A Technique for Enabling and Supporting Debugging of Field Failures

The rapid development of China’s e-commerce industry has led to the rise of China’s second-hand car e-commerce. With the increasingly rich trust theory and the rapid development of e-commerce platforms, the issue of online consumer trust has attracted more and more scholars’ attention. This paper takes China’s B2C second-hand car e-commerce platforms as an example, combines the second-hand car research conclusions and consumer trust theory, and conducts a systematic study on the formation of consumer trust in second-hand car e-commerce platforms. Based on the trust of individual consumers, system environment, website/APP and platform companies, this paper explores the influencing factors of consumer trust and constructs the influencing factors model of trust formation. The empirical study was conducted by using the structural equation model and multiple regression to verify the degree of fitting of the theoretical hypothesis and the model. The research results have a certain reference value for the development of second-hand car e-commerce platforms.

Memory for deictic elements in sentences

The heterogeneity and dynamism of today's software systems make it difficult to assess the performance, correctness, or security of a system outside the actual time and context in which it executes. As a result, there is an increasing interest in techniques for monitoring and dynamically analyzing the runtime behavior of an application. These techniques are usually implemented using ad-hoc solutions that result in tools that are hard to develop, maintain, and reuse. To address this problem, we present a generic framework that enables the collection of different kinds of runtime information, such as data about the execution of various code entities and constructs. The framework lets users easily define how to process the collected information and is extensible to collect new types of information. We implemented the framework for the Java language as a set of Eclipse plugins. The plug-ins provide an intuitive GUI through which the functionality of the framework can be exploited. We also present an example of use of our framework and plugins that helps illustrate their functionality and shows their ease of use.

Big Data computing platform has evolved to be a multi-tenant service. The service quality matters because system failure or performance slowdown could adversely affect business and user experience. To date, there is few study in literature on service quality issues of production Big Data computing platform. In this paper, we present an empirical study on the service quality issues of Microsoft ProductA, which is a company-wide multi-tenant Big Data computing platform, serving thousands of customers from hundreds of teams. ProductA has a well-defined escalation process (i.e., incident management process), which helps customers report service quality issues on 24/7 basis. This paper investigates the common symptom, causes and mitigation of service quality issues in Big Data platform. We conduct a comprehensive empirical study on 210 real service quality issues of ProductA. Our major findings include (1) 21.0% of escalations are caused by hardware faults; (2) 36.2% are caused by system side defects; (3) 37.2% are due to customer side faults. We also studied the general diagnosis process and the commonly adopted mitigation solutions. Our study results provide valuable guidance on improving existing development and maintenance practice of production Big Data platform, and motivate tool support.

Purpose – Personal projects are any kind of projects whose management is left to an individual untrained in project management and is greatly influenced by this individual’s personal touch. This includes the majority of knowledge workers who daily manage information relating to several personal projects. The authors have conducted an in-depth qualitative investigation on information management of such projects and the tacit knowledge behind its processes that cannot be found in the organisational structures of current personal information management (PIM) tools (file managers, e-mail clients, web browsers). The purpose of this paper is to reveal and understand project information management practices in details and provide guidelines for personal project management tools. Design/methodology/approach – Semi-structured interviews similar to that in several other PIM exploratory studies were carried out focusing on project fragmentation, information overlap and project context recreation. In addition, the authors enhanced interviews with sketching approach not yet used to study PIM. Sketches were used for articulating things that were not easily expressed through words, they represented a time stamp of a project context in the projects’ lifetime, uncovered additional tacit knowledge behind project information management not mentioned during the interviews, and were also used to find what they have in common which might be used in prototype designing. Findings – The paper presents first personal project definition based on the conceptualisations derived from the study. The study revealed that the extensive information fragmentation in the file hierarchy (due to different organisational needs and ease of information access) poses a significant challenge to context recreation besides cross-tool fragmentation so far described in the literature. The study also reveals the division of project information into core and support and emphasises the importance of support information in relation to project goals. Other findings uncover the division of input/output information, project overlaps through information reuse, storytelling and visualising information relations, which could help with user modelling and enhancing project context recreation. Research limitations/implications – On of the limitations is the group of participants that cannot represent the ideally generalised knowledge worker as there are many different kinds of knowledge workers and they all have different information needs besides different management practices. However, participants of variety of different backgrounds were observed and the authors converged observations into points of project information management similarities across the spectrum of different professions. Nevertheless, its observations and conceptualisations should be repeatable. For one, some of the issues that emerged during this work have been to different extents discussed in other studies. Practical implications – The empirical findings are used to create guidelines for designing personal project information management tools: support the selective focus on information with the division into core and supportive information; visualise changes in project information space to support narratives for context recreation; overcome fragmentation in the file system with selective unification; visualising project’s information relationship to better understand the complexity of project information space; and support navigating in project information space on two axes: time and between projects (overlaps through information). Originality/value – The study presents a longitudinal insight into personal project information management. As such it provides a first formal definition of personal project from the information point of view. The method used in the study presented uses a new approach – sketching in which participants externalised and visualised personal information and projects they discussed. The insights derived from the study form design implications for personal project management tools for knowledge workers.

