Integrating Optimization Techniques in Software Development Life Cycle - SLR

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.

Estimation of Software Development Effort from Requirements Based Complexity

Software Engineering encompasses a lot of processes of which writing of efficient codes for development of high quality and effective programs is one of them. Development of quality software is achieved through a well-articulated Software Development Life Cycle (SDLC) model. Delivery of software project within timeline and budget require thorough analysis from which these two pertinent questions must be answered such as what shall we do next and how long shall we continue to do it’? Therefore, the need for an appropriate SDLC model for a software project is of high significance. V-Model is applicable in project that requires a lot of time and are complex in nature. When the focus of the project is more of quality than fast delivery time, then V-Model is a choice of SDLC to be considered. Also, Waterfall model is desirable when quality control is of concern with short project duration. On the other hand, Spiral Model is desirable when organizational expectations are unpredictable concerning the software development process. Irrespective of the size of the project, delivery time and level of expertise involved, the organization of the project plays a significant role in the choice of SDLC model. SDLC model under consideration, must take into cognizance the level of risk, duration of the project and cost implication associated with every software project for successful completion. Comparative analysis of the three SDLC models studied was presented.

Patterns are a means for capturing experience in solving general problems. They give general solutions to common and recurring problems. They exist at various phases of the software development life-cycle (SDLC), namely the analysis phase, the design phase, the coding phase and the testing phase. Patterns in each phase are identified independently. It is possible for the patterns of one phase to be related to patterns in other phases. This paper proposes pattern mapping to inter-relate the patterns of various phases in SDLC to address this issue. It is advantageous to capture the related patterns of different phases as a single unit for software development. Reusable integrated components (ICs) of patterns are proposed to capture the related patterns. A software IC is a group of inter-related patterns, that gives solutions for a recurring problem at various phases of SDLC. A representation mechanism for ICs is presented using the URA (Unified Representation of an Artifact) model, which captures the software development process. Also, this paper proposes a software development process that is based on reusable ICs of patterns. The representation of a software project developed using ICs is also discussed.

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.

Cybersecurity risks are increasing in frequency and complexity, but many organizations struggle to plan and implement adequate protections at all stages of the software development life cycle (SDLC). Security is frequently added at the end of development (afterthought), and making effective use of safeguard space is difficult for IT leaders. The purpose of this study is to produce an all‐encompassing framework to adopt and ensure security throughout each phase of the SDLC, from planning through maintenance. The aim is to minimize vulnerabilities and improve the resilience of software by making “security by design” a structure that not only adopts security elegantly as a living document but also is built to be part of the development process. This study adopted a mixed‐methods approach. The initial stage of inquiry involved a systematic literature review (SLR) to identify common cybersecurity issues associated with each SDLC phase. The SLR was followed by an empirical survey of 71 software professionals from a variety of organizations. The survey was designed to gather perceived threats, current practices, and challenges associated with software development for survey participants' organizations. The data collected were analyzed and reviewed statistically, through chi‐square tests and ANOVA, to profile the variance relative to the size of the organization, geographic region, and experience level of the practitioner. The results noted several high‐risk challenges across the SDLC: underfunded security controls, imprecise requirements, insecure architecture, software bugs (i.e., injection vulnerabilities), inadequate testing, misconfigured production environments, and unreliable maintenance. The proposed framework provides cybersecurity mitigation techniques for each stage of the SDLC, such as leveraging security‐oriented design patterns, secure coding policies (i.e., input validation and authentication protocols), robust testing (i.e., penetration testing and code review), and continuous monitoring after deployment. The implementation of these measures leads to a significant risk reduction in the overall organizational security posture. The framework is a formalized end‐to‐end approach to secure software development by embedding security throughout the cycle. Embedding security as a part of the process versus an afterthought at every stage of the cycle creates a risk reduction impact. This integrated approach also provides organizations with the opportunity to foresee and mitigate events earlier in the cycle, along with general compliance mandates (i.e., GDPR, HIPAA, and PCI‐DSS), to provide more resilient, trustworthy software systems.

Software effort estimation is a vital process in the software industry for successfully administering 5Ds of the software development life cycle (SDLC). The 5Ds stand for demand, development, direction, deployment, and designated cost of the software. Software development effort estimation (SDEE) is an effort prediction mechanism to calculate the effort for the development of the software product in order to minimize the challenges in the software field. Academics and practitioners are striving to identify which machine learning estimation technique yields more accurate results based on evaluation metrics, datasets, and other pertinent aspects. The feature selection techniques impact accuracy by selecting the main and relevant features in the dataset and eliminating the redundant and irrelevant features in the dataset. To achieve accurate estimations, the paper utilizes feature selection algorithms, along with various machine learning techniques, which predict the desired effort and the performance of the model has been measured in terms of prediction accuracy, value, relative error, and mean absolute error. The datasets China and Maxwell are trained with the relevant features by applying feature selection algorithms, and estimation techniques are applied to predict the effort. The performance is compared with the regression models and feature selection techniques utilized by many authors previously. The result of the proposed methodology significantly gives the best performance with the combination of feature selection and estimation models than all regression models when applied alone, to both datasets. From the results, it is perceptible that random forest is performing well with the feature selection techniques and obtains the highest prediction accuracy of 99.33% with the China and 89.47% with the Maxwell datasets.

