Reusable integrated components of inter-related patterns for software development

A fuzzy logic based approach for phase-wise software defects prediction using software metrics

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 security has become increasingly important because the malicious attack and other hacker risks of a computer system have grown popularity in the last few years. As a result, several researchers have examined security solutions as early as the requirement engineering phase. With the growth of the software business and the internet, there is a need to understand the security risks against each phase of the software development life cycle (SDLC). This study aims to empirically investigate and prioritize the risks that could negatively impact the software security aspects of SDLC in the context of global software development (GSD). To achieve the study objectives, we conducted an industrial empirical study to determine the impact of software security threats against each phase of SDLC. Furthermore, the fuzzy analytical hierarchy process (FAHP) was used to prioritize the list of software security risks against the SDLC. The results and analysis of this study provide a ranked‐based decision‐making framework, which assists the practitioners in considering the most critical security risks on priority. The results show “improper plan for secure requirement identification, inception, authentication, authorization, and privacy,” “lack of threat models updating,” “lack of output validation,” “lack of certification in the final release and archive,” and “spoofing” as the top‐ranked security risks of SDLC in GSD. In addition, the application of FAHP is novel in this domain as it is helpful to address multicriteria decision‐making problems.

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.

The software development life cycle (SDLC) encompasses diverse aspects, including design, requirements, methodologies, programming languages, tools, frameworks, and user interface design. Effective interoperability and integration among these components are crucial for streamlining workflows, mitigating compatibility issues, and delivering robust software solutions. This study employs the Grey Relational Analysis (GRA) method to evaluate the interoperability and relative importance of these SDLC elements in software development endeavors. The analysis reveals that fostering seamless collaboration among design, requirements, methodologies, languages, tools, and frameworks is essential for optimizing development processes and enhancing overall efficiency and effectiveness. The normalized data highlight the varying degrees of influence each component exerts across different SDLC phases, underscoring the need to recognize and leverage these interdependencies. The deviation sequence, obtained through the GRA method, unveils the relative importance or effectiveness of various elements, providing insights for informed decision-making and identifying areas for potential improvement or optimization. Furthermore, the Grey Relation Coefficient quantifies the correlations between different facets of software development, enabling stakeholders to prioritize areas for improvement and focus attention on elements with the most substantial influence. Notably, the final Grey Relational Grade (GRG) Rank reveals that testing frameworks secured the top rank, suggesting their significant impact on overall development quality, followed by programming languages and user interface design. These rankings offer valuable insights for prioritizing efforts and allocating resources, ultimately enhancing development processes and achieving better project outcomes. The study underscores the importance of a holistic and integrated approach to software development, recognizing the interdependencies among various components and leveraging the insights derived from the GRA method. By embracing this approach, software teams can make informed decisions, streamline workflows, and deliver high-quality, user-centric solutions that meet industry standards and drive success in an increasingly competitive digital landscape.

Accessibility and Software Engineering Processes: A Systematic Literature Review

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.

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.

This paper proposes a methodology for the development and its Verification and Validation(V&V) of safety-rated software. The development methodology is based on the structured analysis and structured design methodology, which has been proven in the field of safety software development during long period. The suggested the development and the V&V methodology additionally focuses on the quality attributes 3C+T (completeness, Correctness, Consistency and traceability), which are important criteria in IEC international standards. The software development life cycle is compiled from IEC international standardization, which are of the requirements analysis phase, design phase, implementation phase, testing phase, installation/commissioning phase, and operation & maintenance phases. The activities of the development process method were defined from requirements analysis to implementation, and the activities of the verification and validation were defined to include the scope of the developer's activities and then to include the test phase, installation/commissioning phase, and operation phases additionally. In other words, testing phase performed by the developer was defined as informal testing, and testing performed by the verifier according to test criteria, test plans, and test procedures was defined as formal testing. According to proposed methodology, the requirements phase defines the sequence of Entity Relationship Diagram (ERD)-Context Diagram-Data Flow Diagram (DFD), functional decomposition process and defines operational scenario. In the design phase, module design such as task analysis and task allocation were defined. In the implementation phase, we listed the coding guidelines that must be followed for safety-related system. The test phase defined the test criteria, test plan, test procedure, and test result report activities. In the installation/commissioning and operation phases, recommendations for improving reliability, quality, and safety were proposed for deliverables such as user documentation and technical documentation.

Artificial Intelligence (AI) integration has been the goal in many industries, including in the software development industry. One example of this integration comes in the form of integrating AI in the Software Development Lifecycle (SDLC). To date, the difficulties of incorporating AI-based tools into particular phases of SDLC have not received much attention in research. Using qualitative approach, this study aims to discover the perception on the use of AI-based tools and challenges in integrating them in the analysis phase of SDLC. The study finds out that analyst have positive perception about integrating this technology in their field of work but there are some challenges while integrating this technology such as data security and reliability concern, dependency, and adapting to this technology. This study also discovers some key factors of why some analysts adopt or refuse this technology namely time, urgency, budget, and insecurities of the users.

Practitioners as well as academics claim that the component-based software development paradigm is of major importance for the field of software engineering, and expect that in the near future most software systems will be developed following from components. Software organisations, applying component-based software-development technologies, are not only better able to handle complexity but also to reduce development times and cost by the systematic reuse of in-house and standard components. Thus, component-based development offers organisations a way to quickly react on market requirements.In practice the component-based development paradigm has only has a significant impact on the implementation phase of the software life cycle. Component technologies such as CORBA, JavaBeans/EJB, DCOM/AxtiveX and lately .NET basically allow the ‘technical’ cooperation of binary software building blocks of different origin. To counter this view there is a significant need to introduce the component-based development paradigm into all phases of the development life-cycle. In other words, the concept of a component should not just be seen as an implementation vehicle, but also as a central part of software design in term of concepts, methods and processes.The goal of this workshop is to examine the process of component-based software development in all phases of the development life-cycle (i.e., specification, design, composition, testing, deployment) and to identify how this process needs to be different from traditional software development. Participation is encouraged both from practitioners to provide their experiences and help in identifying open questions, and from researches to suggest methodological support for addressing these questions. The ultimate goals is thus to enable an exchange of experience between practitioners and researches concerning the relevance and feasibility of using the component paradigm throughout the software life-cycle.

Early software defect prediction: A systematic map and review

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.

Effective prediction of software modules, those that are prone to defects, will enable software developers to achieve efficient allocation of resources and to concentrate on quality assurance activities. The process of software development life cycle basically includes design, analysis, implementation, testing, and release phases. Generally, software testing is a critical task in the software development process wherein it is to save time and budget by detecting defects at the earliest and deliver a product without defects to the customers. This testing phase should be carefully operated in an effective manner to release a defect-free (bug-free) software product to the customers. In order to improve the software testing process, fault prediction methods identify the software parts that are more noted to be defect-prone. This paper proposes a prediction approach based on conventional radial basis function neural network (RBFNN) and the novel adaptive dimensional biogeography based optimization (ADBBO) model. The developed ADBBO based RBFNN model is tested with five publicly available datasets from the NASA data program repository. The computed results prove the effectiveness of the proposed ADBBO-RBFNN classifier approach with respect to the considered metrics in comparison with that of the early predictors available in the literature for the same datasets.

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.