Knapsack problems: algorithms and computer implementations
Knapsack problems: algorithms and computer implementations
New directions on agile methods: a comparative analysis
Proceedings of the 25th International Conference on Software Engineering
Rescheduling Manufacturing Systems: A Framework of Strategies, Policies, and Methods
Journal of Scheduling
User Stories Applied: For Agile Software Development
User Stories Applied: For Agile Software Development
Supporting Software Release Planning Decisions for Evolving Systems
SEW '05 Proceedings of the 29th Annual IEEE/NASA on Software Engineering Workshop
Bi-objective release planning for evolving software systems
Proceedings of the the 6th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Empirical studies of agile software development: A systematic review
Information and Software Technology
Guidelines for conducting and reporting case study research in software engineering
Empirical Software Engineering
A systematic review on strategic release planning models
Information and Software Technology
An integrated approach for requirement selection and scheduling in software release planning
Requirements Engineering
Conceptual scheduling model and optimized release scheduling for agile environments
Information and Software Technology
Sprint planning optimization in agile data warehouse design
DaWaK'12 Proceedings of the 14th international conference on Data Warehousing and Knowledge Discovery
A Lagrangian heuristic for sprint planning in agile software development
Computers and Operations Research
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Most agile methods divide a project into sprints (iterations), and include a sprint planning phase that is critical to ensure the project success. Several factors impact on the optimality of a sprint plan, which makes the planning problem difficult. In this paper we formalize the planning problem and propose an optimization model that, given the estimates made by the project team and a set of development constraints, produces a multi-sprint optimal plan that maximizes the business value perceived by users. To cope with the inherent flexibility and uncertainty of agile projects, our approach ensures that a baseline plan can be revised and re-optimized during project execution without disrupting it, which we call smooth replanning. The planning problem is converted into a generalized assignment problem, given a linear programming formulation, and solved using the IBM ILOG CPLEX Optimizer. Our model is validated on both real and synthetic projects. In particular, a case study on two real projects confirms the effectiveness of our approach; as to efficiency, for medium-sized problems an exact solution is found in a few minutes, while for large problems a heuristic solution that is less than 1% far from the exact one is returned in a few seconds. Finally, some smooth replanning tests investigate the trade-off between plan quality and stability.