Abstract
The Next Release Problem consists in selecting which requirements will be implemented in the next software release. For many SBSE approaches to the NRP, there is still a lack of ability to efficiently include the human opinion and its peculiarities in the search process. Most of these difficulties are due to the problem of the human fatigue. Thus, it is proposed the use of a machine learning technique to model the user and replace him in an Interactive Genetic Algorithm to the NRP. Intermediate results are able to show that an IGA can succesfully incorporate the user preferences in the final solution.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Bagnall, A.J., Rayward-Smith, V.J., Whittley, I.M.: The next release problem. Information and Software Technology 43(14), 883–890 (2001)
Harman, M., Mansouri, S.A., Zhang, Y.: Search based software engineering: A comprehensive analysis and review of trends techniques and applications. Department of CS, Kings College London, Tech. Rep. TR-09-03 (2009)
Harman, M., McMinn, P., de Souza, J.T., Yoo, S.: Search based software engineering: Techniques, taxonomy, tutorial. In: Meyer, B., Nordio, M. (eds.) LASER Summer School 2008-2010. LNCS, vol. 7007, pp. 1–59. Springer, Heidelberg (2012)
Harman, M.: Search based software engineering for program comprehension. In: 15th IEEE International Conference on Program Comprehension, ICPC 2007, pp. 3–13. IEEE (2007)
Takagi, H.: Interactive evolutionary computation: Fusion of the capabilities of ec optimization and human evaluation. Proceedings of the IEEE 89(9), 1275–1296 (2001)
Tonella, P., Susi, A., Palma, F.: Using interactive ga for requirements prioritization. In: 2010 Second International Symposium on Search Based Software Engineering (SSBSE), pp. 57–66. IEEE (2010)
Simons, C.L., Parmee, I.C., Gwynllyw, R.: Interactive, evolutionary search in upstream object-oriented class design. IEEE Transactions on Software Engineering 36(6), 798–816 (2010)
Baker, P., Harman, M., Steinhofel, K., Skaliotis, A.: Search based approaches to component selection and prioritization for the next release problem. In: 22nd IEEE International Conference on Software Maintenance, ICSM 2006, pp. 176–185. IEEE (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Araújo, A.A., Paixão, M. (2014). Machine Learning for User Modeling in an Interactive Genetic Algorithm for the Next Release Problem. In: Le Goues, C., Yoo, S. (eds) Search-Based Software Engineering. SSBSE 2014. Lecture Notes in Computer Science, vol 8636. Springer, Cham. https://doi.org/10.1007/978-3-319-09940-8_17
Download citation
DOI: https://doi.org/10.1007/978-3-319-09940-8_17
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09939-2
Online ISBN: 978-3-319-09940-8
eBook Packages: Computer ScienceComputer Science (R0)