Risk Mitigation Techniques in Agile Development Processes

The main purpose of agile development methods is to reduce risks leading to a more successful and effective information system. In fact, analysing priorities, finding and identifying risks are important activities in all development approaches, including Agile development. However, some studies seek to assess risk management based on agile global software development (GSD) and provide mitigation measures to address specific risks. The risk mitigation technique for good development for sustainable development is expected to be designed to achieve time efficiency improvements to obtain greater resources at lower cost and thereby gain and maintain a competitive advantage

Risk Mitigation Techniques in Agile Development Processes

The main purpose of agile development methods is to reduce risks leading to a more successful and effective information system. In fact, analysing priorities, finding and identifying risks are important activities in all development approaches, including Agile development. However, some studies seek to assess risk management based on agile global software development (GSD) and provide mitigation measures to address specific risks. The risk mitigation technique for good development for sustainable development is expected to be designed to achieve time efficiency improvements to obtain greater resources at lower cost and thereby gain and maintain a competitive advantage

Requirement Prioritization Decision Factors for Agile Development Environments

In an agile development environment, project planners continuously prioritize work tasks so requirements that provide the most value are delivered first. This strategy is based on Value Based Software Engineering principles that different requirements deliver different levels of value and diverse stakeholders view the importance of the value of various requirements differently and thus, will prioritize them differently. However, we found that there are several core values that stakeholders have more agreement in terms of relevancy and importance than others. By knowing these core values, project planners have increased insights as to which requirements should be prioritized higher, hence, hopefully increasing overall stakeholder satisfaction and reducing project risk

Enhancing Requirements Change Request Categorization and Prioritization in Agile Software Development Using Analytic Hierarchy Process (AHP)

Software development now relies heavily on agile methods, which call for the efficient administration and prioritization of change requests. In order to improve requirement prioritization using the Analytic Hierarchy Process (AHP) in Agile methods, this study article presents a new framework for classifying software requirements into Small Change Requests (SCRs) and Large Change Requests (LCRs). The paper examines the difficulties associated with requirement prioritization and categorization in Agile settings and offers a methodical system for dividing change requests into categories based on complexity, impact, and timeline. In order to provide a thorough grasp of the project scope and objectives, the framework considers both functional and non-functional needs. A case study containing several Agile software development projects is used to evaluate the performance of the suggested categorization and prioritization model. According to the findings, the combination of SCR and LCR categorization with AHP enables more effective teamwork and greater matching of development goals with partner objectives. The research also shows that the suggested framework's integration into the Agile development process results in a more efficient decision-making process, less time wasted on talks, and improved resource distribution. The model aids in risk mitigation by allowing a methodical and quantifiable approach to requirement prioritization. These risks are related to quick changes in project scope and changing client requirements. By presenting a fresh framework for requirement categorization and prioritization, this study adds to the current discussion on successful requirement management in Agile methods. Agile software development projects become more effective and adaptable overall thanks to the incorporation of AHP, which guarantees a more methodical and objective prioritization process. This study has the potential to greatly improve the administration of shifting needs and user expectations in Agile settings by offering a structured method to classify and rank change requests

Developing a Risk Management Framework in Construction Project Based on Agile Management Approach

Construction projects in nature, carry a lot of risks, and unpredictable conditions. Thus, flexible management is required for the purpose of efficient responding to the various changes appear during their implementation. As an attempt to deal with risk in the construction project, this research aims at proposing a risk management framework in construction projects that built based on Agile management concept, which is a sequence of procedure deals with the project’ primary vision to its final delivery. The risk management framework will trace alignment and discover a contact between Agile and traditional project management concepts and find contact points among two of the more used Agile frameworks (Scrum) and one of the more confirmed project management framework (PMBOK®) processes. This will result in a recognition of comparable areas between Scrum and PMBOK® processes. The goal of the framework is to assist the project managers to adapt a more flexible approach to managing and implementing the construction project. The results proved that Agile management process from the create prioritized project backlog, sprint planning, sprint review, to sprint retrospective procedures and less time of the cycle, eliminate or mitigate many risks that lead to project challenges and failure

Reinforcement Learning for Automatic Test Case Prioritization and Selection in Continuous Integration