Uptake of HCI and usability engineering by software development organisations can be terminally impeded by lack of appreciation of the benefits of HCI activities. However, descriptions of HCI offerings in terms of activities (e.g. task analysis, user mapping, allocation of function, interaction design) and methods (e.g. user profiling, prototyping, GOMS modelling) do not convey to product managers a readily comprehensible conception of the value of such offerings. Similarly, descriptions of HCI activities and methods give little indication of how these are to be associated and managed with reference to stages and deliverables in a software development life cycle. This lack of clear association between usability engineering and software engineering contributes to the marginalisation of usability related activities. Even when investment is made in usability resources its eventual pay off can be minimal, with resulting disillusionment on both sides. Specification of usability deliverables can provide a solid basis for a manageable usability perspective on the development of software products. The article identifies usability deliverables and describes their content and relation to deliverables in a software design and development process. More general implications for an approach to the specification of quality processes for the creation of interactive software products are discussed.

Apart from the different formats of software process descriptions and life cycle models as discussed in the previous chapter, there are many different types of such models. The basis for these models is formed by several fundamental life cycles, in particular sequential models such as the waterfall model or the V-shaped model, and iterative-incremental models such as the spiral model or Scrum. These fundamental life cycles can be varied in many forms, or extended by adding information leading to detailed process models such as the (Rational) Unified Process. The models can also include different sets of processes, where at one end of the spectrum, software processes support software development by structuring the different development-related activities. At the other end of the spectrum, software processes also provide a more comprehensive perspective, e.g. including operation and IT service management, or interfacing with organisational and administrative tasks. Depending on the purpose of the model, there are some very different types of process reference models available, including for example method-driven life cycle models, agile methodologies, process assessment models. In this chapter, we survey these different types of software processes and their role in the software life cycle. We provide a categorization of software processes, introduce the basic life cycle models, and present some selected reference models.

Due to ever‐changing technology and business requirements, the inefficiency and ineffectiveness of traditional plan‐driven software development life cycle models are being questioned. Software engineers have to find ways of improving software development processes by applying more agile principles to the traditional plan‐driven approaches. This paper addresses this issue and suggests how project and technical management can apply principles from the agile group of life cycle models to alleviate some of the problems encountered. Project characteristics that can be used to evaluate individual projects to determine the degree to which the software life cycle can be adapted, are indicated. Practices are also proposed for adapting traditional plan‐driven life cycle processes that can benefit from more agile approaches.

At present, software development life cycle has many standards involved. However, during the process of creating components in an application, there are many problems that originate in the knowledge gap between stakeholders and developers. The problem of developing is issues such as ambiguity, misunderstanding, miscommunications, different domain skills, and conflicting goals. Metamodel are needed because the methodology contents must be purpose-fit and optimally adjusted for the users/stakeholders/organisation. Metamodel, a model of software model includes endeavor domain, method domain, and metamodel domain. It has contents for user's needs, including organization, project, and product aspect. Three interconnected meta-elements are work products, work units, and producers, as well as relationship between them. ISO/IEC 24744 is the standard that includes metamodels.Application software are now applied knowledge management components aiming to reduce the gap between users/stakeholders and software developer team. The knowledge can be shared and transferred to others. This paper, therefore, focuses on applying knowledge management metamodel for software development process. We will extend the metamodel concept in ISO/IEC 24744 for knowledge acquisition, knowledge representation, and knowledge transfer to WorkUnits and WorkProducts, thereby increasing their explicitness in the software development process. Tacit knowledge will be focused and propose knowledge metamodel will be shown.

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.

The current software engineering practices observed in the local software industry generally lacks the software metrics planning part. The specific planning required to improve the software practices, to gauge the productivity of the individuals, and productivity at different phases of software development life cycle (SDLC), is generally missing. These organizations do not have any planning to gauge and control the business development issues and improve their productivities. During development phase, most of these software houses do collect data about different aspects of the project like project planning, requirement specification, testing, and bugs found. However, these organizations, generally, do not understand the importance of such data elements, how to maintain the data, how to built measurements plan, and most importantly how to use this data to improve their processes and productivity. In fact most of the time, the available data gets destroyed and hence never used. The current talk will discuss the need and importance of software metrics, the role of metrics in different phases of SDLC, and particularly the requirement phase. The requirement elicitation is considered as the most important aspect of software development, and if not handled properly, may cause severe productivity and quality issues. The talk will elaborate different metrics that may be used in requirement elicitation process and hence may help improve the requirement document resulting in improved productivity in the overall software development.

Accessibility modifications are required for individuals with situational, temporary, or permanent impairments to properly interact with web applications. Incorporating accessibility guidelines, such as the Web Content Accessibility Guidelines (WCAG), into software development, along with the software development life cycle and other paradigms, poses challenges. The linear progression of steps in a conventional software development process leads to the identification of problems at a later stage because testing is typically conducted toward the end. Limited attention to accessibility until the final development phase results in prolonged efforts, increased resource allocation, and higher expenses to address accessibility issues. Consequently, numerous software applications remain inaccessible to users with impairments. This study focuses on a Shift Left-based model to improve accessibility in the software development process. Employing the Shift Left a11y Model that emphasizes early integration for accessibility and coupling it with the Extreme Programming Development Life Cycle would enhance the integration of various testing practices and facilitate the development of software that is accessible to all users, including those with impairments. Keywords: Accessibility, accessible software, shift-left, model, methodology for accessible software

This history column article provides a tour of the main software development life cycle (SDLC) models. (A lifecycle covers all the stages of software from its inception with requirements definition through to fielding and maintenance.) System development lifecycle models have drawn heavily on software and so the two terms can be used interchangeably in terms of SDLC, especially since software development in this respect encompasses software systems development. Because the merits of selecting and using an SDLC vary according to the environment in which software is developed as well as its application, I discuss three broad categories for consideration when analyzing the relative merits of SDLC models. I consider the waterfall model before the other models because it has had a profound effect on software development, and has additionally influenced many SDLC models prevalent today. Thereafter, I consider some of the mainstream models and finish with a discussion of what the future could hold for SDLC models.