Traditional Software Development Methods Research Articles

Software Engineering in Nigeria: Trends and Challenges

Bringing theory and practice together is aspiration of software engineering education, so that the learner may acquire a deep understanding on basic concepts and principles, along with skills and competences to solve real-world problems. Thus, it is not just an academic concern about teaching relevant topics, but also a task to shape skilled individuals equipped for the industry demand. Moreover, due to the rapid development the software industry is and transnational nature, several challenges are challenging the qualification of software engineers, capable to develop products according to the international standards into markets overseas. Agile software development methods are the generally used and prominent software development methods. Agile methods are simple, easy and deliver software faster than the traditional software development methods. Software development in Nigeria is at developing stage.

Pervasive Computing For New Design In Big Data Analytics Software Development: Requirements Engineering Perspective

In recent years, the field of big data has been rapidly growing and has become a crucial aspect of many industries. The ability to collect, analyze, and interpret massive amounts of data has enabled businesses to make more informed decisions and has led to the development of new products and services. However, with the increase in data volume, velocity, and variety, traditional software development methods have become inadequate. This has led to the emergence of new design approaches that can handle the complexities of big data. Big data is very important nowadays for business organizations to make smart decisions based on insight gained from the big data. These benefit the organization to be competent in the market as well as to maximize their profit. However, there is a high rate of big data software project failure. This is due to a lack of new design approaches that can handle different dimensions of requirements for big data. The objective of this paper is to show how the pervasive computing / pervasive requirements engineering approach should be considered for big data software development based on different perspectives in pervasive environments to design new software

Structured software development versus agile software development: a comparative analysis

The use of agile methodology has become widespread in organizations that previously relied on traditional or structured software development methods, such as the waterfall approach. Successful completion rates for agile initiatives are at 40%, whereas only 15% of waterfall projects were successfully completed. To take advantage of the benefits of each method, many organizations are using a hybrid approach that combines Agile with Waterfall and structured software development methodologies. Rather than asking which methodology is superior, it is more productive to determine which one is most effective for a particular project. Agile projects have a failure rate of 10%, while waterfall projects fail 30% of the time. This study aims to compare and contrast agile and waterfall methodologies in order to create a decision tree for selecting the most suitable method for a software development project. Several cases and scenarios are examined using the hybrid development approach. Despite many advantages of Agile methodologies, a combination approach may be necessary, as Waterfall may be required for certain projects or development phases. This study explores the feasibility of combining Waterfall and Agile methodologies in software development management.

Role of Agile Methodologies for Ensuring Quality in Complex Systems: A Systematic Literature Review

In software development, the selection of a software process model set the base for the success of a software product. An inappropriate selection may lead to a delay in project release, introduce defects and make the project difficult to update. This lack of quality characteristics may lead to the risk of losing customer expectations as well as the failure of the project itself. In the case of complex systems, the problems become more severe. To meet such expectations, agile methodologies are used to ensure quality in software and meet customers’ expectations. There is currently no literature that gives insights into the role of agile methodologies in ensuring quality in complex systems. The purpose of this paper is to evaluate the effectiveness and the impact of agile methodology in achieving the quality of complex systems. For this, we perform a Systematic Literature Review (SLR) and define a review protocol. By performing a thorough search and screening, we selected 39 papers related to agile methods and complex systems. Our analysis shows that complex systems have various requirements of quality attributes some of the complex systems mainly focus on security, reliability, and efficiency whereas other emphasizes safety, response time, and maintainability. Our analysis also shows that agile methodologies are widely used for the development of complex systems because ensuring the quality requirements of complex systems is not possible with the use of traditional methods of software development.

HealMA: a model-driven framework for automatic generation of IoT-based Android health monitoring applications.

The development of IoT-based Android health monitoring mobile applications (apps) using traditional software development methods is a challenging task. Developers need to be familiar with various programming languages to manage the heterogeneity of hardware and software systems and to support different communication technologies. To address these problems, in this paper, we first analyze the domain of health monitoring mobile applications and then propose a framework based on model-driven engineering that accelerates the development of such systems. The proposed framework, called HealMA, includes a domain-specific modeling language, a graphical modeling editor, several validation rules, and a set of model-to-code transformations, all packed as an Eclipse plugin. We evaluated the framework to assess its applicability in generating various mobile health applications, as well as its impact on software productivity. To this end, four different health monitoring applications have been automatically generated. Then, we evaluated the productivity of software developers by comparing the time and effort it takes to use HealMA compared to a code-centric process. As part of the evaluation, we also evaluated the usability of HealMA-generated apps by conducting a user study. The results show that HealMA is both applicable and beneficial for automatic generation of usable IoT-based Android health monitoring apps.

