Agile Development with 3D Data Modeling

Software Engineering: A Methodical Approach (Second Edition) provides a comprehensive, but concise introduction to software engineering. It adopts a methodical approach to solving software engineering problems, proven over several years of teaching, with outstanding results. The book covers concepts, principles, design, construction, implementation, and management issues of software engineering. Each chapter is organized systematically into brief, reader-friendly sections, with itemization of the important points to be remembered. Diagrams and illustrations also sum up the salient points to enhance learning. Additionally, the book includes the author’s original methodologies that add clarity and creativity to the software engineering experience. New in the Second Edition are chapters on software engineering projects, management support systems, software engineering frameworks and patterns as a significant building block for the design and construction of contemporary software systems, and emerging software engineering frontiers. The text starts with an introduction of software engineering and the role of the software engineer. The following chapters examine in-depth software analysis, design, development, implementation, and management. Covering object-oriented methodologies and the principles of object-oriented information engineering, the book reinforces an object-oriented approach to the early phases of the software development life cycle. It covers various diagramming techniques and emphasizes object classification and object behavior. The text features comprehensive treatments of: Project management aids that are commonly used in software engineering An overview of the software design phase, including a discussion of the software design process, design strategies, architectural design, interface design, database design, and design and development standards User interface design Operations design Design considerations including system catalog, product documentation, user message management, design for real-time software, design for reuse, system security, and the agile effect Human resource management from a software engineering perspective Software economics Software implementation issues that range from operating environments to the marketing of software Software maintenance, legacy systems, and re-engineering This textbook can be used as a one-semester or two-semester course in software engineering, augmented with an appropriate CASE or RAD tool. It emphasizes a practical, methodical approach to software engineering, avoiding an overkill of theoretical calculations where possible. The primary objective is to help students gain a solid grasp of the activities in the software development life cycle to be confident about taking on new software engineering projects.

This article presents an epistemological reading of knowledge evolution in software engineering (SE) both within a software project and into SE theoretical frameworks principally modeling languages and software development life cycles (SDLC). The article envisages SE as an artificial science and notably points to the use of iterative development as a more adequate framework for the enterprise applications. Iterative development has become popular in SE since it allows a more efficient knowledge acquisition process especially in user intensive applications by continuous organizational modeling and requirements acquisition, early implementation and testing, modularity,… SE is by nature a human activity: analysts, designers, developers and other project managers confront their visions of the software system they are building with users’ requirements. The study of software projects’ actors and stakeholders using Simon’s bounded rationality points to the use of an iterative development life cycle. The later, indeed, allows to better apprehend their rationality. Popper’s knowledge growth principle could at first seem suited for the analysis of the knowledge evolution in the SE field. However, this epistemology is better adapted to purely hard sciences as physics than to SE which also takes roots in human activities and by the way in social sciences. Consequently, we will nuance the vision using Lakatosian epistemology notably using his falsification principle criticism on SE as an evolving science. Finally the authors will point to adaptive rationality for a lecture of SE theorists and researchers’ rationality.

Software lifecycles are becoming an increasingly important issue for computational science & engineering (CSE) software. The process by which a piece of CSE software begins life as a set of research requirements and then matures into a trusted high-quality capability is both commonplace and extremely challenging. Although an implicit lifecycle is obviously being used in any effort, the challenges of this process-respecting the competing needs of research vs. production-cannot be overstated. Here we describe a proposal for a well-defined software life-cycle process based on modern Lean/Agile software engineering principles. What we propose is appropriate for many CSE software projects that are initially heavily focused on research but also are expected to eventually produce usable high-quality capabilities. The model is related to TriBITS, a build, integration and testing system, which serves as a strong foundation for this lifecycle model, and aspects of this lifecycle model are ingrained in the TriBITS system. Indeed this lifecycle process, if followed, will enable large-scale sustainable integration of many complex CSE software efforts across several institutions.

