Context: The software development industry is rapidly adopting machine learning for transitioning modern day software systems towards highly intelligent and self-learning systems. However, the full potential of machine learning for improving the software engineering life cycle itself is yet to be discovered, i.e., up to what extent machine learning can help reducing the effort/complexity of software engineering and improving the quality of resulting software systems. To date, no comprehensive study exists that explores the current state-of-the-art on the adoption of machine learning across software engineering life cycle stages. Objective: This article addresses the aforementioned problem and aims to present a state-of-the-art on the growing number of uses of machine learning in software engineering. Method: We conduct a systematic mapping study on applications of machine learning to software engineering following the standard guidelines and principles of empirical software engineering. Results: This study introduces a machine learning for software engineering (MLSE) taxonomy classifying the state-of-the-art machine learning techniques according to their applicability to various software engineering life cycle stages. Overall, 227 articles were rigorously selected and analyzed as a result of this study. Conclusion: From the selected articles, we explore a variety of aspects that should be helpful to academics and practitioners alike in understanding the potential of adopting machine learning techniques during software engineering projects.
University of Goettingen（哥廷根大学）；TU Clausthal（克劳斯塔尔工业大学）
Transformers are the current state-of-the-art of natural language processing in many domains and are using traction within software engineering research as well. Such models are pre-trained on large amounts of data, usually from the general domain. However, we only have a limited understanding regarding the validity of transformers within the software engineering domain, i.e., how good such models are at understanding words and sentences within a software engineering context and how this improves the state-of-the-art. Within this article, we shed light on this complex, but crucial issue. We co…
In the last couple of years we have witnessed an enormous increase of machine learning (ML) applications. More and more program functions are no longer written in code, but learnt from a huge amount of data samples using an ML algorithm. However, what is often overlooked is the complexity of managing the resulting ML models as well as bringing these into a real production system. In software engineering, we have spent decades on developing tools and methodologies to create, manage and assemble complex software modules. We present an overview of current techniques to manage complex software, an…
This paper represents preliminary work in identifying the foundation for the discipline of Software Engineering and discovering the links between the domains of Software Engineering and Information Technology (IT). Our research utilized IEEE Transactions on Software Engineering (IEEE-TSE), ACM Transactions on Software Engineering and Methodology (ACM-TOSEM), Automated Software Engineering (ASE), the International Conference on Software Engineering(ICSE), and other related journal publication in the software engineering domain to address our research questions. We explored existing frameworks a…
Software Engineering as an industry is highly diverse in terms of development methods and practices. Practitioners employ a myriad of methods and tend to further tailor them by e.g. omitting some practices or rules. This diversity in development methods poses a challenge for software engineering education, creating a gap between education and industry. General theories such as the Essence Theory of Software Engineering can help bridge this gap by presenting software engineering students with higher-level frameworks upon which to build an understanding of software engineering methods and practi…
Development of scientific and engineering software is usually different and could be more challenging than the development of conventional enterprise software. The authors were involved in a technology-transfer project between academia and industry which focused on engineering, development and testing of a software for optimization of pumping energy costs for oil pipelines. Experts with different skillsets (mechanical, power and software engineers) were involved. Given the complex nature of the software (a sophisticated underlying optimization model) and having experts from different fields, t…
Digitization not only affects society, it also requires a redefinition of the location of computer science and computer scientists, as the science journalist Yogeshwar suggests. Since all official aspects of digitalization are based on software, this article is intended to attempt to redefine the role of software engineering and its research. Software-based products, systems or services are influencing all areas of life and are a critical component and central innovation driver of digitization in all areas of life. Scientifically, there are new opportunities and challenges for software enginee…
