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Traditional portfolio management tools and methods are challenging for software companies that use agile and lean approaches, because of the complex pre-planning activities required. In this paper, traditional portfolio management tools and methods that have been conventionally used in industry and presented in literature are reviewed. Findings concerning their use in agile and lean software companies are investigated, on the basis of the literature review and semi-structured interviews conducted in 7 agile and lean software companies in Finland. The findings indicate that the studied companies do not use traditional portfolio management tools and methods in their entirety. The software companies adapted suitable components from traditional portfolio management tools and methods into their practices. They also apply new tools and methods to manage their portfolios of offerings, to cope with the dynamics required by agile and lean methods. The companies' emphasis is on using tools to facilitate immediate feedback from customers, to assess the value of offerings in their portfolio. The results showed a growing interest in using Kanban at the portfolio level to provide a visual overview of offerings. [ABSTRACT FROM AUTHOR]

Scrum is a simple process to understand, but hard to adopt. Therefore, there is a need for resources to assist on its adoption. In this paper, we present the process followed to build a Bayesian network to assist on the assessment of the quality of the software process in the context of Scrum projects. The model provides data to help Scrum Masters lead the improvement of business value delivery of Scrum teams. The process is divided into 2 phases. In the first phase, we built the Bayesian network based on expert knowledge extracted from the literature and experts. We used a top-down approach and reasoning to define the key metrics necessary to build the models and their relationships. In the second phase, we updated the Bayesian network based on limitations of the first version. We validated the Bayesian network inferences with 10 simulated scenarios. Comparing both versions, for all scenarios, we improved the accuracy of the inferences. Therefore, we concluded that the Bayesian networks adequately represent Scrum projects from the viewpoint of the Scrum Master. Finally, the model built is in conformance with agile methods tailoring and can be adapted to any Scrum team. [ABSTRACT FROM AUTHOR]

Regression testing repeatedly executes test cases of previous builds to validate that the original features are not affected with any new changes. In recent years, regression testing has seen a remarkable progress with the increasing popularity of agile methods, which stress the central role of regression testing in maintaining software quality. The optimum case for regression testing in agile context is to run regression set at the end of each sprint and release, which requires a lot of cost and time. In this paper, we present an automated agile regression testing approach on both the sprints and release levels. The proposed approach addresses both weighted sprint test cases prioritization technique, which prioritizes test cases based on several parameters having real practical weight for testers, and Cluster-based Release Test cases Selection technique that clusters user stories based on the similarity of covered modules to solve the scalability issue. Test cases are then selected based on issues logged for failed test cases using text mining techniques. The proposed approach achieves enhancement for both the prioritization and selection of test cases for agile regression testing. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]