A visualization and measurement environment for software engineering

Having a solid theoretical foundation is essential for designing an effective software visualization (SV) tool. Despite the decades of developing different SV tools, there are still doubts about their effectiveness. Furthermore, learner engagement plays an important role in building a successful SV tool. In programming education, the problem of the high failure rates among students is still unresolved. Therefore, there is a need to understand the theories behind the exciting SV tools from the engagement perspective in order to have a road map for future tool construction. Yet the factors influencing learner engagement in SV tools are still unclear. This study set out to determine how to develop an SV design model to enhance student engagement in an introductory programming course. A systematic literature review (SLR) was used to obtain an overview of the current theoretical foundation used. The search identified a total of 432 papers between 2011 and 2017. This study examined 58 papers selected based on a well-defined selection process. In this paper, the contribution in constructing the protocol for SLR is presented as well as the preliminary results of the study. The researchers were in the process of data extraction phase to address the research questions. The expected outcomes of this review became the identification of a theoretical background used to construct and explain engagement in software visualization. The expected output of this study was a list of the factors that have a positive impact on learner engagement in SV tools.

Software development is a fast-changing area. New methods and new technologies emerge all the time. As a result, the education of software engineering is generally considered not to be keeping pace with the development of software engineering in industry. Given the limited resources in academia, it is unrealistic to purchase all the latest software tools for classroom usage. In this chapter, the authors describe how free/open-source data and free/open-source tools are used in an upper-level software engineering class at Indiana University South Bend. Depending on different learning objectives, different free/open-source tools and free/open-source data are incorporated into different team projects. The approach has been applied for two semesters, where instructor’s experiences are assembled and analyzed. The study suggests (1) incorporating both free/open-source tools and free/open-source data in a software engineering course so that students can better understand both development methods and development processes and (2) updating software engineering course regularly in order to keep up with the advance of development tools and development methods in industry.

Software engineering education must be guided by developments in software engineering and aim for professional and educational development of students. This position paper explores the historical and conceptual evolution of software engineering as a discipline central to modern integrated design, software systems, and process science, tracing the trajectory from early structured models, through waterfall, to Agile and AI-augmented paradigms, and looks at how changes in application mix and modes of use, technological complexity, and business and enterprise needs have shaped development methodologies. Special attention is paid to the role of generative AI on the software engineering process and the role of the software engineer, altering workflows, collaboration, and enterprise architectures, and further enabling automation, digital transformation, and autonomous systems, shifting responsibilities and skill sets upwards. The article then considers corresponding shifts in software engineering education, highlighting the need for curricula that intertwine process thinking, systems theory, and ethical engagement, integrate with generative AI technologies, and place greater emphasis on “soft skills”, in courses that combine development of professional expertise with conceptual capabilities and an enhanced capacity for life-long learning. It then presents a set of requirements, options, and guidelines for software engineering education in the era of generative AI.

With the rapid development of science and technology, database programming technology has become more mature and perfect, and it has been widely used in the field of computer software engineering, laying a good foundation for the development of computer software engineering and the whole society. Based on this, this paper briefly introduces the database file generation process in computer software engineering, and then summarizes the database programming technology in computer software engineering. Based on this, it analyzes the importance of database programming technology in computer software engineering, discusses the application points of database programming technology in computer software engineering, and provides support for better application of database programming technology.

This chapter addresses the application of computer games and simulations in order to explore reality in many educational areas. The Games-Based Learning (GBL) can improve the teaching and learning experience by training future professionals in real life scenarios and activities that enable them to apply problem-solving strategies by putting into use the correct technique stemming from their own skills. For that reason, GBL has been used in software engineering teaching. At Pontifical Catholic University of Rio de Janeiro, the authors have developed SimulES-W (Simulation in Software Engineering), a tool for teaching software engineering. SimulES-W is a collaborative software board game that simulates a software engineering process in which the player performs different roles such as software engineer, technical coordinator, project manager, and quality controller. The players can deal with budget, software engineer employment and dismissal, and construction of different software artifacts. The objective of this chapter is to describe the approach to teaching software engineering using SimulES-W and demonstrate how pedagogical methodology is applied in this teaching approach to improve software engineering education. The teaching experience and future improvements are also discussed.

