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Abstract: The need for applications that are developed especially for Computational Science and Engineering (CSE) has been growing rapidly in the recent years. These applications are often a prerequisite for research and have to be evolved and maintained for considerable periods of time. However, CSE researchers have traditionally put focus on achieving better computational performance and results rather than the software’s comprehensibility, maintainability and extensibility. This paper first presents two case studies on two different CSE research projects, where common and specific problems are identified. Second we propose solutions that intend to apply software engineering methodologies and tools to improve the CSE research software development. [ABSTRACT FROM AUTHOR]

An adaptive system is able to adapt at runtime to dynamically changing environments and to new requirements. Adaptive systems can be single adaptive entities or collective ones that consist of several collaborating entities. Rigorous engineering requires appropriate methods and tools that help guaranteeing that an adaptive system lives up to its intended purpose. This paper introduces the special section on "Rigorous Engineering of Collective Adaptive Systems." It presents the 11 contributions of the section categorizing them into five distinct research lines: correctness by design and synthesis, computing with bio-inspired communication, new system models, machine learning, and programming and analyzing ensembles. [ABSTRACT FROM AUTHOR]

Provides an overview of selected papers that deals with different aspects of tool data integration techniques from a meta-modeling point of view, presented at the European Software Engineering Conference 2003 Workshop on Tool Integration in System Development, which took place on September 1-2, 2003 in Helsinki, Finland. Survey of model integration and transformation approaches; Suggested systematic approach for the development of the architecture of integrated development environments; List of sessions where the papers were presented.

The article discusses the IEEE International Requirements Engineering Conference (RE). This issue contains an introduction of the best papers presented during the conference on requirements activities in the fields of systems and software engineering. The conference was held at the University of Paris 1-Pantheon Sorbonne.

This theme section brings together the latest research at the intersection of artificial intelligence (AI) and model-driven engineering (MDE). Over the past years, we have witnessed a substantial rise of AI successfully applied to different domains, including software development and MDE. Dedicated events at the intersection of AI and MDE have been created, too, such as the MDE Intelligence workshop series co-located with the MODELS conference. This theme section covers research contributions integrating AI components into MDE approaches—increasing the current benefits of MDE processes and tools and pushing the limits of "classic" MDE with the goal to provide software and systems engineers with the right techniques to develop the next generation of highly complex model-based systems—and applications of MDE to the development of AI components. In total, nine submissions were accepted in the theme section after a thorough peer-reviewing process. [ABSTRACT FROM AUTHOR]

The International Computer and Software Applications Conference has celebrated its tenth anniversary in 1986. The conference has been very successful in attracting excellent papers and panels from both academia and industry. It continued the tradition and attracted superb papers for the following tracks: software quality, software engineering, software requirements, development environments, software techniques and knowledge-based systems.

This article is an editorial that discusses the topic of understanding and engineering cyber-physical collectives (CPCs). It highlights the complexity of CPCs and the need for scientific and engineering ideas, methods, and tools to address their challenges. The article mentions various theoretical and engineering perspectives that can be applied to CPCs, such as coordination models, swarm robotics, and collective intelligence. It includes summaries of several research papers that contribute to the understanding and engineering of CPCs, covering topics like geometric pattern formation, collision avoidance, and collective exploration and exploitation. The article concludes by emphasizing the importance of considering the collective dimension in the engineering of socio-technical systems and the potential for universal laws and techniques for analyzing and engineering collective systems. [Extracted from the article]

User participation and involvement in software development are considered to be essential for a successful software system. Three research areas, human aspects of software engineering, requirements engineering, and information systems, study these topics from various perspectives. We think it is important to analyze user participation and involvement in software engineering comprehensively to encourage further research in this area. We investigate the evidence on effects of user participation and involvement on system success and we explore which methods are available in literature. A systematic mapping study was conducted. The systematic search yielded 3,698 hits, from which we identified 289 unique papers. These papers were reviewed by the first author based on inclusion and exclusion criteria. The second author validated the selection of papers by reviewing the reasons for exclusion and inclusion and the corresponding papers on a sample base. 58 of the 289 papers were selected (22 statistical survey and meta-study papers and 36 methods papers). Based on the empirical evidence of the surveys and meta-studies, we developed a meta-analysis of structural equation models. This overview demonstrates that most papers showed positive correlations between aspects of development processes (including user participation) and human aspects (including user involvement) and system success. The analysis of the proposed solutions from the method papers revealed a wide variety of user participation and involvement practices for most activities within software development. [ABSTRACT FROM AUTHOR]

