A content analysis process for qualitative software engineering research

We welcome you to the Twenty-Eighth International Conference on Software Engineering and Shanghai, China. This is the first instance of the ICSE conference series to be held in China, and it is an exciting time and place for ICSE 2006. The conference brings researchers, educators, practitioners and students together to present, exchange ideas and engage in discussions about the recent and exciting innovations and research in software engineering. Exciting sessions on practical experience, educational issues, and doctoral and new faculty symposia have been organized. The conference also includes a wide variety of tutorial, workshops and demonstration offerings. Finally, since research and markets in our host country China are continuously growing, ICSE includes a separate Far East Track for discussions on the contributions and challenges of our Chinese colleagues. We trust that this mix will provide interesting and stimulating offerings to all members of our growing community. The technical program committee is pleased to present this conference proceeding that contains the research papers of the technical program for ICSE 2006. The technical program for this conference focuses on new and innovative software engineering contributions in theory, formal methods, system building and empirical studies. The papers represent an alluring array of topics, including software design, architecture, reuse, testing, analysis, processes and formal methods. Because of the growing number of paper submission and the resulting large program committees in the past, we instituted a new two-phase reviewing process this year. Our program committee had 36 members. In the first phase, each submitted paper was reviewed by 3 reviewers: 2 from the program committee and an external reviewer from the software engineering community. We had 265 external reviewers who contributed 370 reviews for this phase. Those papers receiving the best reviews were considered in the second phase. A total of 99 papers entered the second phase. Each of these papers was reviewed by another program committee member. Thus, each accepted paper had a total of 4 reviews (3 reviews from pc members and 1 review from an external reviewer). Each rejected paper had at least 3 reviews. The pc members reviewed 24-25 papers in the two phases, a reasonable number. We feel that this system worked very well. The program committee met for two days in December, 2005 in Frankfurt, Germany. By the end of the meeting, a consensus emerged for the 36 papers in this proceedings (9% of the total submissions). There were many high quality submissions that could not be accommodated in the program; hopefully a revised version will be published elsewhere. In addition to the papers, we organized four invited sessions. One invited session focuses on empirical studies, an increasingly important component of software engineering research and practice. We also have an invited panel that addresses the value and practice of formal methods. Since software engineering techniques are growing in importance in challenging safety critical domains, we included two invited sessions: one on software engineering for automotive engineering and the other on software engineering for assisted living. We are very pleased that a notably diverse and outstanding group of three leaders of the software engineering community have agreed to present keynote speeches. The opening day keynote will be presented by Prof. Yang Fuqing, from Peking University, a woman who has been at the very forefront of the software engineering communities of research and practice in China for decades. Her perspectives on the past and future of software engineering in China will be complemented by a keynote on similar themes presented on the second day. This second keynote will be delivered by Prof. Barry Boehm, from the University of Southern California, USA. His talk will review the history of software engineering research and practice in the West over the past decades, and project it forward into the 21st century. Finally, the keynote speaker on the third day, Mr. Reinhold Achatz, from Siemens Corp., will present a complementary view of software engineering research and practice, as viewed from the perspective of one of the great multinational corporations, based in Europe. We are truly excited at the prospect that these three keynotes will provide a searching multidimensional view of our community at this time of historic convergence of communities. The continued success and high quality of the ICSE conference series would not be possible without the help and support of the software engineering community. First, we would like to gratefully acknowledge and thank all of the authors who submitted papers. We especially thank the program committee members for their efforts and commitments in reviewing the papers and securing reviews from external reviewers. They put in an extraordinary amount of their time to provide thoughtful and knowledgeable reviews. The exceptionally strong technical program represented by the papers in this proceeding could not be possible without their efforts.