The software development process model or what is commonly called SDLC (Software Development Life Cycle) is one of the Software Engineering (RPL) course materials in the Information Engineering Education (PTI) undergraduate study program where one of the competencies is understanding and knowing the concepts of device engineering software that can be applied in the software development life cycle which is summarized in the material for the SDLC software development process model. This material is the initial material that must be mastered by students to develop quality software. The use of interactive and interesting computer assisted learning media is expected to help the stages of the student learning process properly. This requires an interactive learning multimedia application. The purpose of this research is to develop interactive learning media as an alternative to independent learning tools to assist students in mastering the Software Development Process Model (SDLC) material for students and to find out the feasibility of multimedia application products for learning the Software Development Process Model (SDLC). The research and development methodology used in this research is Research and Development (R&D) with Borg and Gall's development steps which include: (1) Research and data collection; (2) Planning; (3) Development of product drafts; (4) Initial field trials; (5) Revision of trial results (6) Field trials; (7) Product improvement; (8) Field implementation test; (9) Completion of the final product; and (10) Dissemination of implementation. This methodology covers all matters relating to development to produce quality interactive learning media software. Based on the trials, the results obtained were 90.63 percent from media experts, 98.08 percent from material experts, 85.46 percent from initial field trials, 84.56 percent from field trials, and 86.27 percent from field implementation trials. The average value obtained is 89 percent based on the results of the overall data analysis. The conclusion of this research is that the development of multimedia applications for learning the Software Development Process Model (SDLC) is feasible as an independent learning medium. The product produced in this development research is a multimedia application for learning flash-based software development process (SDLC) models.

The aim of this article is to describe a method that helps analysts to translate qualitative data gathered in the field, collected for the purpose of requirements specification, to a model usable for software engineers. Requirements specification constitutes three different parts: functional requirements, quality requirements, and nonfunctional requirements. The first one specifies how the software system should function, who are the actors, and what are the input and output of the functions. The second one specifies what quality requirements the software should meet while operating in context of its environment such as reliability, usability, efficiency, portability, and maintainability. Finally, the third part specifies other requirements including context of use and development constraints. Examples of context of use are where and when the system is used, and examples of development constraints are human resources, cost and time constraints, technological platforms, and development methods. The role of the requirements specification is to give software engineers a basis for software design, and, later in the software development life cycle, to validate the software system. Requirements specification can also serve the purpose of validating users’ or customers’ view of the requirements of the system. On one hand, there has been a growing trend towards analyzing needs of the user and abilities through participatory design (Kuhn & Muller, 1993), activity theory (Bertelsen & Bødker, 2003), contextual design (Beyer & Holtzblatt, 1998), user-centered design (Gulliksen, Göransson, & Lif, 2001), and co-design and observation as in ethnography (Hughes, O’Brien, Rodden, Rouncefield, & Sommerville, 1995). Common to these methods is that qualitative data (Taylor & Bogdan, 1998) is collected, to understand the future environment of the new system, by analyzing the work or the tasks, their frequency and criticality, the cognitive abilities of the user and the users’ collaborators. The scope of the information collected varies depending on the problem, and sometimes it is necessary to gather data about the regulatory, social, and organizational contexts of the problem (Jackson, 1995) to be solved. The temporal and spatial contexts describe when the work should be carried out and where. On the other hand, software engineers have specified requirements in several different modelling languages that range from semiformal to formal. Examples of semiformal languages are UML (Larman, 2002), SADT, and IDEF (Ross, 1985). Examples of the latter are Z (Potter, Sinclair, & Till, 1996), VDM or ASM. Those are modelling languages for software development, but some languages or methods focus on task or work modelling such as Concurrent Task Trees (Paterno, 2003) and Cognitive Work Analysis (Vicente, 1999). Others emphasize more the specification method than a modelling language. Examples of the former are Scenario-Based Design (SBD) (Rosson & Carroll, 2002) and Contextual Design (Beyer & Holtzblatt, 1998). In practice, many software developers use informal methods to express requirements in text, e.g., as narrations or stories. Agile Development Methods (Abrahamsson, Warsta, Siponen, & Ronkainen, 2003) emphasize this approach and thereby are consistent with their aim of de-emphasizing methods, processes, and languages in favor of getting things to work. A popular approach to requirements elicitation is developing prototypes. There has been less emphasis on bridging the gap between the above two efforts, for example, to deliver a method that gives practical guidelines on how to produce specifications from qualitative data (Hertzum, 2003). One reason for this gap can be that people from different disciplines work on the two aspects, for example, domain analysts or experts in HCI, and software engineers who read and use requirements specification as a basis for design. Another reason for this gap may be in the difference in the methods that the two sides have employed, that is, soft methods (i.e., informal) for elicitation and analysis and hard methods (i.e., formal) for specification. In this article, we suggest a method to translate qualitative data to requirements specification that we have applied in the development of a Smart Space for Learning. The process borrows ideas from or uses scenarios, interviews, feature-based development, soft systems methodology, claims analysis, phenomenology, and UML.

