(ISEF): an integrated industrial-strength software engineering framework

Computer science and art have been in contact since the 1960s. Our hypothesis is that software engineering can benefit from multidisciplinary research at the intersection with art for the purpose of increasing innovation and creativity. To do so, we have designed and planned a literature review in order to identify the existing knowledge base in this interdisciplinary field. A preliminary analysis of both results of our review and observations of software development projects with artist participation, reveals four main issues. These are software development issues, which include requirement management, tools, development and business models; educational issues, with focus on multidisciplinary education; aesthetics of both code and user interface, and social and cultural implications of software and art. The identified issues and associated literature should help researchers design research projects at the intersection of software engineering and art. Moreover, they should help artists to increase awareness about software engineering methods and tools when conceiving and implementing their software-based artworks.

Learning Software Engineering principles, processes, methods and tools is a prerequisite to becoming a Software Engineer. The technological advancements and revolution in this new century are probing the boundaries of education and training in software engineering. This work tries to locate the shortcomings in existing approaches to Education in Software Engineering (ESE) in respect to today's technological advancements. We hereby proposed a new model for Education in Software Engineering to bridge the industry-academia gap.

A comprehensive engineering framework for guaranteeing component compatibility

Although Semantic Web Services are expected to produce a revolution in the development of Web-based systems, very few enterprise-wide design experiences are available; one of the main reasons is the lack of sound Software Engineering methods and tools for the deployment of Semantic Web applications. In this chapter, we present an approach to software development for the Semantic Web based on classical Software Engineering methods (i.e., formal business process development, computer-aided and component-based software design, and automatic code generation) and on semantic methods and tools (i.e., ontology engineering, semantic service annotation and discovery).

This paper considers the current state of software engineering for parallel systems. A review of existing approaches and techniques identifies inadequacies. Recent work on design, verification and automated support is outlined. The next generation of embedded and distributed technologies will compound the problems through increased demand and diversity. This paper discusses the implications for the progression of current techniques into new methods for future software engineering of parallel systems.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Context: Capture-recapture method has long been adopted in software engineering as a relatively objective way for defect estimation. While many relevant studies have been carried out to evaluate various capture-recapture models and estimators, there still lacks common understanding on the adoption status of the method in software engineering. It is necessary to systematically collect empirical evidence of Capture-recapture adoption hence form necessary understanding on the method.Objective: This study aims to synthesize relevant primary studies on the adoption of capture-recapture method in software engineering, and try to identify possible gaps between the state-of-practice and the state-of-art so as to provide clues for future research.Method: By following the guidelines of Kitchenham, we conducted a Systematic Literature Review(SLR) on studies of the adoption of capture-recapture method in software engineering.Results: From 5 common digital libraries, we retrieved 506 published articles, among them 44 were identified as relevant primary studies. We identified 18 capture-recapture estimators under 4 basic models. Types of the currently existing studies as well as the relevant influencing factors to adoption of the capture-recapture method are also discussed.Conclusion: Results show that there are no conclusive decisions on the best capture-recapture models and estimators. Besides, the number of inspectors and their capability to detect defects as well as the difficulty to detect defects are most critical influencing factors. In addition, lacking of industrial application may be the major issue of current adoption status of capture-recapture method in software engineering.

The ultimate aim of software engineering methods and tools is to reduce risks associated with the development of software products. Accepted risk management procedures recognize that software development is inherently risky, however fail to take into account the changing nature of both software products and the organizations undertaking their development. SE research has traditionally focused on the needs of very large corporations undertaking equally mammoth and complex development projects, thus most tools and methods are predicated on this model. Yet most software development is undertaken by small to medium enterprises. Consequently, these development efforts are either undertaken with little or no adherence to any SE standard process or by attempting to tailor processes intended for larger organizations. Neither of these alternatives is ideal, with both introducing new elements of risk. The rise of the Internet as a platform for commercial applications has partly driven this move away from monolithic software development and has also contributed to the proliferation of software products built using COTS components. Clearly there is a risk involved in the use of components not developed specifically for a particular application while Internet applications introduce an. entirely new set of possible risks. These newer risk factors directly affect the quality of the software product and the paper discusses these factors in detail, showing how they contribute to making software development today an even riskier proposition than previously.

To summarize,Software engineering Environmentsprovides a useful overview of recent progress in software engineering tools and methods; particularly from a UK perspective. The majority of the contributions are well-written but the general paucity of introductory material and the level of technical detail in some chapters might prove daunting to readers unfamiliar with software engineering. It would have been helpful if the editor had made more effort to draw out the common themes and important issues; either by linking sections of the book with short discussion (as Hawley did forArtificial Intelligence Programming Environments) which helps to smooth over the changes in prose style or by cross-referencing points made by different authors. As it stands the result is rather a peculiar hybrid between a conference proceedings and a multi-author text book.