Background: The rapid development of short-form video platforms has transformed university students’ media consumption patterns and given rise to a new digital learning ecology in higher education. Although short-form videos are frequently used as sources of informal learning, their fast-paced, repetitive, and highly stimulating characteristics raise concerns about students’ ability to maintain sustained attention, which is a crucial prerequisite for academic language comprehension. However, empirical studies that integrate short-form video consumption, attentional focus, and language comprehension within a single, comprehensive explanatory model remain limited, particularly in the context of Indonesian higher education. Objective: This study aims to analyze the effect of short-form video consumption on university students’ language comprehension and to examine the role of attentional focus as a mediating variable in this relationship. Method: This study employed an explanatory quantitative approach with a cross-sectional survey design. Data were collected from 312 undergraduate students enrolled in Indonesian higher education institutions using a Likert-scale questionnaire. Data analysis was conducted using descriptive statistics, multiple regression analysis, and mediation testing with a bootstrapping approach. Results: The findings indicate that short-form video consumption has a significant negative effect on students’ language comprehension. In addition, short-form video consumption negatively affects attentional focus, while attentional focus has a positive and significant effect on language comprehension. Mediation analysis demonstrates that attentional focus serves as a partial mediator in the relationship between short-form video consumption and language comprehension. Conclusion: This study concludes that short-form video consumption not only has a direct impact on university students’ language comprehension but also exerts an indirect effect through a reduction in sustained attentional focus.

Online education has been developing since the 1990s, and many traditional education institutions have begun to explore online education development models. Therefore, this paper aims to study the new profit model of B2C online education and improve user stickiness and intention to pay, promoting the healthy development of B2C online education platforms. This paper uses a combination of structural equation model and artificial neural network prediction to conduct empirical research. 557 valid questionnaires were collected, and data analysis was performed using SPSS24.0 and Amos22.0. The research results show that perceived utilitarian value, Word-of-Mouth, and personalization have a positive effect on MOOC continuance intention, which then have a positive effect on willingness to pay with perceived price fairness. The innovation of this research is to build a structural equation model by reading the literature, and then combine it with artificial neural network methods. Few scholars in the field of B2C online education used two empirical methods. The research of this paper is specifically targeted at B2C online education companies, and the results have important guiding effects in this field.

The actual competitive context is stressing the importance of knowledge management (KM) enhancing organizational performance through the creation, sharing and reuse of knowledge.

Security throughout the software development lifecycle is the prime concern in the current software engineering, thus giving rise to a natural evolution, DevSecOps, from DevOps. It, from the very outset of development, integrates security into the whole process and ensures its way into every phase of the software delivery pipeline, as opposed to the earlier paradigms of software development that would always consider security as an afterthought. Using a systematic literature review and an empirical study, this research investigates the influences of DevSecOps practices on quality, security, and organizational factors impacting software. The findings indicate that DevSecOps dramatically improves the security of software because it allows vulnerabilities to be identified and mitigated early on, thus redounding to the improved reliability of code while also reducing the attack surface. Automation here uses force to enable continuous security monitoring, automated vulnerability scanning, and rapid incident response. Continuous Integration and Continuous Deployment (CI/CD) pipelines promote smooth embedment of security checks into the software development workflow, thus reducing the possibility of their being introduced at later stages. However, thus far, most challenges abound its adoption. Many organizations face the challenges with complexity of security tool; they have a steep learning curve for developers implementing DevSecOps; and there is often limited existence of security expertise in development teams. Finding a balance between conflicting issues such as trade-off security, on the one hand, and speed and agility that are the essence of DevOps on the other, continues to be a challenge because, on the one hand, security can slow down development cycles. Resistance to change and the culture of organizations are further barriers to the complete adoption of DevSecOps. Therefore, the recommendations for addressing such problems include industry best practices like automated security testing, regulatory compliance, and culture fostering awareness on security. Organizations should also invest in training programs for developers with respect to security skills and create incentives for collaboration among development, security, and operations. Moreover, AI-based security automation promises to open an avenue through which security efficiency can be improved at high speed of detection of threats and by reducing manual efforts in security testing.