Testing in Continuous Integration (CI) involves test case prioritization, selection, and execution at each cycle. Selecting the most promising test cases to detect bugs is hard if there are uncertainties on the impact of committed code changes or, if traceability links between code and tests are not available. This paper introduces Retecs, a new method for automatically learning test case selection and prioritization in CI with the goal to minimize the round-trip time between code commits and developer feedback on failed test cases. The Retecs method uses reinforcement learning to select and prioritize test cases according to their duration, previous last execution and failure history. In a constantly changing environment, where new test cases are created and obsolete test cases are deleted, the Retecs method learns to prioritize error-prone test cases higher under guidance of a reward function and by observing previous CI cycles. By applying Retecs on data extracted from three industrial case studies, we show for the first time that reinforcement learning enables fruitful automatic adaptive test case selection and prioritization in CI and regression testing.Comment: Spieker, H., Gotlieb, A., Marijan, D., & Mossige, M. (2017). Reinforcement Learning for Automatic Test Case Prioritization and Selection in Continuous Integration. In Proceedings of 26th International Symposium on Software Testing and Analysis (ISSTA'17) (pp. 12--22). AC

The Methods of Selection of the Project Management Methodology

The problem of selecting the methodology to manage the company's projects or a specific project is reviewed. The authors suggest the methods to select methodology that are designated for application under the conditions of different degrees of awareness of the decision-maker about the existing methodologies, their advantages and weaknesses, about the range of efficient use. As the methods are more precise, so they require a more laborious analysis of the project and its environment. It is proposed to make the most substantiated choice resulting from solution of the task on optimizing the project's scope to the following criteria: profit, time, cost, quality, risk, and in terms of the company's maturity growth

Who are Metrics Team’s Stakeholders and What Do They Expect? Conducting Stakeholder Mapping with Focus on Communication in Agile Software Development Organization

As an increasing number of organizations create metrics teams, conducting stakeholder mapping is pivotal for identifying and analyzing metrics stakeholders’ expectations for reducing the risks of miscommunication and project failure. Further, though team-stakeholder communication is essential for successful collaboration, few studies focus on it in software measurement context. This case study seeks to identify and analyze metrics team’s stakeholders, with a special focus on communication challenges in team-stakeholder contacts. Inspired by Bryson\u27s Basic Stakeholder Analysis Techniques and Mitchell, Agle, and Wood\u27s theoretical model for stakeholder identification, a stakeholder mapping exercise was conducted using interactive workshops and follow-up interviews with 16 metrics team members and their stakeholders. The results illustrate the complexity of identifying stakeholders in agile organizations, the importance of developing a metrics culture, and enhancing transparency in team-stakeholder communication. The study aims to contribute to the development of stakeholder theory and offers insights into communication in software engineering context

Prioritizing Critical Success Factors of Requirements Engineering using Analytical Hierarchy Process

Requirements engineering is not as straightforward as asking stakeholders what they want the information systems to do. In most cases, their vision tends to be limited by the status quo. Eliciting a complete set of requirements that fulfil every gap and withstand scrutiny during validation is challenging. Hence, it is important to consider various factors influencing the success of requirements engineering. This paper identifies and prioritizes multiple critical success factors of requirements engineering using the Analytical Hierarchy Process. The initial model was developed from literature review and validated using evidence from an empirical study. Quantitative data was collected through a questionnaire and then analyzed to rank the success criteria and critical success factors. The results show that the user satisfaction is the most important success criterion, while the clear definition of project scopes and goals is the most critical factor for the success of requirements engineering

A Bayesian Approach for Software Release Planning under Uncertainty

Release planning — deciding what features to implement in upcoming releases of a software system— is a critical activity in iterative software development.Many release planning methods exist but most ignore the inevitable uncertainty of future development effort and business value. The thesis investigates how to analyse uncertainty during release planning and whether analysing uncertainty leads to better decisions than if uncertainty is ignored. The thesis’s first contribution is a novel release planning method designed to analyse uncertainty in the context of the Incremental Funding Method, an incremental cost-value based approach to software development. Our method uses triangular distributions, Monte-Carlo simulation and multi-objective optimisation to shortlist release plans that maximise expected net present value and minimise investment cost and risk. The second contribution is a new release planning method, called BEARS, designed to analyse uncertainty in the context of fixed-date release processes.Fixed-date release processes are more common in industry than fixed-scope release processes. BEARS models uncertainty about feature development time and economic value using lognormal distributions. It then uses Monte-Carlo simulation and search-based multi-objective optimisation to shortlist release plans that maximise expected net present value and expected punctuality. The method helps release planners explore possible tradeoffs between these two objectives. The thesis’ third contribution is an experiment to study whether analysing uncertainty using BEARS leads to shortlisting better release plans than if uncertainty is ignored, or if uncertainty is analysed assuming fixed-scope releases. The experiment compares 5 different release planning models on 32 release planning problems.The results show that analysing uncertainty using BEARS leads to shortlisting release plans with higher expected net present value and higher expected punctuality than methods that ignore uncertainty or that assume fixed-scope releases.Our experiment therefore shows that analysing uncertainty can lead to better release planning decisions than if uncertainty is ignored