Context: In the last years, the Grey Literature (GL) had a notable increase in interest in diverse areas of knowledge. In Software Engineering (SE), with the advance of social media, the SE practitioners are heavy consumers of GL, opposite to traditional research papers, such as the Systematic Literature Review (SLR). Problem: Despite the increase of numbers of SLRs, some researchers claim the lack of connection to the practice of SE, due to the lack of evidence derived from SE practitioners. Goal: Introduce methods and techniques to support a Grey Literature Review (GLR) in SE, aiming to approximate the literature review to the practice of SE. Method: First, we will investigate how secondary studies use GL; Second, we will employ a survey with researchers of SLRs and SE practitioners; Third, we will analyze the use of GL according to the context; Fourth, we will review the GL source in SE; Finally, we will propose a guideline to help SE researchers and practitioners to conduct the GLR. Preliminary findings: We have initiated the tertiary study conducting the manual (4,875 studies) and automatic (6,279 studies) searches. We eliminated those that were not an article, and also those were not written in English, remaining 8,019 potential studies. Currently, we are applying the inclusion and exclusion criteria.

CERSE - Catalog for empirical research in software engineering: A Systematic mapping study

This scientific paper aims to explore the identification and quantification of the knowledge level within a team working on a software engineering project. The knowledge level of a team plays a crucial role in the success and efficiency of project outcomes. To achieve this objective, a comprehensive review of existing literature on knowledge management, team dynamics, and software engineering practices was conducted. This article reveals insights into the knowledge dynamics within software engineering teams. The research methodology consists of different quantitative and qualitative methods for data collection and analysis. The identified knowledge gaps and strengths can inform strategies for improving team performance, such as targeted training programs or knowledge sharing initiatives. Furthermore, the quantification of knowledge levels can serve as a benchmark for future projects, allowing for better resource allocation and team composition. Overall, this research is bringing benefits to the field of software engineering by providing a systematic approach to identify and quantify the knowledge level of teams, enabling organizations to optimize their team structures and enhance project outcomes.

Theory-oriented software engineering

This panel gives a non-standard view of the future of software engineering. Two of the speakers are recent Ph.D. graduates in computer science, with expertise in software engineering, who have taken academic positions; as people who will educate the next generation of software engineering practitioners and researchers, they provide a key vision of the future. The other two speakers are senior, having moved from the research community into a world in which they face the problems of engineering software on a daily basis. Collectively, along with interactions from the audience, these two often underrepresented perspectives provide a sense of the key directions in which software engineering— practice, research, and education—should and must go.

Background: Software organizations increasingly need developers with high skills for social interactions. Managers, leaders, and academics need to know the human factors influencing the individuals, the development team, and the software project activities. Despite the increasing number of secondary studies about human factors in Software Engineering (SE) and in Agile Software Development (ASD), there is no study synthesizing which human factors influence software development without a specific perspective from SE or human factor thematic. Objective: We aim to summarise human factors and their influence on SE development teams and ASD teams. Method: We executed a tertiary study. We used thematic analysis to examine the resulting data. Results: We found 29 systematic literature reviews and systematic mapping studies addressing the human perspective in SE teams. We identified 101 human factors and 79 influences grouped in 4 categories (Team member, Team, Project, and Organization). Also, we identified 71 human factors and 60 influences on ASD. The most investigated human factors are Communication, Collaboration, Knowledge, and Motivation. Conclusions: The identified human factors and their influences can be considered most significant by software organizations, researchers, and academics in SE practices. Based on our results, practitioners might propose activities that enhance human capital behaviors that influence individual motivation, agile mindset, team climate, software quality, or agile transition in traditional organizations.

Background: The adoption of the evidence-based research paradigm by software engineering researchers has created a growing knowledge base provided by the outcomes from systematic reviews. Aim: We set out to identify and catalogue a sample of the knowledge provided by systematic reviews, to determine what support they can provide for an evidence-informed approach to teaching about software engineering practice. Method: We undertook a tertiary study (a mapping study of systematic reviews) covering the period to the end of 2015. We identified and catalogued those reviews that had findings or made recommendations that were considered relevant to teaching about industry practice. Results: We examined a sample of 276 systematic reviews, selecting 49 for which we could clearly identify practice-oriented findings and recommendations that were supported by the data analysis provided in the review. We have classified these against established software engineering education knowledge categories and discuss the extent and forms of knowledge provided for each category. Conclusion: While systematic reviews can provide knowledge that can inform teaching about practice, relatively few systematic reviews present the outcomes in a form suitable for this purpose. Using a suitable format for presenting a summary of outcomes could improve this. Additionally, the increasing number of published systematic reviews suggests that there is a need for greater coordination regarding the cataloguing of their findings and recommendations.