The nature of software re-engineering is to improve or transform existing software so it can be understood, controlled and reused as new software. Needs, the necessity of re-engineering software has greatly increased. The system software has become obsolete no longer used in architecture, platform they're running, stable and consistent they support the development and support needs change. Software re-engineering is vital to restore and reuse the things inherent in the existing software, put the cost of software maintenance to the lowest in the control and establish a basis for the development…
The Continuous software engineering is a collaborative software development environment which offers the continues development and deployment of quality software project within short time. The Continuous software engineering practices are not yet mature enough, and the software organizations hesitate to adopt it. This study aims: (1) to explore the Continuous software engineering challenges by conducting systematic literature review (SLR) and to get the insight of industry experts via questionnaire survey study; (2) to prioritize the investigated challenges using fuzzy analytical hierarchy pro…
To legitimize itself as a scientific discipline, the software engineering academic community must let go of its non-empirical dogmas. A dogma is belief held regardless of evidence. This paper analyzes the nature and detrimental effects of four software engineering dogmas - 1) the belief that software has "requirements"; 2) the division of software engineering tasks into analysis, design, coding and testing; 3) the belief that software engineering is predominantly concerned with designing "software" systems; 4) the belief that software engineering follows methods effectively. Deconstructing the…
Given the data-intensive and collaborative trend in science, the software engineering community also pays increasing attention to obtaining valuable and useful insights from data repositories. Nevertheless, applying data science to software engineering (e.g., mining software repositories) can be blindfold and meaningless, if lacking a suitable knowledge architecture (KA). By observing that software engineering practices are generally recorded through a set of factors (e.g., programmer capacity, different environmental conditions, etc.) involved in various software project aspects, we propose a…
Software Engineering is the process of a systematic, disciplined, quantifiable approach that has significant impact on large-scale and complex software development. Scores of well-established software process models have long been adopted in the software development life cycle that pour stakeholders towards the completion of final software product development. Within the boundary of advanced technology, various emerging and futuristic technology is evolving that really need the attention of the software engineering community whether the conventional software process techniques are capable to i…
In the recent past, software product line engineering has become one of the most promising practices in software industry with the potential to substantially increase the software development productivity. Software product line engineering approach spans the dimensions of business, architecture, software engineering process and organization. The increasing popularity of software product line engineering in the software industry necessitates a process maturity evaluation methodology. Accordingly, this paper presents a business maturity model of software product line, which is a methodology to e…
Empirical methods like experimentation have become a powerful means to drive the field of software engineering by creating scientific evidence on software development, operation, and maintenance, but also by supporting practitioners in their decision making and learning. Today empirical methods are fully applied in software engineering. However, they have developed in several iterations since the 1960s. In this chapter we tell the history of empirical software engineering and present the evolution of empirical methods in software engineering in five iterations, i.e., (1) mid-1960s to mid-1970s…
Hidden Figures in Software Engineering: A Replication Study Exploring Undergraduate Software Students' Awareness of Distinguished Scientists from Underrepresented Groups
This article attempts to describe specific mental techniques that are related to resolving very complex tasks in software engineering. This subject may be familiar to some software specialists to different extents; however, there is currently no common consensus and popular terminology for this subject area. In this article, the area is charted from a practical usability perspective. This article also proposes to treat software engineering itself as research on human thinking because software is meant to simulate thinking.
