareness and perception of TD among participants from different backgrounds, such as startups, government, and job roles. The findings suggest the need for further research efforts in other software engineering communities to address the specific TD challenges and needs of different organizational contexts.
INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING
(2023)
Article
Computer Science, Software Engineering
Rebeca C. Motta, Kathia M. de Oliveira, Guilherme H. Travassos
Summary: This study presents an evidence-based roadmap for IoT development, which supports developers in specifying, designing, and implementing IoT systems. Based on experimental studies and multidisciplinary knowledge, the roadmap consists of 117 items organized into 29 categories, addressing various concerns in each aspect. The study also validates the applicability of the roadmap through an observational study of a real healthcare IoT project.
JOURNAL OF SYSTEMS AND SOFTWARE
(2023)
Proceedings Paper
Computer Science, Information Systems
Bruno P. de Souza, Paulo Sergio M. dos Santos, Guilherme H. Travassos
Summary: Modern information systems require the use of contemporary software systems, which face challenges in construction, maintainability, and evolution, as well as managing dependencies among various actors and components. Continuous Experimentation (CE) is proposed as a solution to mitigate these risks and improve the engineering of CSS. However, there are challenges and gaps in implementing CE for CSS engineering, calling for further investigation and development of software technologies and guidance.
PROCEEDINGS OF THE 19TH BRAZILIAN SYMPOSIUM ON INFORMATION SYSTEMS
(2023)
Proceedings Paper
Computer Science, Software Engineering
Andrea Cristina de Souza Doreste, Guilherme Horta Travassos
Summary: Context-Aware Software Systems (CASS) need to be prepared to handle context and its variations, but currently there is a lack of software technologies to support their testing. CATS# is a testing technique that helps specify test cases for CASS and its initial feasibility was demonstrated in an undergraduate project.
PROCEEDINGS OF THE 21TH BRAZILIAN SYMPOSIUM ON SOFTWARE QUALITY, SBOS 2022
(2022)
Proceedings Paper
Computer Science, Software Engineering
Nicolli Rios, Rodrigo Spinola, Guilherme H. Travassos
Summary: The study investigates how technical debt is perceived, identified, and managed in IoT software projects by examining two specific projects. By applying a management strategy, 153 TD items clustered into 16 types (including three new ones) and 75 effects due to their presence were identified.
PROCEEDINGS OF THE 21TH BRAZILIAN SYMPOSIUM ON SOFTWARE QUALITY, SBOS 2022
(2022)
Article
Engineering, Multidisciplinary
Francisco J. Pino, Mario Piattini, Guilherme Horta Travassos
REVISTA FACULTAD DE INGENIERIA-UNIVERSIDAD DE ANTIOQUIA
(2013)
Proceedings Paper
Engineering, Multidisciplinary
Bruno Allison Araujo, Gabriel Dias Travassos, Antonio Almeida Silva, Eudesio Oliveira Vilar, Jorge Palma Carrasco, Carlos Jose Araujo
ADVANCED COMPUTATIONAL ENGINEERING AND EXPERIMENTING
(2011)
Article
Computer Science, Information Systems
Hao Ren, Yanhui Li, Lin Chen, Yuming Zhou, Changhai Nie
Summary: This study aims to explore the breakable blocking bugs (BBBs) through quantitative and qualitative analysis. The analysis reveals that BBBs have higher levels of involvement, longer fix time, and more complex source code compared to other bugs. The study also identifies four reasons for breaking blocking relationships between bugs and three measures adopted by developers to break these relationships.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Chunyong Zhang, Tianxiang Yu, Bin Liu, Yang Xin
Summary: This paper proposes a vulnerability detection framework based on federated learning (VDBFL), which combines code property graph, graph neural networks, and convolutional neural networks to detect vulnerability code. The experimental results show that this method outperforms other vulnerability detection methods.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Martin Stancek, Ivan Polasek, Tibor Zalabai, Juraj Vincur, Rodi Jolak, Michel Chaudron
Summary: The aim of this research is to support distributed software design activities in Virtual Reality (VR). Using design science research methodology, a tool for collaborative design in VR is designed and evaluated. The efficiency of collaboration and recall of design information when using VR software design environment compared to non-VR environment are evaluated. Furthermore, the perceptions and preferences of users are collected to explore the opportunities and challenges of using VR software design environment.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Zhen Yang, Jacky Wai Keung, Zeyu Sun, Yunfei Zhao, Ge Li, Zhi Jin, Shuo Liu, Yishu Li