Too often, software engineering (SE) tool research is focused on creating small, stand-alone tools that address rarely understood developer needs. We believe that research should instead provide developers with flexible environments and interoperable tools, and then study how developers appropriate and tailor these tools in practice. Although there has been some prior work on this, we feel that flexible tool environments for SE have not yet been fully explored. In particular, we propose adopting the Web 2.0 idea of mashups and mashup environments to support SE practitioners in analytic activities involving multiple information sources.

Progress in software engineering has led to system development following models of the system life cycle. These models incorporate the use of prototyping and formal methods of program verification. They are becoming supported by integrated project support environments and permit the planning and monitoring of software development projects.In contrast, knowledge based systems (KBS) are developed using informal views of the system life cycle. Tools have been developed to support some stages of the life cycle in an undisciplined manner. The commercial use of KBS needs development projects to be planned and monitored. This requires methods and tools based on systematic life cycle models to be established for KBS.This paper reviews the current state of life cycle approaches to software engineering and KBS development projects in order to provide a direction for the development of methodical KBS life cycle models.

The quest by E&P companies and their service providers to gain a competitive edge through technology is driving a demand for higher standards in engineering software. Time to market is a critical success factor and is often viewed as contradictory to higher standards and other factors such as limited resources and budgets. An optimum approach to engineering software development can successfully satisfy both time-to-market and budgetary requirements while continually raising standards. This paper will discuss software practices that have proven effective during a full oilfield engineering software application development life cycle. Although the process activities – including specification, design, development, testing and deployment – were conventional, they were sequenced in a non-conventional manner and augmented with techniques such as risk management, use cases analysis, software modeling and configuration management. The paper presents a case study that illustrates how these practices were used in a sand control engineering software development project to successfully design and remodel an existing horizontal gravel pack spreadsheet application into a standalone desktop application. The new application provides a user-friendly interface to design and analyze gravel transport for solids of varying density in Newtonian fluids. A computation engine was developed as a plug-in component to perform various computations during the gravel packing process. An object-oriented architecture and framework were designed and built to avoid having to rebuild every new application from scratch. The authors will explain how the system was built and extended to incorporate new capabilities and how adopting optimized development practices has enabled reuse of software components in new applications and increased both the standards and cost-effectiveness of engineering software development.

During the process of appearance and development of software engineering, the thought originality plays a very important role. The paper analyzes several examples of the thought originality promoting development of software engineering, such as, understanding software and software development, the form of structuring software development method, the form of object-oriented software development method and the form of agile software development method. The paper is to point out except teaching the knowledge of software engineering; we must teach them the ideas of thought originality and strengthen the ideas of thought originality, during the process of software engineerpsilas teaching.

Specialized tools, such as IDEs, issue trackers, and code review tools, are an indispensable part of the modern software engineering process. These tools are constantly evolving. Besides enabling tools to support a wider range of technologies and frameworks, we are learning to provide additional features in completely new ways. One prominent stream of innovation in software engineering tools is dedicated to utilizing historical data to enable data-driven features, such as defect prediction engines and recommender systems, which leverage records of prior activity to assist with decision making. Many data-driven features in software engineering tools initially get born out of the context of real-world tools as techniques devised and evaluated in synthetic settings by researchers. While convenient, synthetic evaluation of approaches that are ultimately aimed at bringing improvement to real world problems involves a number of simplifications and assumptions. In this dissertation, we highlight several aspects that, while vital for bringing innovative methods to software engineering tools, are often discarded in existing research. We closely explore several topics specific to artificial evaluation environments, such as simplifications in mining file modification histories, use of synthetic datasets for source code authorship attribution, and a gap between accuracy of reviewer recommendation models and their perception by users. Moreover, we make a case for sharing technical artifacts by converting data mining pipelines into reusable tools, and propose a novel approach to modeling expertise transfer from code modification by capturing individual contribution style of developers. Key contributions of this dissertation include a high-level model of the lifecycle of a data-driven software engineering technique, a discussion of dangerous assumptions and simplifications that are made on every step in this lifecycle, a demonstration of importance of a careful approach to mining software repositories, and a demonstration of serious misalignment between artificial evaluation and realistic environments for the problems of code reviewer recommendation and code authorship attribution. We conclude the dissertation by discussing underlying reasons for misalignment between research environments and real-world tools, and propose potential steps to narrow it down and ultimately accelerate innovation in software engineering tooling.