In previous work we described how the process algebra based language PSF can be used in software engineering, using the ToolBus, a coordination architecture also based on process algebra, as implementation model. In this article we summarize that work and describe the software development process more formally by presenting the tools we use in this process in a CASE setting, leading to the PSF-ToolBus software engineering environment. We generalize the refine step in this environment towards a process algebra based software engineering workbench of which several instances can be combined to fo…
Context: Understanding the types of software engineering practices and techniques used in the industry is important. There is a wide spectrum in terms of the types and maturity of software engineering practices conducted in each software team and company. To characterize the type of software engineering practices conducted in software firms, a variety of surveys have been conducted in different countries and regions. Turkey has a vibrant software industry and it is important to characterize and understand the state of software engineering practices in this industry. Objective: Our objective is…
Software engineering has long studied how software developers work, building a body of work which forms the foundation of many software engineering best practices, tools, and theories. Recently, some developers have begun recording videos of themselves engaged in programming tasks contributing to open source projects, enabling them to share knowledge and socialize with other developers. We believe that these videos offer an important opportunity for both software engineering research and education. In this paper, we discuss the potential use of these videos as well as open questions for how to…
Six months ago an important call was made for researchers globally to provide insights into the way Software Engineering is done in their region. Heeding this call we hereby outline the position Software Engineering in Australasia (New Zealand and Australia). This article first considers the software development methods practices and tools that are popular in the Australasian software engineering community. We then briefly review the particular strengths of software engineering researchers in Australasia. Finally we make an open call for collaborators by reflecting on our current position and …
A broad class of software engineering problems can be generalized as the "total recall problem". This short paper claims that identifying and exploring total recall language processing problems in software engineering is an important task with wide applicability. To make that case, we show that by applying and adapting the state of the art active learning and text mining, solutions of the total recall problem, can help solve two important software engineering tasks: (a) supporting large literature reviews and (b) identifying software security vulnerabilities. Furthermore, we conjecture that (c…
Data scientists often develop machine learning models to solve a variety of problems in the industry and academy but not without facing several challenges in terms of Model Development. The problems regarding Machine Learning Development involves the fact that such professionals do not realize that they usually perform ad-hoc practices that could be improved by the adoption of activities presented in the Software Engineering Development Lifecycle. Of course, since machine learning systems are different from traditional Software systems, some differences in their respective development processe…
Current day software development relies heavily on the use of service architectures and on agile iterative development methods to design, implement, and deploy systems. These practices result in systems made up of multiple services that introduce new data flows and evolving designs that escape the control of a single designer. Academic privacy engineering literature typically abstracts away such conditions of software production in order to achieve generalizable results. Yet, through a systematic study of the literature, we show that proposed solutions inevitably make assumptions about softwar…
In previous work we described how the process algebra based language PSF can be used in software engineering, using the ToolBus, a coordination architecture also based on process algebra, as implementation model. We also described this software development process more formally by presenting the tools we use in this process in a CASE setting, leading to the PSF-ToolBus software engineering environment. In this article we summarize that work and describe a similar software development process for implementation of software systems using a client / server model and present this in a CASE setting…
Effective Requirements Engineering is a crucial activity in softwareintensive development projects. The human-centric working mode of Design Thinking is considered a powerful way to complement such activities when designing innovative systems. Research has already made great strides to illustrate the benefits of using Design Thinking for Requirements Engineering. However, it has remained mostly unclear how to actually realize a combination of both. In this chapter, we contribute an artifact-based model that integrates Design Thinking and Requirements Engineering for innovative software-intensi…
As software engineering research becomes more concerned with the psychological, sociological and managerial aspects of software development, relevant theories from reference disciplines are increasingly important for understanding the field's core phenomena of interest. However, the degree to which software engineering research draws on relevant social sciences remains unclear. This study therefore investigates the use of social science theories in five influential software engineering journals over 13 years. It analyzes not only the extent of theory use but also what, how and where these theo…
Quantum computing (QC) represents the future of computing systems, but the tools for reasoning about the quantum model of computation, in which the laws obeyed are those on the quantum mechanical scale, are still a mix of linear algebra and Dirac notation; two subjects more suitable for physicists, rather than computer scientists and software engineers. On this ground, we believe it is possible to provide a more intuitive approach to thinking and writing about quantum computing systems, in order to simplify the design of quantum algorithms and the development of quantum software. In this paper…
In empirical software engineering, benchmarks can be used for comparing different methods, techniques and tools. However, the recent ACM SIGSOFT Empirical Standards for Software Engineering Research do not include an explicit checklist for benchmarking. In this paper, we discuss benchmarks for software performance and scalability evaluation as example research areas in software engineering, relate benchmarks to some other empirical research methods, and discuss the requirements on benchmarks that may constitute the basis for a checklist of a benchmarking standard for empirical software enginee…
This short papers discusses the issues of teaching cloud computing from a software engineering rather than a business perspective. It discusses what topics might be covered in a senior course on cloud software engineering.