This article reviews the integration of machine learning (ML) techniques into Software Engineering (SE) across various phases of the software development life cycle (SDLC). The purpose is to investigate the applications of ML in SE, analyze its methodologies, present findings, and draw conclusions regarding its impact. The study categorized ML applications in SE and assessed the performance of various ML algorithms. Authors identified ML applications in SDLC phases, including requirements analysis, design, implementation, testing, and maintenance. ML algorithms, such as supervised and unsupervised learning, are employed for tasks like software requirement identification, design pattern recognition, code generation, and automated testing. In summary, we find that ML-based techniques are experiencing a substantial surge in adoption within the field of software engineering. Nevertheless, it is evident that substantial endeavors are needed to establish thorough comparisons and synergies among these approaches, perform meaningful evaluations grounded in detailed real-world implementations that are applicable to industrial software development. Therefore, our key takeaway is the necessity for a shift in focus towards reproducible research, prioritizing this over isolated novel concepts. Failure to do so may result in the limited practical implementation of these promising applications.

Researchers have examined a wide variety of practices to help software engineers complete different programming tasks. Despite the fact that studies show software engineering practices and tools created to improve the software development process are useful for preventing bugs, decreasing debugging costs, reducing debugging time, and providing additional benefits, software engineers rarely use them in practice. To persuade humans to alter and adopt new behaviors, psychologists have studied the concept of nudges. My research aims to investigate how digital nudges, or the process of using technology to automatically create nudges, can be beneficial in helping software developers and teams adopt software engineering activities and integrate them into their normal workflow.

As a basis subject of computer, Computer software engineering has been increasingly used in various fields, Games management system has been pre-designed on the basis of application of software engineering theory and method. The actual games management system software has been developed from using software engineering methods, in the actual design and development, it has been proved that a practical system has been perfect created with efficiency design, fully functional form, rational and affordable design.

This paper describes work that explores how tools can help change agents in software organizations incorporate new software engineering tools and methods more effectively. A prototype expert system was built to assist change agents in gathering information and planning tasks in a software engineering adoption and implementation effort. The knowledge engineering process for this system helped to integrate and translate research and practice from software engineering technology adoption and implementation within the field of technology transfer and diffusion of innovation for software change agents.KeywordsSoftware engineeringadoptionimplementationtechnology transferknowledge-based toolexpert systemknowledge elicitation

In this paper, we identify a set of factors that may be used to forecast software productivity and software development time. Software productivity was measured in function points per person hours, and software development time was measured in number of elapsed days. Using field data on over 130 field software projects from various industries, we empirically test the impact of team size, integrated computer aided software engineering (ICASE) tools, software development type, software development platform, and programming language type on the software development productivity and development time. Our results indicate that team size, software development type, software development platform, and programming language type significantly impact software development productivity. However, only team size significantly impacts software development time. Our results indicate that effective management of software development teams, and using different management strategies for different software development type environments may improve software development productivity.

The discipline of Software Engineering is continuously adapting to new challenges while gaining more and more insights. The age of globalisation has brought about a new movement of internationalisation and localisation. While practitioners fully embrace the efforts, educators only marginally consider the implications for the teaching and learning of Software Engineering. While the relevance of the software deployment context has been widely recognised, the intrinsic values of the development context are less evident. Besides western cultural indicators being omnipresent in software applications, they are deeply rooted in Software Engineering concepts and methods. Standards and models have been established in the absence of possible deviations from other -- e.g. African -- contexts. Educators and authors of common and internationally used textbooks present Software Engineering concepts and methods as universally valid. Thus software engineering graduates all over the world continue to be ill-equipped for specific software development contexts. Moreover the necessity to localise Software Engineering education is illustrated by our vast amount of challenges, experiences and best-practices of teaching Software Engineering in a Sub-Saharan country. In this paper, we introduce a generic framework leading towards a Contextualised Software Engineering education (CSE2).

The ever-increasing level of interaction across the "border" between software engineering and information systems is evidence of substantive maturity and sustained effort to articulate these closely-related disciplines. As software engineering principles have matured and proven themselves, information systems developers have incorporated them in the analysis and design process. We anticipate that continued development and improvement of software engineering methods and tools enables developers to continually improve the software development effort, resulting in better software and greater client satisfaction.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>