In recent years, the use and investigations about Grey Literature (GL) increased, in particular, in Software Engineering (SE) research. However, its understanding is still scarce and sometimes controversial, such as interpreting GL types and assessing their credibility. This study aimed to understand the credibility aspects that SE researchers consider in assessing GL and its types. To achieve this goal, we surveyed 53 SE researchers (who answered that they have used GL in our previous investigation), receiving a total of 34 valid responses. Our main findings show that: 1) GL source produced or cited by a renowned source is the main credibility criteria used to assess GL, 2) most of the GL types tend to have a Low to Moderate level of Control and Expertise, 3) there is a positive statistical correlation between the level of Control and Expertise for most GL types, and 4) the different respondent profiles shared similar opinions about the credibility criteria. Our investigation contributes to helping future SE researchers that intend to use GL with more credibility. Additionally, shows the need for future studies to better understand the GL types in SE research.

Background: The use of Grey Literature (GL) has been investigated in diverse research areas. In Software Engineering (SE), this topic has an increasing interest over the last years. Problem: Even with the increase of GL published in diverse sources, the understanding of their use on the SE research community is still controversial. Objective: To understand how Brazilian SE researchers use GL, we aimed to become aware of the criteria to assess the credibility of their use, as well as the benefits and challenges. Method: We surveyed 76 active SE researchers participants of a flagship SE conference in Brazil, using a questionnaire with 11 questions to share their views on the use of GL in the context of SE research. We followed a qualitative approach to analyze open questions. Results: We found that most surveyed researchers use GL mainly to understand new topics. Our work identified new findings, including: 1) GL sources used by SE researchers (e.g., blogs, community website); 2) motivations to use (e.g., to understand problems and to complement research findings) or reasons to avoid GL (e.g., lack of reliability, lack of scientific value); 3) the benefit that is easy to access and read GL and the challenge of GL to have its scientific value recognized; and 4) criteria to assess GL credibility, showing the importance of the content owner to be renowned (e.g., renowned author and institutions). Conclusions: Our findings contribute to form a body of knowledge on the use of GL by SE researchers, by discussing novel (some contradictory) results and providing a set of lessons learned to both SE researchers and practitioners.

In this paper,I first review the seminal work by Thomas Kuhn — The Structure of Scientific Revolutions — and elaborate my view on paradigm shifts in software engineering research and practice as it turns 50 years old in 2018. I then examine major undertakings of the computing profession since early days of modern computing, especially those done by the software engineering community as a whole. I also enumerate anomalies and crises that occurred at various stages, and the attempts to provide solutions by the software engineering professionals in the past five decades. After providing such a background, I direct readers attention toward emerging anomalies in software engineering, at a severity level that is causing another software engineering crisis, and suggest a set of criteria for feasible solutions. The main theme of this paper is to advocate that situation analytics, equipped with necessary definitions of essential concepts including situation and intention as parts of a new computational framework, can serve as the foundation for a new software engineering paradigm named the Situation-Centric Paradigm. In this framework, situation is considered a new abstraction for computing and is clearly differentiated from the widely accepted existing abstractions, namely function and object. I argue that the software engineering professionals will inevitably move into this new paradigm, willingly or unwillingly, to empower Human-Embedded Computing (HEC) and End-User Embedded Computing (EUEC), much more than what they have done with traditional human-centered or user-centric computing altogether. In the end, I speculate that an ultimate agile method may be on the rise, and challenge readers to contemplate “what if" hundreds of thousands “end-user developers" emerge into the scene where the boundaries between end users and developers become much more blurred.

