Advertisement

Identifying the Reusable Components from Component-Based System: Proposed Metrics and Model

  • Neelamadhab Padhy
  • Rasmita Panigrahi
  • Suresh Chandra Satapathy
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 863)

Abstract

Reusability is the key component from the software development prospective. This job describes a measurement which is popularly called as reprocess measurement to discover and investigate the static activities of the module. This paper proposed a set of reusability metrics especially partly adaptable, completely changeable and moderately capable modules. The process of reusability can be measured to degree of module in component-based system. This paper provides the novel model as well as the proposed metrics. We propose reusability-metric for all categories of components including partially modifiable, fully modifiable as well as for off-the-shelf components. Using reusability-metric, we draw a reusability-matrix containing the reusability ratios of all the different classes of components. This paper introduces selection criteria for components by using the reusability features of component-based software.

Keywords

CBS (Component-Based System) Reusability Reusability-matrix 

References

  1. 1.
    Diamantopoulos, K., Thomopoulos, Symeonidis, A.: QualBoa: reusability-aware recommendations of source code components. In: IEEE/ACM 13th Working Conference on Mining Software Repositories (MSR) Austin, TX, pp. 488–491 (2016)Google Scholar
  2. 2.
    Hinkel, G., Kramer, M., Burger, E., Strittmatter, M., Happe, L.: An empirical study on the perception of metamodel quality. In: Proceedings of the 4th International Conference on Model-Driven Engineering and Software Development (MODELSWARD). IEEE, Rome, Italy, 16990400 (2016). Electronic ISBN: 978-989-758-2Google Scholar
  3. 3.
    Hudaib, A., Huneiti, I.: Othman: software reusability classification and predication using self- organizing map (SOM). Commun. Netw. 8, 179–192 (2016). http://dx.doi.org/10.4236/cn.2016.83018
  4. 4.
    Irshad, M., Petersen, K., Poulding, S.: A systematic literature review of software requirements reuse approaches. Int. Softw. Technol. (2018)Google Scholar
  5. 5.
    Sarro, F., Ferrucci, F., Harman, M., Manna, A., Ren, J.: Adaptive multi-objective evolutionary algorithms for overtime planning in software projects. IEEE Trans. Softw. Eng. 43(10), 898–917 (2017).  https://doi.org/10.1109/TSE.2017.2650914CrossRefGoogle Scholar
  6. 6.
    Al Dallal, J., Abdin, A.: Empirical evaluation of the impact of object-oriented code refactoring on quality attributes: a systematic literature review. IEEE Trans. Softw. Eng. 44(1), 44–69 (2018)Google Scholar
  7. 7.
    Singh, A.P., Tomar, P.: Estimation of component reusability through reusability metrics. World Academy of Science, Engineering and Technology. Int. J. Comput. Inf. Eng. 8(11) (2014)Google Scholar
  8. 8.
    Padhy, N., Singh, R.P., Satapathy, S.C.: Complexity estimation by using Multiparadigm approach: a proposed metrics and algorithms. International Journal of Networking and Virtual Organisations, Vol. X, No. Y, Inderscience, Switzerland (Press) (2018)Google Scholar
  9. 9.
    Padhy, N., Singh, R.P., Satapathy, S.C.: Estimation of complexity by using an object oriented metrics approach and its proposed algorithm and models. Int. J. Netw. Virtual (Press) (2018)Google Scholar
  10. 10.
    Padhy, N., Satapathy, S., Singh, R.P.: State-of-the-art object-oriented metrics and its reusability: a decade review. In: Satapathy, S., Bhateja, V., Das, S. (eds.) Smart Computing and Informatics. Smart Innovation, Systems and Technologies, vol. 77, pp. 431–441. Springer, Singapore (2018).  https://doi.org/10.1007/978-981-10-5544-7_42
  11. 11.
    Padhy, N., Panigrahi, R., Baboo, S.: A systematic literature review of an object oriented metric: reusability. In: 2015 International Conference on Computational Intelligence and Networks, pp. 190–191, Bhubaneswar (2015)Google Scholar
  12. 12.
    Padhy, N., Singh, R.P., Satapathy, S.C.: Cluster Computing, “Cost-Effective and Fault-Resilient Reusability Prediction Model by Using Adaptive Genetic Algorithm Based Neural Network for Web-of- Service Applications”. Springer US (2018). Print ISSN 1386-7857, Online ISSN 1573-7543,  https://doi.org/10.1007/s10586-018-2359-9
  13. 13.
    Padhy, N., Singh, R.P., Satapathy, S.C.: Software reusability metrics estimation: Algorithms, models and optimization techniques. Elsevier, Comput. Electr. Eng. vol. 69, pp. 653–668. (2017)Google Scholar
  14. 14.
    Padhy, N., Singh, R.P., Satapathy, S.C.: Utility of an object-oriented metrics component: Examining the feasibility of .Net and C# object-oriented program from the perspective of mobile learning. Int. J. Mobile Learn. Organ. (IJMLO) (2018). 10011924 Issue: 3, 263–279. Inderscience Publishers (IEL).  https://doi.org/10.1504/ijmlo.2018
  15. 15.
    Padhy, N., Singh, R.P., Satapathy, S.C.: Cluster Computing, “Enhanced evolutionary computing based artificial intelligence model for web-solutions software reusability estimation”. Online ISSN 1573-7543, Springer, Cluster Comput. (2017).  https://doi.org/10.1007/s10586-017-1558-0
  16. 16.
    Padhy, N., Singh, R.P., Satapathy, S.C.: Utility of an object-oriented metrics component: Examining the feasibility of .Net and C# object-oriented program from the perspective of mobile learning. Int. J. Mobile Learn. Organ. vol.12, issue: 3 (2018).  https://doi.org/10.1504/IJMLO.2018.092777

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Neelamadhab Padhy
    • 1
  • Rasmita Panigrahi
    • 1
  • Suresh Chandra Satapathy
    • 2
  1. 1.Rasmita Panigrahi Gandhi Institute of Engineering and Technology, GIET (Autonomous)GunupurIndia
  2. 2.Kalinga Institute of Industrial TechnologyBhubaneswarIndia

Personalised recommendations