This study aims to suggest variability mechanisms for software product line development and to explain the results of case study. Software product line engineering is an extension of software engineering and many organizations constantly engage in reengineering and refactoring to adopt the software product line engineering. Software product line engineering has two engineering processes: domain engineering process and application engineering process. Feature Identification and feature model are key success factor to construct variability model. Feature model describes the variable parts to be extended or replaced and common part to be reuse by themselves. Feature model gives the directions to the following architecture design and component implementation. However, feature model is not the design strategy and variability mechanism for product line implementation. Therefore, these are the obstacles for organizations that are unfamiliar with feature model and variability mechanism to adopt software product line engineering. Several variability mechanisms for software intensive software are suggested but these are not applicable for embedded software since it has different development process and structure. In this paper, variability elements in architecture design and component design of embedded software are identified as state variable, state transition information, and algorithm. Variability management mechanisms are defined for these elements. To provide the detail strategy and to evaluate the suggested variability management methods, process and results of real case study are described. [ABSTRACT FROM AUTHOR]

The production of green hydrogen and its scale-up require the enginering and installation of new electrolysis plants. Modular electrolysis plants ease the scale-up as they allow to add further modules with growing demand. While many engineering methods focus on the detailed planning of the plants and their automation systems, the early engineering phases are scarcely considered, supported or formalized. However, especially these phases are crucial in the current scale-up of modular electrolysis plants. In this paper, an intention-based engineering approach for the early engineering phases Requirements Engineering and Conceptual Engineering for modular electrolysis plants is presented and evaluated based on three different use cases. The approach is based on Goal-oriented Requirements Engineering from Software Engineering and relies on an early, systematic as well as formalized description and analysis of intentions of different engineering disciplines. [ABSTRACT FROM AUTHOR]

In the context of its initiative to promote the adoption of model‐based approaches in the development of present and upcoming missions, the European Space Agency (ESA) organised this year its annual workshop on Model‐Based Space Systems and Software Engineering (MBSE2023) at its European Space Research and Technology Centre (ESTEC) premises. The aim of this year's workshop was to investigate how the model‐based systems engineering community could contribute to bridging the gap with domain‐specific model‐based approaches used in subsystem design. The World Café Method was used to facilitate the group discussions, the outcomes of which are summarized and presented in this paper. [ABSTRACT FROM AUTHOR]

The research aimed to develop Android-based teaching material to improve the understanding of Software Engineering of Informatics Engineering students whose validity and effectiveness are measured. The method used in this paper is Research and Development (R&D) with the Analysis, Design, Development, Implementation, and Evaluation (ADDIE) model which is used to develop Android-based teaching material. The validity of teaching material product has confirmed by media experts and material experts in their fields. The effectiveness of the product was measured through the post-test only control group design with two groups of Informatics Engineering students in Higher Education involving 57 people. Data collection was carried out through questionnaires and tests, with descriptive analysis for the results of the validation of teaching material and pilot tests and t-tests for testing the effectiveness of teaching material. The results showed that Android-based teaching material is easy to use and has video tutorial features and quiz menus that provide direct feedback to users, so teaching material can be applied as a valid and effective learning media in increasing student understanding of Software Engineering material which has never been applied in the research location so far. Based on the results obtained, further research can be carried out on a broader subject and pay attention to other aspects such as increasing motivation and metacognitive students of Informatics Engineering. [ABSTRACT FROM AUTHOR]

Requirements analysis is the first phase of software development process and it is one of the main concerns of software engineers. The selection of requirements is a complex problem caused by the heterogeneity of the users and their varied interests and demands. In this paper, it is justified that their is a strong need of optimization in requirement analysis. The paper argues that requirement selection can be viewed as an application area of Search-Based Software Engineering(SBSE). The aim is to justify the claim that requirement engineering can be re-formulated as search problem to which meta-heuristic technique can be applied. [ABSTRACT FROM AUTHOR]

