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Software systems evolve continuously and must be developed quickly to fit user requirements and new advances in technology. This has led the software engineering to propose several methods and approaches to overcome the development and maintenance of these software systems. In this regard, Agile Methodologies and Model-Driven Engineering (MDE) are two main approaches that have emerged in recent years and suggest a solution to some of the issues associated with Software systems developments. MDE focuses on software reuse through models and on generative approaches based on separation of concerns whereas Agile Methods promote the use of simpler models and best practices for programming to achieve quick feedback from clients within a development process. However, these two approaches have evolved separately and there are only a few works related to their combination. This paper presents a customized V development life cycle based on models which combines the two MDE variants: The MDA approach in the V left branch with the MBT approach to generate tests of the V right branch. In addition, we integrate this customized V life cycle in the agile Scrum methodology to facilitate the management of each Scrum sprint. [ABSTRACT FROM AUTHOR]

Flexible iterative development life cycle, adaptive nature and fast delivery has given Agile an upper edge as compared to all other software development frameworks. In the current industry scenario agile methods are gaining popularity, owing to its people centric approach, hence organizations are adopting agile development methodologies at a large scale. Agile projects work in self-organizing small collaborative teams. Team size varies according to the project requirement however, agile development focus on smaller team size. Supervised machine learning is applied in this study to provide optimum prediction model. All the available regression models in Matlab R2019b are used to predict number of team members required for an agile project. Iterations from five different open source projects are considered for this study. The results after training all the variants of each regression model, namely Linear Regression models, Support Vector Machine models, Tree models, Ensemble models and Gaussian Process Regression models are compared using Root Mean Square Error (RMSE) score and R-squared values. On the basis of evaluative and comprehensive analysis, the most significant model to predict manpower requirement for an agile project has been chosen. [ABSTRACT FROM AUTHOR]

Agile methodologies are increasingly considered important in the current context because of their focus on business benefit, strong stakeholder involvement and rapid incorporation of changing requirements. The Scrum methodology presents a generic and agile model for software development, but there are some gaps regarding solution architecture and requirements modeling and traceability. Fast customer feedback and support for volatile requirements result in higher product value, however, initial requirements modelling using modelling techniques are not commonly used in agile processes such as Scum to prepare the phase of Implementation of the software project. This article presents a first proposal for a visual environment to support the product / sprint backlog, helping to prioritize, track and decide on the most valuable, aligned and quickly deployable requirements. [ABSTRACT FROM AUTHOR]

Since the beginning of 2000, the software industry has turned a corner to adopting agile lightweight methods that are subject to change at a more efficient pace; in addition, risk management is generally not explicitly addressed in agile projects. So agile teams generally do not use an intentional risk management approach. Although agile methodologies tend to manage project risk implicitly, it is important to have an appropriate risk management mechanism in agile methodologies.Therefore, in this paper a framework for integrating risk management in the agile development projects is proposed while considering Scrum as an agile method and the PMBOK as a project risk management guide. The main goals of this framework are to improve the risk management mechanism in Scrum and to increase the Scrum project's success rate [ABSTRACT FROM AUTHOR]

Business processes represent an important core component of the company's activities and should be therefore more considerate. It takes a long time until the processes modeled down to the smallest detail, analyzed and designed. When these steps have been completed, often the process will not be adapted. Here would be an agile approach interesting to be flexible on trends and enterprise decisions which will have any dependencies to the processes. For this reason, the purpose of this study is to develop a holistic approach, in which the advantages of the previous models can be optimally used and the current challenges such as the desired agility can be included. The research methodology used in the investigation consists of a combination of methods and tools of Business Process Management (BPM) and agile management. The aim of the research is to evaluate whether these methods can contribute positively to the process modeling improvement in the framework of the Enterprise Information System. The finding of this research consists of a holistic model for acting agile within BPM. This allows companies to act flexible to adapt or implement enterprise processes. The resulting added value can be seen in the model for flexible implementation with regular controlling which are set apart from the previous rigid waterfall models. [ABSTRACT FROM AUTHOR]