The field of software refactoring has been evolving rapidly, driven by the need to maintain software quality and manage complexity as software systems grow. This special issue of the Journal of Software: Evolution and Process focuses on “Software Refactoring: Application Breadth and Technical Depth,” aiming to promote research that advances our understanding of software refactoring practices and their impact. The selected papers in this issue reflect the broad scope and technical depth of the topic, covering a variety of innovative methodologies, empirical studies, and new tools that push the boundaries of current software refactoring research. The paper “Software Refactoring Side Effects” by AbuHassan, Alshayeb, and Ghouti addresses the often-overlooked side effects of software refactoring. The authors propose three different approaches for handling these side effects and employ a multi-objective optimization algorithm to identify optimal refactoring decisions. Their work enhances the understanding of refactoring's unintended consequences and proposes practical solutions, fitting well into the theme of exploring new dimensions of refactoring practices. Zhao et al., in their article “An Architecture Refactoring Approach to Reducing Software Hierarchy Complexity,” introduce a novel metric to quantify software hierarchy complexity and propose the Complexity-oriented Software Architecture Refactoring (CoSSR) approach. Their study demonstrates how reducing software hierarchy complexity can improve software quality, aligning with the issue's focus on reducing complexity through innovative refactoring techniques. The article “MARS: Detecting Brain Class/Method Code Smell Based on Metric-Attention Mechanism and Residual Network” by Zhang and Dong presents a new method for detecting complex code smells using a novel deep learning approach. By leveraging a metric-attention mechanism and an improved residual network, their model shows superior performance compared to existing methods. This research contributes to the special issue by applying cutting-edge machine learning techniques to refactoring challenges. AlOmar et al.'s study, “Behind the Scenes: On the Relationship Between Developer Experience and Refactoring,” investigates the correlation between developer experience and refactoring activities across 800 open-source projects. Their findings highlight that experienced developers tend to perform more varied refactoring operations but document less of their refactoring activities. This study offers a new perspective on how human factors influence refactoring practices, enriching the broader conversation on effective software evolution. In “A Study of Refactorings During Software Change Tasks,” Eilertsen and Murphy explore the reasons behind the disuse of refactoring tools during software change tasks. Their observational study reveals that the strategies developers use significantly impact the use of refactoring tools, pointing to a gap between available tool support and actual developer needs. This paper provides valuable insights into the practical challenges of implementing refactoring in real-world settings. Halepmollasi and Tosun, in “Exploring the Relationship Between Refactoring and Code Debt Indicators,” present an empirical analysis of the association between different types of refactorings, code smells, and faults. Their findings challenge previous assumptions about refactoring's impact on code smells and suggest that refactoring activities might be more fault-inducing than previously thought. This research adds a critical dimension to understanding the effects of refactoring on software quality. Lastly, Abdou and Darwish's article, “Severity Classification of Software Code Smells using Machine Learning Techniques: A Comparative Study,” evaluates various machine learning models for classifying the severity of code smells. Their use of the LIME algorithm for model interpretability provides new insights into predicting code smell severity, contributing to the issue's exploration of data-driven approaches to software maintenance. Recent developments in generative AI and machine learning have opened new avenues for advancing software refactoring practices. As demonstrated by some of the studies in this issue, these technologies can automate and enhance refactoring processes, improve tool support, and provide more accurate code smell detection. The application of AI in this domain is still in its early stages, but it holds great promise for transforming how software systems are maintained and evolved. We encourage researchers to explore these emerging trends further, focusing on integrating AI-driven approaches with traditional software engineering practices. We extend our sincere appreciation to all the authors for their contributions, to the peer reviewers for their invaluable feedback and dedication, and to the editorial board members for their support in assembling this special issue. Together, these efforts have created a diverse collection of research that we believe will significantly impact the field of software refactoring.

