Trends in Software Engineering in 2020

<p>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.</p>

A recent trend in software engineering is the shift from a focus on laboratory-oriented software engineering to a more industry-oriented view of software engineering processes. This complements preceding ideas about software engineering in terms of organization and process-orientation. From the domain coverage point of view, many of the existing software engineering approaches have mainly concentrated on the technical aspects of software development. Important areas of software engineering, such as the technical and organizational infrastructures, have been left untouched. As software systems increase in scales, issues of complexity and professional practices become involved. Software development as an academic or laboratory activity, has to engage with software development as a key industrialized process. This expanded domain of software engineering exposes the limitations of existing methodologies that often address only individual subdomains. There is, therefore, a demand for an overarching approach that provide a basis for theoretical and practical infrastructures capable of accommodating the whole range of modern software engineering practices and requirements. One approach is provided by Process-Based Software Engineering (PBSE); part of the more general trend towards a focus on process. This paper provides a review of process techniques for software engineering and a high-level perspective on PBSE. Typical approaches and techniques for the establishment, assessment, improvement and benchmarking of software engineering process systems are introduced in this paper, and many are developed further in other contributions to this volume.

Software Engineering (SE) as a field has grown significantly in terms of the research publications in the last few years. Criterion-based assessment of research performance of scholars, countries along with collaboration networks and links among articles are better judged using bibliometric analysis. The results proposed in this work are based on quantitative analysis and data visualisation of 150,087 scholarly articles published in last 13 years (2007–2019) across 85 research areas based on seven categories by providing a detailed and distinctive time-frame-based comparison to observe a shift in research trend in SE and its 12 distinguished sub-areas. The results of the observations proposed in this work include analysis on types of documents, yearly publication trends with results suggesting a prominent increment for the period (2015–2017) in terms of research publications, languages of research publications with findings indicating that there are articles published in languages other than English language, also, publication count-based rankings of authors, collaboration networks of countries with findings showing the supremacy of USA and China and keyword statistics.

Stack Exchange Q&A website is a major platform of sharing knowledge about number of topics in various domains like Arts, technology, science, communication, literature etc. through Questions & Answers. In this paper, we are analyzing the textual content of Software Engineering, Stack Exchange Q&A website in various dimensions. The dimensions LDA based topic modelling, temporal trends of topics over time, technology impact, technology trends and their popularity. The analysis shows that wide range of topics are discussed in the Software Engineering Q& A website amongst the most popular are Programming skills, object-oriented design and design and development.

Several large companies have conducted initiatives for systematic learning from experience in software engineering. In the international Software Experience Center (SEC), for example, five companies exchanged experiences and collaborated in building experience exchange mechanisms to be used within each company. Many insights were gained and lessons were learned over the years, among them: (1) Written and documented experiences are the exception rather than the rule. (2) Although not documented in detail or controlled by a process, experience needs guidance and support in order to reach the designated person or group. The of experience must be kept in mind. (3) Experience is a delicate material, and any avoidable effort or threshold to participate in systematic experience exploitation may endanger stakeholder participation and success. (4) Tools can effectively be built to support orderly flow of experience, but they must be optimized for cognitive support of their users. These lessons learned from supporting experience exploitation can be applied to software projects more generally: Requirements, rationale, and other information flowing through a software project resemble experience with respect to the above-mentioned characteristics: They are often communicated orally rather than in a document. There are diverse processes and practices designed to channel information flow. Early and vague requirements must be handled with care, and tools need to be optimized to reduce cognitive barriers and thresholds, or they will not be accepted. A focus on information and experience flow takes the above-mentioned lessons into account. Information flows within one project, while experience often cuts across several projects. Requirements of one project are useful only in that same project. Experience in designing a product, however, may be reused in subsequent projects. Information and experience flows need to be modelled explicitly. A simple notation is proposed to capture just the essence of flowing information. What may seem like a subtle shift from processes to flows offers a new perspective: Based on those models, dedicated techniques and tools can be developed for analysing and for improving the flows. A wide range of current trends in software engineering can benefit from a better understanding of --- and support for --- appropriate information flow: Interfaces to the subcontractors, distributed and collaborative teams, Wiki webs, and a variety of new communication channels in global software engineering call for a focus on information flow.

Software Engineering (SE) is evolving to make the best out of the constantly changing technological trends, ranging from development to deployment to management and decommissioning of software systems. In this new column Trending Topics in Software Engineering, we aim at providing insights, reports, and outlooks on how researchers and practitioners around the world are working (or planning to work) on those trends. We intend to collect the challenges they are facing or foresee, and explore them in future issues. Our ultimate ambition is to stimulate fruitful discussion in our columns to contribute to identifying the next SE trends, while illustrating them to our audience.

Software engineering trends before the mid-1970s followed one basic programming methodology, known as structured programming. The structured paradigm, also called the classical paradigm, offered a very straight-forward approach to software engineering which seemed sufficient for the time. This model provided a simple view of a software product: the product was either operation oriented or data oriented. In the first case, primary attention was paid to the functions performed. In the second, the primary focus was on the information being handled. The picture painted by the classical paradigm seemed uncomplicated in the beginning, but as the field of software engineering grew, a fundamental flaw became apparent. Describing a software application based exclusively on either the operations it was to perform or the data it was to manage was just too simplistic.