Today, the most vital step is software testing, especially in product quality. Agile software development is exceedingly difficult and has contentious issues in literature and business. Since most Agile techniques place more emphasis on development than software testing activities, different people have varying opinions about how software testing fits into these methodologies. Agile places a high emphasis on frequent deliveries and tight client connections. However, software testing is complex because agile does not incorporate many destructive testing techniques typically required for a product of higher-quality. The study reveals industry-wide Agile testing procedures and the main problems that arise when Agile development is used. Additionally covered are the differences between manual and automated testing, best automation practices, and ways to lead different testing teams in an agile testing environment. This study covers every facet of the Agile software testing process. Agile development has shown that testing is not a distinct stage but rather a crucial component of software development along with the coding. The agile team employs an overall strategy to produce software products of the highest quality. As part of an agile team, testers collect customer samples of the desired behaviour and collaborate with the developer's team to help the coders translate these examples into executable specifications. Coding and testing are done iteratively and incrementally, developing every item until it is valuable enough to release in production. It addresses several testing modalities. The classification provided by its quadrants aids teams in determining and organizing the necessary tests. To increase quality assurance, this article will examine various and improved Agile Testing Processes and methodologies. Additionally, the topic of Agile development's software testing method is covered. Agile development processes can be improved and more advantageous by incorporating testing procedures.

Computer‐aided software engineering (CASE) is both a field of study and a marketplace. As a field of study, it is the collection of research and development over many years in software development management, methods, environments, and software tools. In general terms, CASE is the industrialization of software engineering techniques and computer technology to improve and automate the practice of information systems development. It is an integration technology that incorporates software development techniques, tools, and approaches into common and consistent frameworks. CASE draws on technologies from computer‐aided design, software engineering, operating systems, database, networking, and many other computer disciplines. Thus CASE is not principally a field of new invention. Rather, it is a field of application, integration, and synthesis. As a marketplace, CASE represents a diverse set of products and services for software development and systems integration. The acronym CASE is used as an umbrella for a wide variety of claims regarding software tools and software development productivity. Definitions of CASE are given. CASE evironments, automation of analusis, computer‐supported collaboration, apportunities for quality engineering, maintenance and reengineering are discussed.

Harmful software has resulted in loss of life, societal and environmental damage alongside economic losses from fines and sales embargoes. When someone perceives their team or organisation is creating or operating harmful software (e.g., defective, vulnerable, malicious or illegal), one way to attempt to change the situation is to “blow the whistle” and disclose the situation internally or externally. Studying harmful situations and the effectiveness of interventions, up to and including whistleblowing, can help identify technical and human successes and failings in software engineering (SE). The aim of this paper is to explore the extent to which whistleblowing is studied in SE with the objective of identifying themes, research approaches, gaps and concerns, and the implications for future SE research and practice. We find that whistleblowing is an under-explored area of SE research, and where research exists, it often takes the view that reporting harm is a matter of individual moral responsibility; we argue this poorly reflects SE collaborative practice where professional responsibilities are distributed across the software development lifecycle. We conclude by 1) recommending approaches that can help a more timely identification and mitigation of harm in SE; 2) suggesting mechanisms for improving the effectiveness and the personal safety of harm-reporting in SE, and 3) reflecting on the role that professional bodies can have in supporting harm reporting, up to and including whistleblowing.