BackgroundPatient narrative data in online health care forums (communities) are receiving increasing attention from the scientific community for implementing patient-centered care. Natural language processing (NLP) methods are gaining more and more attention because of the enormous data volume. However, state-of-the-art NLP still cannot meet the need of high-resolution analysis of patients’ narratives. Manual qualitative analysis still plays a pivotal role in answering complicated research questions from analyzing patient narratives.ObjectiveThis study aimed to develop a systematic framework for qualitative analysis of patient-generated narratives in online health care forums.MethodsOur systematic framework consists of 4 phases: (1) data collection, (2) data preparation, (3) content analysis, and (4) interpretation of the results. Data collection and data preparation phases are constructed based on text mining methods for identifying appropriate online health forums for data collection, differentiating posts of patients from other stakeholders, protecting patients’ privacy, sampling, and choosing the unit of analysis. Content analysis phase is built on the framework method, which facilitates and accelerates the identification of patterns and themes by an interdisciplinary research team. In the end, the focus of interpretation of the results phase is to measure the data quality and interpret the findings regarding the dimensions and aspects of patients’ experiences and concerns in their original contexts.ResultsWe demonstrated the usability of the proposed systematic framework using 2 case studies: one on determining factors affecting patients’ attitudes toward antidepressants and another on identifying the disease management strategies in patient with diabetes facing financial difficulties. The framework provides a clear step-by-step process for systematic content analysis of patient narratives and produces high-quality structured results that can be used for describing patterns or regularities in patients’ experiences, generating and testing hypotheses, and identifying areas of improvement in the health care systems.ConclusionsThe systematic framework is a rigorous and standardized method for qualitative analysis of patient narratives. Findings obtained through such a process indicate authentic dimensions and aspects of patient experiences and shed light on patients’ concerns, needs, preferences, and values, which are the core of patient-centered care.International Registered Report Identifier (IRRID)RR1-10.2196/13914

There has long been a close association between research in software engineering and the design of programming languages. Part of the IMPACT project involves an exploration of the interrelations of these two fields and documentation in a report of how fundamental research in software engineering has been a valuable resource for programming language features commonly used today. The resulting report investigates the relationship by considering features in currently used languages, including exceptions, control and data abstractions, types, inheritance, concurrency and visualization mechanisms.This paper, exerpted from the report, focuses on the influence of software engineering research on the development of exceptions. The paper demonstrates that there is a symbiotic relationship between software engineering research and the design of exception handing in programming languages. Publication of these partial results is aimed at soliciting feedback and comments from both the programming languages and software engineering communities.

Trends that have contributed to the globalisation of the software engineering industry include virtual collaborative teams, off-shore outsourcing, and international migration of IT professionals. These three trends and the international spread of software engineering standards and methodologies are explored with specific examples from the Australian software engineering industry. Results from a Europe/Australia study about adoption of software best practice conducted in 16 countries are then summarised and analysed using Hofstede's cultural dimensions. The discussion considers the efficacy of the concept 'national culture' in light of the analysis and concludes that software engineering researchers need to reconsider the concept and measurement of national culture. Implications of the globalisation of software engineering standards and methodologies on various stakeholders are discussed.

Artificial intelligence and recent advances in deep learning architectures, including transformer networks and large language models, change the way people think and act to solve problems. Software engineering, as an increasingly complex process to design, develop, test, deploy, and maintain large-scale software systems for solving real-world challenges, is profoundly affected by many revolutionary artificial intelligence tools in general and machine learning in particular. In this roadmap for artificial intelligence in software engineering, we highlight the recent deep impact of artificial intelligence on software engineering by discussing successful stories of applications of artificial intelligence to classic and new software development challenges. We identify the new challenges that the software engineering community has to address in the coming years to successfully apply artificial intelligence in software engineering, and we share our research roadmap toward the effective use of artificial intelligence in the software engineering profession, while still protecting fundamental human values. We spotlight three main areas that challenge the research in software engineering: the use of generative artificial intelligence and large language models for engineering large software systems, the need of large and unbiased datasets and benchmarks for training and evaluating deep learning and large language models for software engineering, and the need of a new code of digital ethics to apply artificial intelligence in software engineering.