Role of ITOps in DevOps

The IT industry is transforming itself by adopting DevOps through a combination of development practices, cultural philosophies, software tools that increases the ability to deliver products and applications at high velocity by continuously improving delivery at a faster pace than using traditional software development methods. The success of DevOps relies on the culture of collaborative development, continuous Integration, strong agile principles, reduce time and faster feedback loops, automation of testing and operations work. The expectation of IT Operations is to scale up to the need of provisioning the required hardware infrastructure at the speed of DevOps. This would involve ITOps to be highly efficient and adopt lean principles and culture in terms of hardware procurement and provisioning, network infrastructure, server and device management, IT operations and help desk support. There is a great divide between DevOps which demands Agility and change, verses ITOps that wants to adopt principles of Stability, Compliances and Governance. This paper talks about challenges of both practices and how they could bridge the gap and come together to make the change for a digital transformation.

Evaluating Model-Driven Development Claims with Respect to Quality: A Family of Experiments

Context: There is a lack of empirical evidence on the differences between model-driven development (MDD), where code is automatically derived from conceptual models, and traditional software development method, where code is manually written. In our previous work, we compared both methods in a baseline experiment concluding that quality of the software developed following MDD was significantly better only for more complex problems (with more function points). Quality was measured through test cases run on a functional system. Objective: This paper reports six replications of the baseline to study the impact of problem complexity on software quality in the context of MDD. Method: We conducted replications of two types: strict replications and object replications. Strict replications were similar to the baseline, whereas we used more complex experimental objects (problems) in the object replications. Results: MDD yields better quality independently of problem complexity with a moderate effect size. This effect is bigger for problems that are more complex. Conclusions: Thanks to the bigger size of the sample after aggregating replications, we discovered an effect that the baseline had not revealed due to the small sample size. The baseline results hold, which suggests that MDD yields better quality for more complex problems.

Analysis, Integration and Testing the Component Based Adoption Techniques During Runtime Configuration

Component based Software Engineering is the most common term nowadays in the field of software development. The CBSE approach is actually based on the principle of ‘Select and Use’ rather than ‘Design and Test’ as in traditional software development methods. Since this trend of using and ‘reusing’ components is in its developing stage, there are many advantages and problems as well that occur while use of components. Here is presented a series of papers that cover various important and integral issues in the field concerned. This paper is an introductory research on the approaches, development process, various phases and assessment available in commercialized models in CBD.

Factors Influencing the Efficacy of Agile Usage

Agile techniques that utilize iterative development are broadly used in various industry projects as a lightweight development technique which can satisfy the continuous changes of requirements. Short repetitions are used that are required for efficient product delivery. Traditional and old software development methods are not much efficient and effective to control the rapid change in requirements. Despite the benefits of Agile, criticism on agile methodology states that it couldn’t succeed to pay attention to architectural and design issues and therefore is bound to produce small design-decisions. The past decade has observed numerous changes in systems development with many organizations accepting agile techniques as a viable methodology for developing systems. An increase in the number of research studies reveals the growing demand and acceptance of agile methodologies. While most research has focused on acceptance rate and adaptation of agile practices, there is very limited knowledge of their post-adoption usage and incorporation within organizations. Several factors explain the effective usage of agile methodologies. A combination of previous research in Agile Methodologies, Diffusion of Innovations, Information Systems implementation, and Systems Development has been carried out to develop a research model that identifies the main factors relevant to the propagation and effective usage of agile methodologies in organizations.

