Knapsack problems: algorithms and computer implementations
Knapsack problems: algorithms and computer implementations
Managing software requirements: a unified approach
Managing software requirements: a unified approach
Agile Software Development with Scrum
Agile Software Development with Scrum
A Cost-Value Approach for Prioritizing Requirements
IEEE Software
Optimizing Value and Cost in Requirements Analysis
IEEE Software
Parallel Machine Scheduling by Column Generation
Operations Research
HICSS '01 Proceedings of the 34th Annual Hawaii International Conference on System Sciences ( HICSS-34)-Volume 8 - Volume 8
Invented requirements and imagined customers: requirements engineering for off-the-shelf software
RE '95 Proceedings of the Second IEEE International Symposium on Requirements Engineering
An Industrial Survey of Requirements Interdependencies in Software Product Release Plannin
RE '01 Proceedings of the Fifth IEEE International Symposium on Requirements Engineering
An Analytical Model for Requirements Selection Quality Evaluation in Product Software Development
RE '03 Proceedings of the 11th IEEE International Conference on Requirements Engineering
RE '04 Proceedings of the Requirements Engineering Conference, 12th IEEE International
The Art and Science of Software Release Planning
IEEE Software
Towards a Reference Framework for Software Product Management
RE '06 Proceedings of the 14th IEEE International Requirements Engineering Conference
Minimizing the number of late jobs in a stochastic setting using a chance constraint
Journal of Scheduling
Integrated requirement selection and scheduling for the release planning of a software product
REFSQ'07 Proceedings of the 13th international working conference on Requirements engineering: foundation for software quality
Optimized staffing for product releases and its application at Chartwell Technology
Journal of Software Maintenance and Evolution: Research and Practice - Search Based Software Engineering [SBSE]
The How? When? and What? for the Process of Re-planning for Product Releases
ICSP '09 Proceedings of the International Conference on Software Process: Trustworthy Software Development Processes
Search based data sensitivity analysis applied to requirement engineering
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Does explanation improve the acceptance of decision support for product release planning?
ESEM '09 Proceedings of the 2009 3rd International Symposium on Empirical Software Engineering and Measurement
A systematic review on strategic release planning models
Information and Software Technology
Today/future importance analysis
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Application of re-estimation in re-planning of software product releases
ICSP'10 Proceedings of the 2010 international conference on New modeling concepts for today's software processes: software process
Proceedings of the 11th International Conference on Product Focused Software
Conceptual scheduling model and optimized release scheduling for agile environments
Information and Software Technology
Information and Software Technology
SRP-plugin: a strategic release planning plug-in for visual studio 2010
Proceedings of the 1st Workshop on Developing Tools as Plug-ins
A comparison of model-based and judgment-based release planning in incremental software projects
Proceedings of the 33rd International Conference on Software Engineering
Sensitivity analysis for weak constraint generation
MLDM'11 Proceedings of the 7th international conference on Machine learning and data mining in pattern recognition
A framework for validating task assignment in multiagent systems using requirements importance
PRIMA'10 Proceedings of the 13th international conference on Principles and Practice of Multi-Agent Systems
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We present a mathematical formalization of release planning with a corresponding optimization tool that supports product and project managers during release planning. The tool is based on integer linear programming and assumes that an optimal set of requirements is the set with maximal projected revenue against available resources. The input for the optimization is twofold. The first type of input data concerns the list of candidate requirements, estimated revenues, and resources needed. Second, managerial steering mechanisms enable what-if analysis in the optimization environment. Experiments based on real-life data made a sound case for the applicability of our approach.