User eXperience (UX) is a key factor in the success of software systems. Many software companies face challenges in their work with UX. Existing research does not analyze UX practices and challenges in relation to other software quality characteristics or, in particular, in relation to usability. A better understanding of these challenges can help researchers and practitioners better address them in the future. In this empirical study, we have interviewed 17 practitioners with different backgrounds and occupations from eight software development companies. Their responses are coded, and analyzed with thematic analysis. We report eight themes of challenges that practitioners face in their work with UX. While some of these challenges partly overlap with those reported in existing literature about usability or other software quality characteristics, the participants of our study either view many of the challenges as unique to UX, or more severe in the case of UX. Although at a superficial level challenges of UX and other quality characteristics overlap, we differentiate these challenges at a deeper level through the five main characteristics of UX: subjective , holistic , dynamic , context-dependent and worthwhile . In particular, we identified that these characteristics have at least 20 implications (i.e. additional difficulties) for day-to-day work of practitioners. We found that 11 of these implications have been previously reported in literature. However, to the best of our knowledge, the remaining nine implications are unique to our study. These implications can explain why practitioners perceive the challenges to be more severe than for other quality characteristics. Most importantly, they can explain the industry’s lopsided focus on the pragmatic aspect of UX. Our findings can be useful for researchers in identifying new and industry-relevant research areas and for practitioners to learn from empirically investigated challenges in UX work, and base their improvement efforts on such knowledge. Identifying and investigating the overlaps underlines the importance of these challenges, and can also help finding research areas not only for enhancing UX work but also software quality in general. It also makes it easier for practitioners to spot, better understand as well as find mitigation strategies for UX, through learning from past experiences and developments in the area of software quality.

Phishing attacks, which leverage effective social engineering techniques to exploit human vulnerabilities, continue to pose significant risks to internet users. This systematic literature review analyzes phishing attack research from 2010 to 2025, focusing on phishing susceptibility among internet users. Following the guidelines outlined by Kitchenham and Charters (2007), the review comprises three primary phases: planning, execution, and reporting. Study questions were formulated using the PICOC framework to examine the types of phishing attacks, the theoretical frameworks applied, the persuasive elements utilized, and the challenges and research gaps present in existing literature. A comprehensive search of ten primary digital databases yielded 23,479 studies, from which 49 empirical studies were selected for analysis based on rigorous inclusion, exclusion, and quality assessment criteria. The review indicates that email-based phishing remains the predominant form of attack, followed by social media, smishing, and vishing. In addition to commonly employed persuasion strategies such as urgency, fear appeal, and authority, the review identifies prominent theoretical frameworks. This paper also highlights significant research gaps, particularly in platform development and unexplored user demographics, and provides recommendations for future phishing-related studies. The findings advocate for the development of robust preventative strategies and enhance the systematic understanding of phishing susceptibility.

Concern about the quality of software is widespread. Reliable data about current practice are hard to get as no one likes to admit that they are producing poor software. In a recent survey, Wilson has taken an approach to obtaining data about the practice of software quality assurance among companies in Australia. The same technique has been used here to investigate practice among companies in Europe and America. The survey ams to investigate quality systems used by the organizations, and the application of these systems by software fevelopers. In this paper they are compared with the Australian experience and the results of the survey shown. The company's demographic data and overall response pattern from this survey are compared with Wilson's. Patterns in software quality assurance programs of organizations are suggested by comparing the management's perspective with that of the developers. The most popular software development techniques identified by the developers are prioritized in the order of their popularity by using a weighting scheme and their implications are discussed.

Architecture erosion (AEr) can adversely affect software development and has received significant attention in the last decade. However, there is an absence of a comprehensive understanding of the state of research about the reasons and consequences of AEr, and the countermeasures to address AEr. This work aims at systematically investigating, identifying, and analyzing the reasons, consequences, and ways of detecting and handling AEr. With 73 studies included, the main results are as follows: (1) AEr manifests not only through architectural violations and structural issues but also causing problems in software quality and during software evolution; (2) non‐technical reasons that cause AEr should receive the same attention as technical reasons, and practitioners should raise awareness of the grave consequences of AEr, thereby taking actions to tackle AEr‐related issues; (3) a spectrum of approaches, tools, and measures has been proposed and employed to detect and tackle AEr; and (4) three categories of difficulties and five categories of lessons learned on tackling AEr were identified. The results can provide researchers a comprehensive understanding of AEr and help practitioners handle AEr and improve the sustainability of their architecture. More empirical studies are required to investigate the practices of detecting and addressing AEr in industrial settings.

The objective of this qualitative case study was to observe and describe how software quality is constructed in software development organizations. Eleven software programmers, testers, quality control personnel, requirement managers and research and development personnel were interviewed and common practices of quality construction analyzed. The findings indicated that quality construction practices vary considerably across different organizations. Differences were noted in the type and extent of customer involvement in software development, methods used for requirements elicitation, and objectives of software testing. Based on the results, the following conclusions are drawn. First, requirements elicitation in software development is an ongoing process even after the product has been delivered to the customer. Second, the quality characteristics of the software depend on the type of software, user and application domain. Third, a quality software product is not necessarily technically the best but it must satisfy customer needs. Fourth, the quality of the software is resource-dependent.