Skip to main content
SpringerLink
Log in

An Efficient Approach for Evolution of Functional Requirements to Improve the Quality of Software Architecture

  • Conference paper
  • First Online:
Artificial Intelligence and Evolutionary Computations in Engineering Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 394))

Abstract

Software architecture will be designed within the early phases combined with the development process; the huge constraints makes it possible for the achievement of certain functional requirements, quality attributes (non-functional requirements), and also business goals. Metaheuristic search algorithm performs an important role within the software architecture design to improve the performance of obtaining an optimal solution from the huge search space. This particular paper mainly focusses on balancing the combinations of “Adaptive Genetic algorithm,” which has to be applied. It has incorporated the usage of roulette wheel selection operators; this technique is implemented in java and it also finds out global minima as well as time reduction when compared with Genetic algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Pan W. Applying complex network theory to software structure analysis. World Acad Sci Eng Technol. 2011;60:1636–42.

    Google Scholar 

  2. Abdelmoez M, Jalali AH, Shaik K, Menzies T, Ammar HH. Using software architecture risk assessment for product line architectures. In: Proceedings of. international conference on communication, computer and power (Icccp’09); 2009. Muscat, Feb 15–18, 2009.

    Google Scholar 

  3. Yang XS, Deb S. Engineering optimization by cuckoo search. Int J Math Model Num Optim. 2010;1(4):330–43.

    MATH  Google Scholar 

  4. Frey S, Fittkau F, Hasselbring W. Search-based genetic optimization for deployment and reconfiguration of software in the cloud. In: 2013 35th international conference on software engineering (ICSE); 2013, 18–26 May 2013.

    Google Scholar 

  5. Zitzler E, Deb K, Thiele L. Comparison of multiobjective evolutionary algorithms: empirical results. Evol Comput. 2000;8(2):125–48.

    Article  Google Scholar 

  6. Rela L. Evolutionary computing in search-based software engineering, Lappeenranta University of Technology, Department of Information Technology, M.Sc. Thesis; 2004.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of CSE, Sree Vidyanikethan Engineering College, Tirupati, India

    M. Sunil Kumar

  2. Department of CSE, S.V.U. College of Engineering, SV University, Tirupati, India

    A. Rama Mohan Reddy

Authors
  1. M. Sunil Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. Rama Mohan Reddy
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. Sunil Kumar .

Editor information

Editors and Affiliations

  1. Electrical and Electronics Engineer, SRM Engineering College, Kattankulathur, Tamil Nadu, India

    Subhransu Sekhar Dash

  2. Electrical & Electronics Engineering, Velammal Engineering College, Chennai, Tamil Nadu, India

    M. Arun Bhaskar

  3. Dept Electrical & Electronics Engg, IIT Delhi, New Delhi, India

    Bijaya Ketan Panigrahi

  4. Indian Statistical Institute, Kolkata, India

    Swagatam Das

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer India

About this paper

Cite this paper

Sunil Kumar, M., Rama Mohan Reddy, A. (2016). An Efficient Approach for Evolution of Functional Requirements to Improve the Quality of Software Architecture. In: Dash, S., Bhaskar, M., Panigrahi, B., Das, S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 394. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2656-7_71

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-2656-7_71

  • Published:

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2654-3

  • Online ISBN: 978-81-322-2656-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation