A case study on value-based requirements tracing
Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering
Trade-off Analysis in Web Development
3-WoSQ Proceedings of the third workshop on Software quality
Hybrid Intelligence in Software Release Planning
International Journal of Hybrid Intelligent Systems
Software project management with GAs
Information Sciences: an International Journal
OUTLINING A MODEL OF A RELEASE MANAGEMENT PROCESS
Journal of Integrated Design & Process Science
A controlled empirical evaluation of a requirements abstraction model
Information and Software Technology
Analysis & recommendations for the management of cots: computer off the shelf-software projects
ICCOMP'07 Proceedings of the 11th WSEAS International Conference on Computers
A product management challenge: Creating software product value through requirements selection
Journal of Systems Architecture: the EUROMICRO Journal
Software release planning with time-dependent value functions and flexible release dates
SEA '07 Proceedings of the 11th IASTED International Conference on Software Engineering and Applications
A systematic review on strategic release planning models
Information and Software Technology
REV '09 Proceedings of the 2009 Fourth International Workshop on Requirements Engineering Visualization
A study of the bi-objective next release problem
Empirical Software Engineering
Search based software engineering: techniques, taxonomy, tutorial
Empirical Software Engineering and Verification
Search-based software engineering: Trends, techniques and applications
ACM Computing Surveys (CSUR)
Exact scalable sensitivity analysis for the next release problem
ACM Transactions on Software Engineering and Methodology (TOSEM)
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Delivering software in an incremental fashionimplicitly reduces many of the risks associatedwith delivering large software projects. However,adopting a process, where requirements aredelivered in releases means decisions have to bemade on which requirements should be deliveredin which release. This paper describes a methodcalled EVOLVE+, based on a genetic algorithmand aimed at the evolutionary planning ofincremental software development. The method isinitially evaluated using a sample project. Theevaluation involves an investigation of the trade-offrelationship between risk and the overallbenefit. The link to empirical research is two-fold:Firstly, our model is based on interaction withindustry and randomly generated data for effortand risk of requirements. The results achieved thisway are the first step for a more comprehensiveevaluation using real-world data. Secondly, we tryto approach uncertainty of data by additionalcomputational effort providing more insight intothe problem solutions: (i) Effort estimates areconsidered to be stochastic variables following agiven probability function; (ii) Instead of offeringjust one solution, the L-best (L1) solutions aredetermined. This provides support in finding themost appropriate solution, reflecting implicitpreferences and constraints of the actual decision-maker.Stability intervals are given to indicate thevalidity of solutions and to allow the problemparameters to be changed without adverselyaffecting the optimality of the solution.