Digital transformation is a hot topic in the current global environment as a large number of organizations have been working to adopt digital solutions. Software engineering has also emerged to be a more important role as a large number of systems, either traditional or smart, are dependent on the software that collects, store, and process data. The role of software engineers has also become crucial in digital transformation. In this regard, this paper aims to examine the trends of software engineering and the role of software engineers in digital transformation. In addition to this, this pape…
Proceedings of the 5th International Workshop on Software Engineering Methods in Spreadsheets (SEMS'18), held on October 1st, 2018, in Lisbon, Portugal, and co-located with the 2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC).
Society today cannot run without software and by extension, without Software Engineering. Since this discipline emerged in 1968, practitioners have learned valuable lessons that have contributed to current practices. Some have become outdated but many are still relevant and widely used. From the personal and incomplete perspective of the authors, this paper not only reviews the major milestones and areas of interest in the Software Engineering timeline helping software engineers to appreciate the state of things, but also tries to give some insights into the trends that this complex engineerin…
This paper presents the core principles of reliability in software engineering - outlining why reliability testing is critical and specifying the process of measuring reliability. The paper provides insight for both novice and experts in the software engineering field for assessing failure intensity as well as predicting failure of software systems. Measurements are conducted by utilizing information from an operational profile to further enhance a test plan and test cases, all of which this paper demonstrates how to implement.
In 2014, a Microsoft study investigated the sort of questions that data science applied to software engineering should answer. This resulted in 145 questions that developers considered relevant for data scientists to answer, thus providing a research agenda to the community. Fast forward to five years, no further studies investigated whether the questions from the software engineers at Microsoft hold for other software companies, including software-intensive companies with different primary focus (to which we refer as software-defined enterprises). Furthermore, it is not evident that the probl…
Software Engineering practitioners work using highly diverse methods and practices, and general theories in software engineering are lacking. One attempt at creating a common ground in the area of software engineering methodologies has been the Essence Theory of Software Engineering, which can be considered a method-agnostic project management tool for software engineering. Essence supports the use of any development practices and provides a framework for building a suitable method for any software engineering context. However, Essence presently suffers from low practitioner adoption that is p…
Over the past years there has been quite a lot of activity in the algebraic community about using algebraic methods for providing support to model-driven software engineering. The aim of this workshop is to gather researchers working on the development and application of algebraic methods to provide rigorous support to model-based software engineering. The topics relevant to the workshop are all those related to the use of algebraic methods in software engineering, including but not limited to: formally specifying and verifying model-based software engineering concepts and related ones (MDE, U…
Based on the old but famous distinction between "in the small" and "in the large" software development, at Nancy Université, UHP Nancy 1, we experience for a while software engineering education thanks to actual project engineering. This education method has the merit to enable students to discover and to overcome actual problems when faced to a large project which may be conducted by a large development team. The mode of education is a simulation of an actual software engineering project as encountered in "real lifeé" activities.
This paper investigates the usefulness of PSF in software engineering and reengineering. PSF is based on ACP (Algebra of Communicating Processes) and as some architectural description languages are based on process algebra, we investigate whether PSF can be used at the software architecture level, but we also use PSF at lower abstract levels. As a case study we reengineer the compiler from the Toolkit of PSF.
In general, professionals still ignore scientific evidence in place of expert opinions in most of their decision-making. For this reason, it is still common to see the adoption of new software technologies in the field without any scientific basis or well-grounded criteria, but on the opinions of experts. Experimental Software Engineering is of paramount importance to provide the foundations to understand the limits and applicability of software technologies. The need to better observe and understand the practice of Software Engineering leads us to look for alternative experimental approaches …
Systems Engineering (SE) is the set of processes and documentation required for successfully realising large-scale engineering projects, but the classical approach is not a good fit for software-intensive projects, especially when the needs of the different stakeholders are not fully known from the beginning, and requirement priorities might change. The SKA is the ultimate software-enabled telescope, with enormous amounts of computing hardware and software required to perform its data reduction. We give an overview of the system and software engineering processes in the SKA1 development, and t…