A Technique for Transitioning Of Plan Driven Software Development Method to Distributed Agile Software Development

In the era of twenty first century where human being is moving forward from semi – automated systems to fully automatic and machine learning based systems, software development (SD) mechanisms have also moved from static and pretended process following mechanisms to fast, ready for advices and adaptability based software development methods. Due to this traditional software development methods following heavy documentation based step by step processes have become obsolete and software development industry is transitioning towards dynamic, incremental, iterative, customer – centered, light – documentation based system development mechanisms referred as Agile Software development (ASD). The transition becomes more attention grabbing in distributed environment referred as distributed Agile software development (DASD). Certain processes like – task allocation, backlog prioritization, test case reduction and prioritization use manual processes rather than semi or fully automated processes. This methodology of transformation needs transitioning changes in existing DASD systems. In this paper we have proposed framework for transitioning of plan driven software development method to distributed Agile software development. The major area of concern is to automate the manual processes followed and convert them to semi – automated and fully – automated processes.

The DevOps Phenomenon

Stressful emergency releases are a thing of the past for companies that subscribe to the DevOps method of software development and delivery. New releases are frequent. Bugs are fixed rapidly. New business opportunities are sought with gusto and confidence. New features are released, revised, and improved with rapid iterations. DevOps presents a strategic advantage for organizations when compared with traditional software-development methods. Leadership plays an important role during that transformation. DevOps is about providing guidelines for faster time to market of new software features and achieving a higher level of stability. Implementing cross-functional, product-oriented teams helps bridge the gaps between software development and operations. By ensuring their transformations include all of the principles outlined in CALMS, teams can achieve superior performance and deliver value to their organizations. DevOps is often challenging, but stories from across the industry show that many organizations have already overcome the early hurdles and plan to continue their progress, citing the value to their organizations and the benefits to their engineers.

Reviewing Commonalities between Agile Software Development Methodology and Grounded Theory Methodology

Agile development method has attracted widespread corporate and academic attention as the limitations of traditional software development method become apparent. Similarly focusing on inductive knowledge creation, grounded theory method has achieved seminal status in social science. But there is no attempt so far to identify synergies between these two popular methodologies of diverse fields, so that social science researchers can benefit by using principles and practices of agile methodology. This paper identifies the similarities between these two methods in terms of the underlying philosophy as well as important practices. Focusing on these similarities, multiple recommendations regarding enriching grounded theory method with components of agile methodologies were made. The paper serves as an initial work on an important emerging methodology debate, which need to be further explored, enhanced and detailed.

Transitioning to agile software development: Lessons learned from a government-contracted program

With a need to implement an agile software development methodology in government programs, this study was conducted to explore how organizations transitioned from a traditional waterfall software development method to agile methods. To accomplish this study, a case study research was utilized. A multimillion-dollar government-contracted program in the US was studied. The research findings reveal key challenges faced by organizations during the transition and the lessons learned that can be applied to future programs. Propositions for future research are also presented.

Effort estimation in agile software development using experimental validation of neural network models

Frequent requirement changes are a major point of concern in today’s scenario. As a solution to such issues, agile software development (ASD) has efficiently replaced the traditional methods of software development in industries. Because of dynamics of different aspects of ASD, it is very difficult to keep track, maintain and estimate the overall product. So, in order to solve the effort estimation problem (EEP) in ASD, different types of artificial neural networks (ANNs) have been applied. This work focuses on two types of ANN-feedforward back-propagation neural network and Elman neural network. These two networks have been applied to a dataset which contains project information of 21 projects based on ASD from 6 different software houses to analyze and solve the EEP. Also, the proposed work uses three different performance metrics i.e. mean magnitude of relative error (MMRE), mean square error (MSE) and prediction (PRED(x)) to examine the performance of the model. The results of the proposed models are compared to the existing models in the literature.

The Adoption of Agile Software Methodology with Team Software Process (TSPI) Practices in the Software Engineering Undergraduate Course


 
 
 In computer science, software engineering courses expose the undergraduate students to both the technical and methodological aspects of software development. The traditional software development methods and techniques represent a huge proportion of the courses and hence contribute an essential part of software engineering students’ development process. This plan-driven development is dependent on a set of predefined phases and ongoing documentation which found to be problematic; such as time-consuming, slipped requirements and complicated processes. The main aim of this paper is to study and review the adoption of Agile Software Methodology and Team Software Process (TSPi) practices in the undergraduate course focus on software development. The framework and course plan will be designed to apply and observe the implementation. Furthermore, this study will help to gather the teams’ viewpoint regarding the importance of Agile and TSPi practices in handling small projects with real clients.
 