Limitations regarding process design, optimization, and control often occur when using particular process simulators. With the implementation of connection methodologies, integrated tools could be made by coupling popular process simulation software with each other or with programming environments. In the current paper, we summarized and categorized the existing research regarding the application of multi-software engineering in the chemical industry, with an emphasis on software connections. CAPE-OPEN, COM, OPC, and native integration were discussed in detail, with the intention to serve as a guide for choosing the most suitable software combination and connection. These hybrid systems can handle complex user-defined problems and can be used for decision support, performing custom unit operations, operator training, process optimization, building control systems, and developing digital twins. In this work, we proposed the use of process simulator Aspen HYSYS linked together with the numeric computing platform MATLAB to solve a reaction kinetic parameter identification problem regarding the production of  γ -valerolactone. [ABSTRACT FROM AUTHOR]

In the current technological scenario of the industry and businesses, there has been increasing need of software within systems and also an increasing demand being put onto software-intensive systems. This in effect will lead to a significant evolution of software engineering processes over the next twenty years. This is due to the fact of emerging technological advancements like Industry 4.0 and Internet of Things in the IT field, among other new developments. This paper addresses and tries to analyses the key research challenges being faced by the software engineering field and articulates information that is derived from the key research specializations within software engineering. The paper analyses the past and current trends in software engineering. The future of software engineering is also looked with respect to Industry 4.0 which including emerging technological platforms like Internet of Things. The societal impact aspect of future trends in software engineering is also addressed in this paper. [ABSTRACT FROM AUTHOR]

Collaboration Engineering (CE) is an approach for the design and deployment of repeatable collaborative work practices that can be executed by domain experts without the ongoing support of external collaboration professionals. Since 2001, CE has been an active and productive topic of research that has attracted scientists from different backgrounds and disciplines. CE research started with studies on ways to transfer professional collaboration expertise to novices using a pattern language called thinkLets. Subsequent research focused on the development of theories to explain key phenomena, the development of a structured design methodology, training methods, technology support, design theories, and various field and experimental studies focusing on specific aspects of the CE approach. This paper details the contributions from CE research and practice based on a literature assessment of 331 publications. It extracts the key insights from the body of CE research thus far, identifies significant areas of inquiry that have not yet been explored, and looks ahead at the CE research opportunities that are emerging as our society, organizations, technologies, and the nature of collaboration evolve. [ABSTRACT FROM AUTHOR]

Empirical studies, often in the form of controlled experiments, have been widely adopted in software engineering research as a way to evaluate the merits of new software engineering tools. However, controlled experiments involving human participants actually using new tools are still rare, and when they are conducted, some have serious validity concerns. Recent research has also shown that many software engineering researchers view this form of tool evaluation as too risky and too difficult to conduct, as they might ultimately lead to inconclusive or negative results. In this paper, we aim both to help researchers minimize the risks of this form of tool evaluation, and to increase their quality, by offering practical methodological guidance on designing and running controlled experiments with developers. Our guidance fills gaps in the empirical literature by explaining, from a practical perspective, options in the recruitment and selection of human participants, informed consent, experimental procedures, demographic measurements, group assignment, training, the selecting and design of tasks, the measurement of common outcome variables such as success and time on task, and study debriefing. Throughout, we situate this guidance in the results of a new systematic review of the tool evaluations that were published in over 1,700 software engineering papers published from 2001 to 2011. [ABSTRACT FROM AUTHOR]

An adaptive system is able to adapt at runtime to dynamically changing environments and to new requirements. Adaptive systems can be single adaptive entities or collective ones that consist of several collaborating entities. Rigorous engineering requires appropriate methods and tools that help guaranteeing that an adaptive system lives up to its intended purpose. This paper introduces the special section on "Rigorous Engineering of Collective Adaptive Systems." It presents the seven contributions of the section and gives a short overview of the field of rigorously engineering collective adaptive systems by structuring it according to three topics: systematic development, methods and theories for modelling and analysis, and techniques for programming and operating collective adaptive systems. [ABSTRACT FROM AUTHOR]

Comments on the articles in the "IEEE Transactions on Software Engineering" were given. The periodical has an established, published scope which is subject to change as the file develops. Part of the review process is to state whether the paper meets the criteria. The scope should be limited to papers of interest to the software engineering community. However, besides mainstream software engineering topics, it could include the software engineering of various applications.