• In this article, all 36 dimensional success factors are considered to estimate the required effort and cost to develop any Agile-Scrum based software project. • The work presented in the article computes the required time, effort and cost of projects mentioned in a data set on the basis of different inputs to the system. • For computation purposes, we divided the projects into three categories as Low, Medium and High level project for the unbiased estimation. • The datasets considered for computation purposes, also validated by experienced professionals from software industries. • It is found that the results obtained from the extended algorithm are cost-effective and less effort-oriented to a great extent as a compared to the existing algorithm. Effort and cost estimation is essential processes during software development. For agile methodologies as well, several approaches have been proposed so far to estimate the required effort and cost to develop any software system. Genuine assessment of software products is not an easy task as it requires the constant attention of the product owner. For effective estimation, we need to consider various success factors associated with all possible dimensions. In this article, we look at Scrum-based Agile projects that are developed over multiple sprints. We proposed an extension to the existing algorithm based on a total of 36 success factors; Which estimates the development effort and cost required to complete the project. For assessment and calculation, we have taken a data-set of a total of 30 projects categorized into three groups as low, medium, and high-level projects. This dataset is further validated by experienced professionals. We also compared our results with the existing approach and found that our results are cost-effective and require less effort even after considering more success factors. [ABSTRACT FROM AUTHOR]

The Agile methods favours more communication, continuous integration, rapid delivery of software modules, iterative and incremental approach, but at the same time Agile software development has limitations like lack of upfront planning, lack of sufficient documentation, lack of predictability, etc.. Sometimes these limitations and so many methods make Agile software development more stressful. This work is about finding the current limitations and advantages of Agile software development. For finding the actual limitations beyond the literature, an online survey was conducted with the specified sample size of Agile experienced professionals, then the ANOVA test is applied to satisfy the hypothesis. [ABSTRACT FROM AUTHOR]

Software process standards (e.g. ISO/IEC 12207, ISO/IEC 15504) and models (e.g. CMMI) provide a set of best practices and guidelines for improving the quality of the software process and products resulting from that process. However, they do not prescribe a particular software development methodology (i.e. RUP, MSF), and thus software development teams face a compliance problem between the selected development methodology and a pursued particular standard or model. In this research, the particular issue of compliance of Agile Software Development Methodologies (SCRUM, XP, and UPEDU) and the new ISO/IEC 29110 standard is studied. Because the new standard is focused on the software process in very small software development companies or small software project teams in the range from 1 to 25 people, and the Agile Software Development Methodologies (ASDMs) are primarily for same targets, this study is important. The ISO/IEC 29110 standard contains two processes: Project Management and Software Implementation. This study is focused on the first process. The main findings indicate that the UPEDU and SCRUM methodologies present and high compliance level with the ISO/IEC 29110 Project Management process, while XP has a moderate level. Thus, software developer teams interested in achieving compliance with the ISO/IEC 29110 Project Management process can count with two ASDMs. However, a full compliance study (with both Project Management and Software Implementation) is still missing. [ABSTRACT FROM AUTHOR]

Today's software development environment dictates speed, flexibility and a people-centered focus. Virtual teams represent a new organizational form that does not provide for same proximity collaboration. In this paper we propose a solution approach of a virtual team, as well as show some examples of using the Microsoft Visual Team Foundation Server 2013 tools to address these challenges. [ABSTRACT FROM AUTHOR]

Software project development is a dynamic process by nature, since it is common that events such as changes in the software requirements and in the development team occur during the execution of the original project plan. When such disruptive events occur, the project plan needs to be adjusted, and the activity of adjusting the original plan in order to comply with the date and costs constraints of the project is called project rescheduling. This situation is not exclusive to whole-project plan-driven approaches to software development, as it is also present when software projects are developed following agile methodologies such as Scrum. In Scrum, shorter period project plans, called release plans, are used and when disruptive events occur release plan rescheduling needs to be performed. Plan rescheduling can be modeled as a multi-objective optimization problem, however, there have been no studies that investigate the release plan rescheduling problem (RPRP) and its solution by means of multi-objective optimizers. The study presented in this paper intends to address the lack of studies of the release plan rescheduling problem and covers three fundamental topics. First, a model for the release plan rescheduling problem is proposed, which considers metrics that are particularly important to define a release plan, including story points and velocity. Second, three evolutionary multi-objective algorithms are utilized for solving a number of problem instances and an appropriate in-depth analysis of their solutions is provided. Finally, a careful examination of the solutions with respect to their practicability is performed. • Release plan rescheduling, in the context of agile software development, is modeled. • Five criteria are defined for the multi-objective optimization problem. • Three evolutionary multi-objective algorithms are applied to test instances. • Analysis of results include conflict between the objectives and algorithm performance. • Results are examined regarding the practicability of the rescheduled release plans. [ABSTRACT FROM AUTHOR]