: Software engineering tools are computer programs that assist people in doing the work of software engineering. As understanding of the software engineering process has broadened and the need to solve problems has intensified, there has been increasing interest in using software engineering tools. Understanding what a tool does and comparing it to similar tools are difficult tasks given the diversity of functionality that exists. This report describes a tool classification technique that helps those investigating tools decide where a tool fits in the software engineering process and identify what a tool does or doesn't do. It also provides guidance to the tool evaluation process and lists specific criteria that should be considered when evaluating tools.

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.

The work of our project is intended to help introducing digital technologies into nuclear power into nuclear power plant safety related software applications. In our project we utilize a combination of modern software engineering methods: design process discipline and feedback, formal methods, automated computer aided software engineering tools, automatic code generation, and extensive feasible structure flow path testing to improve software quality. The tactics include ensuring that the software structure is kept simple, permitting routine testing during design development, permitting extensive finished product testing in the input data space of most likely service and using test-based Bayesian updating to estimate the probability that a random software input will encounter an error upon execution. From the results obtained the software reliability can be both improved and its value estimated. Hopefully our success in the project's work can aid the transition of the nuclear enterprise into the modern information world. In our work, we have been using the proprietary sample software, the digital Signal Validation Algorithm (SVA), provided by Westinghouse. Also our work is being done with their collaboration. The SVA software is used for selecting the plant instrumentation signal set which is to be used as the input the digital Plant Protection System (PPS). This is the system that automatically decides whether to trip the reactor. In our work, we are using -001 computer assisted software engineering (CASE) tool of Hamilton Technologies Inc. This tool is capable of stating the syntactic structure of a program reflecting its state requirements, logical functions and data structure.

The open source movement has created and uses a set of software engineering tools with features that fit the characteristics of open source development processes. To a large extent, the open source culture and methodology are conveyed to new developers via the toolset itself, and through the demonstrated usage of these tools on existing projects. The rapid and wide adoption of open source tools stands in stark contrast to the difficulties encountered in adopting traditional Computer-Aided Software Engineering (CASE) tools. This chapter explores the characteristics that make these tools adoptable and discusses how adopting them may influence software development processes.

The constant advancement of processes, methods and tools in software engineering, as well as the steady rise in quality requirements and complexity of products require a systematic improvement approach. This article describes an organizational approach, called Software Experience Center (SEC), for the systematic and experience-based improvement of processes and products. In order to explain the structure and functioning of a SEC more easily the example of a store is used. The six areas of this store are described in more detail: The Shop Window, the Self-Service department, the Project Support Counter, the Information Network, the On-Site Service area and the Working Office. Two general groups with their requirements and functions form the focal point. On the one side is the development organization with their projects. The goal here is product development under given constraints of time, costs and quality. Requirements arise through the use of suitable processes, methods and tools. On the other side there is the SEC support team. This team has to fulfil the requirements coming out of the projects. In addition it has to detect and improve weak points in the whole development organization. Constant observation, reflection and evaluation of the assigned processes, methods and tools is necessary in order to fulfil these requirements. The experiences gained within the projects and the knowledge transfer beyond the project boundaries are the key factors.