Abstract. The rapid advancement of Artificial Intelligence (AI) has significantly influenced various industries, including software engineering. This paper explores the integration of AI into software engineering, focusing on its applications across different stages of the software development life cycle, including design, development, testing, project management, and maintenance. AI's ability to automate tasks, enhance efficiency, and improve code quality is revolutionizing how software is built and maintained. The paper also addresses the challenges and risks associated with AI-driven software engineering, such as dependency on AI tools, ethical concerns, and security vulnerabilities. Finally, the paper highlights future trends in AI-powered software engineering, including adaptive and self-healing systems, AI-enhanced collaboration, and full software automation. The role of AI in shaping the future of software engineering is both profound and transformative, making it a critical area of study.

Component reuse has become a trend in software engineering. However, third-party components have the potential to introduce vulnerabilities into software applications and become the weakest link in the security chain. In this paper, we discuss the limitations of traditional security practices and controls against vulnerable components. As a solution, we present a software design and development approach, combined with a collaborative, cloud-based vulnerability and threat management system. This combination aims at enabling applications to gain “artificial immunity” to third-party components by dynamically identifying and controlling related security risks. It also strives to promote the automatic discovery of, and near real-time information dissemination about emerging threats and zero-day vulnerabilities. At the heart of our solution, we use application-level API sandboxing, as well as adaptive signature-based and anomaly-based API intrusion detection and prevention. The need-to-know, cost-effectiveness, and user acceptance through separation of concerns have been our guiding security engineering principles.

In recent years, Service-Oriented Computing (SOC) has emerged as a great new trend in software engineering. At the same time that SOC was attaining its space within both academia and industry, there was a growth in the supply and use of mobile and embedded devices. These devices are the key pieces for accomplishing the vision of ubiquitous/pervasive computing. One of the challenges for realising this vision consists in making heterogeneous devices to dynamically find each other in order to exchange data and advertise/consume services. In this context, SOC actually stands out as the better bullet for accomplishing this need, but at the cost of a number of other issues that system architects need to deal with. In this article, a set of issues related to the integration of mobile devices and SOC in the context of smart spaces is surveyed.

A recent trend in software engineering is to support the development process by providing flexible tool chains allowing for effective Model-Driven approaches. These solutions are very appealing in industrial settings since they enable the creation of development and verification processes, enhancing abstraction and reuse, and hence improving productivity. This paper addresses advantages and challenges in extending Model-Driven approaches to system engineering and specifically to verification and validation (V&V) of critical computer-based systems. Specifically, the paper highlights the needs for real-world industrial contexts and proposes the definition of a unifying Model-Driven process for V&V of functional and non-functional system properties. Some enabling techniques which aim at improving the reuse of Model-Driven artifacts are addressed to deal with process scalability and effectiveness. Two sample applications are described for ERTMS/ETCS signalling system in order to show the advantages of the approach: formal modeling for performance evaluation of message delivery between train and track controllers and test case generation for the verification of functional requirements of trains outdistancing.

One of the major current research trends in Software Engineering is the focus on the development of new techniques to deal efficiently with the design of systems that are able to evolve overtime and adapt to rapid changes of their requirements. However, it is still an open issue how to quantify and evaluate the adaptability of a given software system. In this paper we propose the definition of metrics able to quantify and evaluate such software adaptability at the architectural level. Besides, we define a relationship with the quality of service that the software must guarantee by means of a relation between the values of these metrics and the system quality requirements. The presented metrics can be used by the software architect to guide the system adaptation to fulfill the overall quality requirements.

Component-based software engineering is an influential trend in software engineering. Adopting component-based techniques, a system can be constructed by synthesis of various distributed components. This paper presents a framework of remote testing of distributed software components. Based on the CORBA architecture and Java technology, this paper provides an environment to allow a client-side software component to define tests for a black-box component published on the server-side. This technique simplifies test execution, test results check and report, and supports test reuse and test automation. The paper reveals a practical approach to test software components by enhancing software component testability and test re-usability. The incremental testing framework introduced in this paper is helpful in saving time, energy, and cost required for testing distributed components and for enhancing software quality. A testing supporting tool is implemented to facilitate distributed component testing based on CORBA

Service-Oriented Computing (SOC), a main trend in software engineering, promotes the construction of applications based on the notion of services. SOC has recently attracted a great deal of attention from researchers, and has been comprehensively adopted by industry. However, service composition enabling the aggregation of existing services into composite services still imposes a great challenge to service-oriented technology. Web service composition requires component Web services to be available in request, to behave correctly in operation, and to be replaceable flexibly in failure. Although availability of Web services plays a crucial role in building robust SOC-based applications, it has been largely neglected, especially for service composition. In this chapter, we propose a service composition framework that integrates a set of composition-based service discovery mechanisms, a user-oriented service delivery approach, as well as a service management mechanism for composite services.

DevOps [1] is a recent trend in software engineering that bridges the gap between software development and operations, putting the developer in greater control of the operational environment in which the application runs. To support Quality-of-Service (QoS) analysis, the developer may rely on software performance models. However, to provide reliable estimates, the input parameters must be continuously updated and accurately estimated. Accurate estimation is challenging because some parameters are not explicitly tracked by log files requiring deep monitoring instrumentation that poses large overheads, unacceptable in production environments.