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Machine Learning for User Modeling in an Interactive Genetic Algorithm for the Next Release Problem

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Search-Based Software Engineering (SSBSE 2014)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 8636))

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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.

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References

  1. Bagnall, A.J., Rayward-Smith, V.J., Whittley, I.M.: The next release problem. Information and Software Technology 43(14), 883–890 (2001)

    Article  Google Scholar 

  2. 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)

    Google Scholar 

  3. 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)

    Google Scholar 

  4. Harman, M.: Search based software engineering for program comprehension. In: 15th IEEE International Conference on Program Comprehension, ICPC 2007, pp. 3–13. IEEE (2007)

    Google Scholar 

  5. Takagi, H.: Interactive evolutionary computation: Fusion of the capabilities of ec optimization and human evaluation. Proceedings of the IEEE 89(9), 1275–1296 (2001)

    Article  Google Scholar 

  6. 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)

    Google Scholar 

  7. 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)

    Article  Google Scholar 

  8. 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)

    Google Scholar 

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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

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  • 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)

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