 

Agile methods tailoring – A systematic literature review

Background: The software development industry has been adopting agile methods instead of traditional software development methods because they are more flexible and can bring benefits such as handling requirements changes, productivity gains and business alignment. Objective: This study seeks to evaluate, synthesize, and present aspects of research on agile methods tailoring including the method tailoring approaches adopted and the criteria used for agile practice selection. Method: The method adopted was a Systematic Literature Review (SLR) on studies published from 2002 to 2014. Results: 56 out of 783 papers have been identified as describing agile method tailoring approaches. These studies have been identified as case studies regarding the empirical research, as solution proposals regarding the research type, and as evaluation studies regarding the research validation type. Most of the papers used method engineering to implement tailoring and were not specific to any agile method on their scope. Conclusion: Most of agile methods tailoring research papers proposed or improved a technique, were implemented as case studies analyzing one case in details and validated their findings using evaluation. Method engineering was the base for tailoring, the approaches are independent of agile method and the main criteria used are internal environment and objectives variables.

Moving from Traditional to Agile Software Development Methodologies Also on Large, Distributed Projects.

Abstract The challenge that all companies face in a quickly changing business environment is to stay competitive in order to retain and if possible expand their market share. Traditional software development methods are inflexible and fail to respond on aggressive customer requests. In contrast, agile software methodologies provide a set of practices that allow for quick adaptations matching the modern product development needs. Although the value of the agile methodologies is well proven for small, collocated teams, the research question that this work is addressing refers to the benefits of the agile methodologies on large, distributed projects. With this paper, evidence is provided by the analysis of a case study that agile software development methodologies perform better than traditional methodologies also in large, distributed projects. Improvements are observed on the quality and on the customer perception of the end product, while agile methodologies allow for requirement changes even late in the project. At the same time, building better communication and collaboration in the team as an outcome of following the agile practices, results to enhanced relations between team members and to improved employee satisfaction metrics.

Empirical Validation of Neural Network Models for Agile Software Effort Estimation based on Story Points

Abstract Now-a-days agile software development process has become famous in industries and substituting the traditional methods of software development. However, an accurate estimation of effort in this paradigm still remains a dispute in industries. Hence, the industry must be able to estimate the effort necessary for software development using agile methodology efficiently. For this, different techniques like expert opinion, analogy, disaggregation etc. are adopted by researchers and practitioners. But no proper mathematical model exists for this. The existing techniques are ad-hoc and are thus prone to be incorrect. One popular approach of calculating effort of agile projects mathematically is the Story Point Approach (SPA). In this study, an effort has been made to enhance the prediction accuracy of agile software effort estimation process using SPA. For doing this, different types of neural networks (General Regression Neural Network (GRNN), Probabilistic Neural Network (PNN), Group Method of Data Handling (GMDH) Polynomial Neural Network and Cascade-Correlation Neural Network) are used. Finally performance of the models generated using various neural networks are compared and analyzed.

A Review of Requirement Engineering Issues and Challenges in Various Software Development Methods

Requirement Engineering (RE) is a systemic and integrated process of eliciting, elaborating, negotiating, prioritizing, specifying, validating and managing the requirements of a system. The detailed and agreed requirements are documented and specified to serve as the basis for further system development activities. The software industry has moved from traditional software development method to service oriented software development. While many researchers and practitioners have observed issues and challenges in Requirement Engineering phase specific to a software method, very little attention has been given to investigate diversity of issues and challenges of RE in different software development methods under one umbrella. This paper tries to review significant issues and challenges of RE from traditional software development method to recent service oriented software development method. The study unveils that there is a wide scope for developing new approaches and techniques in requirement engineering to resolve problems observed in various SE methods. The review discussion reveals the need of standardization and automation of RE process especially for Service oriented software development. KeywordsEngineering, RE phase, SE methods, traditional software development, service oriented software development, automation of RE

An Automatic Code Generation Framework for Service Dynamic Binding

Service-oriented computing is a novel computing paradigm that utilizes simple small-scale services as fundamental elements to orchestrate applications that are complex large-scale services, while traditional software development methods and running environment are insufficient to support the challenges required by dynamic services binding and service reuse. We concentrate on service-oriented programming, and propose a mutable pragmatic and effective automated code generation framework for service dynamic binding. Service-oriented applications are developed in a unified and coordinated way, and the additional codes are generated automatically to invoke diverse services developed by distinct technologies. Service dynamic binding is achieved by filtering from a set of candidate services through the execution engine.