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. [ABSTRACT FROM AUTHOR]

Despite the increasing demand for utilizing high-performance computing (HPC) for CSE applications, software development for HPC historically attracted little attention from the software engineering (SE) community. Paradoxically, the HPC CSE community has increasingly been adopting SE techniques and tools. Indeed, the development of CSE software for HPC differs significantly from the development of more traditional business information systems, from which many SE best practices and tools have been drawn. The workshop summarized in this column, the fourth in the series to be collocated with the Supercomputing conference series, examined two main topics: testing and tradeoffs. Through presentations of work in this area and structured group discussions, the participants highlighted some of the key issues, as well as indicated the direction the community needs to go. In particular, there is a need for more high-quality research in this area that we can use as an evidence base to help developers of CSE applications change practice and benefit from advances in software engineering. [ABSTRACT FROM PUBLISHER]

The interpretations of logical expressions found in most introductory textbooks are not suitable for use in software engineering applications because they do not deal with partial functions. More advanced papers and texts deal with partial functions in a variety of complex ways. This paper proposes a very simple change to the classic interpretation of predicate expressions, one that defines their value for all values of all variables, yet is almost identical to the standard definitions. It then illustrates the application of this interpretation in software documentation. [ABSTRACT FROM AUTHOR]

This section introduces a series of articles on software engineering.

The impact of model-based design on the software engineering community is impressive, and recent research in model transformations, and elegant behavioral specifications of systems has the potential to revolutionize the way in which systems are designed. Such techniques aim to raise the level of abstraction at which systems are specified, to remove the burden of producing application-specific programs with general-purpose programming. For complex real-time systems, however, the impact of model-driven approaches is not nearly so widespread. In this paper, we present a perspective of model-based design researchers who joined with software experts in robotics to enter the DARPA Urban Challenge, and to what extent model-based design techniques were used. Further, we speculate on why, according to our experience and the testimonies of many teams, the full promises of model-based design were not widely realized for the competition. Finally, we present some thoughts for the future of model-based design in complex systems such as these, and what advancements in modeling are needed to motivate small-scale projects to use model-based design in these domains. [ABSTRACT FROM AUTHOR]

Abstract??If empirical software engineering is to grow as a valid scientific endeavor, the ability to acquire, use, share, and compare data collected from a variety of sources must be encouraged. This is necessary to validate the formal models being developed within computer science. However, within the empirical software engineering community this has not been easily accomplished. This paper analyses experiences from a number of projects, and defines the issues, which include the following: (1) How should data, testbeds, and artifacts be shared? (2) What limits should be placed on who can use them and how? How does one limit potential misuse? (3) What is the appropriate way to credit the organization and individual that spent the effort collecting the data, developing the testbed, and building the artifact? (4) Once shared, who owns the evolved asset? As a solution to these issues, the paper proposes a framework for an empirical software engineering artifact agreement. Such an agreement is intended to address the needs for both creator and user of such artifacts and should foster a market in making available and using such artifacts. If this framework for sharing software engineering artifacts is commonly accepted, it should encourage artifact owners to make the artifacts accessible to others (gaining credit is more likely and misuse is less likely). It may be easier for other researchers to request artifacts since there will be a well-defined protocol for how to deal with relevant matters. [ABSTRACT FROM AUTHOR]

This article presents information about the selection of the four best papers submitted to the 27th International Conference on Software Engineering held on May 21, 2005. A summary for each paper is provided along with the author's name and the main topic of each paper. One paper deals with a new approach to software fault tolerance. Another paper discusses an environment for finding and visualizing examples of usage of an API. The third paper reports on a study to determine the limitations of tools used in computer maintenance tasks.

An introduction to the journal is presented in which the guest editors discuss research in software engineering.

Machine Learning (ML) is ubiquitously on the advance. Like many domains, Earth Observation (EO) also increasingly relies on ML applications, where ML methods are applied to process vast amounts of heterogeneous and continuous data streams to answer socially and environmentally relevant questions. However, developing such ML- based EO systems remains challenging: Development processes and employed workflows are often barely structured and poorly reported. The application of ML methods and techniques is considered to be opaque and the lack of transparency is contradictory to the responsible development of ML-based EO applications. To improve this situation a better understanding of the current practices and engineering-related challenges in developing ML-based EO applications is required. In this paper, we report observations from an exploratory study where five experts shared their view on ML engineering in semi-structured interviews. We analysed these interviews with coding techniques as often applied in the domain of empirical software engineering. The interviews provide informative insights into the practical development of ML applications and reveal several engineering challenges. In addition, interviewees participated in a novel workflow sketching task, which provided a tangible reflection of implicit processes. Overall, the results confirm a gap between theoretical conceptions and real practices in ML development even though workflows were sketched abstractly as textbook-like. The results pave the way for a large-scale investigation on requirements for ML engineering in EO. [ABSTRACT FROM AUTHOR]