Summary: This paper presents MetaCoder, a meta-learning code generation approach that efficiently extracts general-purpose knowledge from large-scale source languages and rapidly adapts to domain-specific scenarios.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Pilsu Jung, Seonah Lee, Uicheon Lee
Summary: This study proposes an automated code-based approach (ActSPL) for reusing SPL test cases by utilizing source code and test cases. The results show that ActSPL achieves high precision and recall, and significantly reduces the time required for testing a new product.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Chao Liu, Runfeng Cai, Yiqun Zhou, Xin Chen, Haibo Hu, Meng Yan
Summary: This paper conducts an empirical study on the implementation issues of deep learning frameworks, focusing on relevant questions on Stack Overflow. The study identifies various implementation issues and constructs a taxonomy, revealing that data processing, model setting, model training, and model prediction are the most common categories. The paper also provides suggestions for future research and aims to help developers and researchers understand these issues better.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Muhammad Azeem Akbar, Arif Ali Khan, Mohammad Shameem, Mohammad Nadeem
Summary: This study identifies key variables in quantum software development (QSD) and develops a model for predicting the success probability of QSD projects. The results show that as the QSD process matures, project success probability significantly increases and costs are notably reduced. The developed prediction model can help practitioners focus on key areas for successful implementation of QSD projects.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Md. Shamsujjoha, John Grundy, Hourieh Khalajzadeh, Qinghua Lu, Li Li
Summary: This paper investigates the challenges and benefits of incorporating human aspects into eHealth app development and usage from the perspectives of developers and end-users. The study used a mixed-method approach and gathered data from online surveys and interviews. The findings suggest that addressing human aspects throughout the app development life-cycle is beneficial for more effective eHealth apps.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Yuchao Jiang, Boualem Benatallah, Marcos Baez
Summary: This paper reports on interviews and surveys with early-stage researchers (ESRs) and explores the potential of online research communities in supporting ESRs to learn from diverse perspectives and experiences. The results reveal the limited adoption of research communities for learning and identify unmet needs in their design. Design implications for future socio-technical systems are provided to support the development of research skills.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Jyoti Prakash Meher, Sourav Biswas, Rajib Mall
Summary: Accurate bug classification is important for speeding up bug triage, code inspection, and repair tasks. To improve classification, this study proposes a novel bug classification approach based on deep learning. The approach includes building a bug taxonomy with eight bug classes using keywords, annotating a large set of bug resolution reports, and utilizing attention-based classification techniques. Experimental results show that the proposed technique outperforms existing methods in terms of F1-Score by an average of 16.88% on the considered dataset.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Rodrigo Santos, Eleni Constantinou, Pablo Antonino, Jan Bosch
Summary: In the last decade, software engineering has faced challenges beyond technical aspects. The field now considers technological, organizational, and social aspects together in research and practice to handle complexity and provide solutions to the industry's demands. Systems-of-systems (SoS) and software ecosystems (SECO) have emerged as topics of interest, bringing together researchers and practitioners to understand how to manage and engineer software-intensive systems in modern, complex, distributed, dynamic, and open environments.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Article
Computer Science, Information Systems
Zhuo Wu, Zan Wang, Junjie Chen, Hanmo You, Ming Yan, Lanjun Wang
Summary: In this paper, a statistical method called Stratified random Sampling with Optimum Allocation (SSOA) is proposed to provide an unbiased estimation of model accuracy with the smallest estimation variance. The unlabeled test set is first divided into strata based on predictive confidences. Then, two stratum accuracy variance estimation methods are designed to allocate the given budget to each stratum based on the optimum allocation strategy. Multiple experiments are conducted to evaluate the effectiveness and stability of SSOA by comparing it with baseline methods.
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
Review
Computer Science, Information Systems
Jorge Chueca, Javier Veron, Jaime Font, Francisca Perez, Carlos Cetina
INFORMATION AND SOFTWARE TECHNOLOGY
(2024)