The software development life cycle (SDLC) is a structured process for delivering a high-quality product within a specified timeframe. Developing a cost-effective and efficient software product life cycle has always been a priority in software engineering, which can impact product quality. This study aims to provide an overview of the recent articles that focus on applying optimization techniques, mathematical models, and software cost estimation in the software development process and propose possible future directions. For the selected 29 studies, the development phase of the SDLC is most commonly focused on in studies. This emphasis highlights the pivotal role of optimization and mathematical modeling in enhancing software development efficiency.

This paper describes an approach to integrating software engineering concepts and principles into the Electrical and Computer Engineering (ECE) and Computer Science (CS) curricula. Our philosophy is to apply software engineering techniques throughout the ECE/CS curricula to leverage learning in non-software engineering courses. Our technique is to seek out faculty interested in innovative teaching techniques, consult with them to identify some way that they and we feel a course they are teaching could benefit pedagogically from some application of software engineering, and work with them to make that happen. The chief intended result is to leverage learning in diverse courses, thereby benefiting pedagogy of non-software engineering topics. An auxiliary important result is to increase awareness among both students and faculty of the software engineering body of knowledge. Many software engineering approaches to understanding and solving problems in the software life cycle can also address a variety of learning needs across disciplines in ECE and CS. For example, there are software engineering techniques that can emphasize visualization (benefiting students who respond to the visual modality), logical sequences (benefiting sequential learners), summarizations (benefiting global learners), and others. Additionally, general issues of teamwork and the engineering life cycle can be addressed. We have applied our approach to a diverse set of electrical engineering and computing courses at four universities in the US and Canada, and based on those experiences we believe we have identified a win-win paradigm that can be a model for integration of software engineering concepts into electrical engineering and computing curricula.

About Our Authors

У статті розкриваються погляди на методологію та порядок оцінювання спеціального програмного забезпечення з урахуванням вимог Національних стандартів України ДСТУ ISO/ІЕС 25010:2016 (ISO/ІЕС 25010:2011, IDT). “Інженерія систем і програмних засобів. Вимоги до якості систем і програмних засобів та її оцінювання. Моделі якості системи та програмних засобівˮ та ДСТУ ІS0/ІЕС 9126-1:2013 (ІS0/ІЕС 9126 1:2001, IDТ). “Програмна інженерія. Якість продукту. Частина 1. Модель якостіˮ. Як приклад розглядається перевірка якості спеціального програмного забезпечення для управління військами.

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.

Large Language Models (LLM) are reshaping the field of Software Engineering (SE). They enable innovative methods for executing many SE tasks, including automation of entire process of Software Development Life Cycle (SDLC). However, only a limited number of existing works have thoroughly explored the potential of LLM based AI agents to automate the entire lifecycle in SE. In this paper, we demonstrate the success of our initial efforts in automating the entire lifecycle autonomously based on given software specification as input, which has shown remarkable efficiency and significantly reduced development time. Our preliminary results suggest that the careful implementation of AI agents can enhance the development lifecycle. We aim to streamline the SDLC by integrating all phases into an AI-driven chat interface, enhancing efficiency and transparency. Furthermore, we seek to enhance collaboration, creating an environment where stakeholders from various backgrounds can contribute, review, and refine ideas and requirements in real-time. This forward-looking direction guarantees to redefine the paradigms of SE and also make software creation more inclusive, collaborative, and efficient.

Analysis and validation using simulation is a helpful tool in systems engineering, but requires in-depth knowledge of various aspects of the system itself, the used model class(es), an appropriate software tool, and sometimes software engineering. Usually, this expertise is spread over a number of team members, and thus the development of a simulation-based system design tool is not a simple task. This paper presents a framework enabling the rapid development of extensible and reusable simulation-based applications. It supports an agile, iterative, evolutionary, and architecture-centric software development process. The design of the framework together with its components as well as the corresponding software development process is described. As an example, an environment for the configuration and analysis of wireless sensor network applications in the aeronautic domain is presented, which has been designed and implemented based on the proposed environment.