Null function classification using NFR matrix and decision tree

  • Authors

    • Hedayatullah Hoshmand Chandigarh University
    • Sandeep Singh Kang Chandigarh University
    2018-06-23
    https://doi.org/10.14419/ijet.v7i3.12495
  • Classification, Null Function, Decision tree, NFR matrix

  • Abstract

    This research work is based on the classification of the functions which are required and which is not required for the efficient development of the software. The motivation of this work is to identify non required functions to reduce development cost and efforts. The classification is the technique which can classify data into certain number of classes. The NFR matrix is the existing technique which can classify the Null functions. To classify the null functions NFR use clustering method which can modify to increase accuracy of classification. In the existing method NFR matrix is used for the null function classification, it use the clustering for the classification. In this work, decision tree will based with the clustering. It take input result of clustering and generate classified result.

  • References

    1. [1] R. Veleda and L. M. Cysneiros, “An Initial Approach to ReuseNon-Functional Requirements Knowledge,†in Proceedings ofthe Eighth International i* Workshop (istar 2015), 2015, pp.25–30.

      [2] P. P. Sancho, C. Juiz, R. Puigjaner, L. Chung, and N.Subramanian, “An Approach to Ontology-aided PerformanceEngineering Through NFR Framework,†in Proceedings ofthe 6th International Workshop on Software andPerformance, 2007, pp. 125–128.

      [3] M. M. Hasan, P. Loucopoulos, and M. Nikolaidou,“Classification and Qualitative Analysis of Non-FunctionalRequirements Approaches,†Springer Berlin Heidelberg, 2014,pp. 348–362.

      [4] H. Hu, Q. Ma, T. Zhang, Y. Tan, H. Xiang, C. Fu, and Y.Feng, “Semantic modelling and automated reasoning of nonfunctionalrequirement conflicts in the context of softgoalinterdependencies,†IET Softw., vol. 9, no. 6, pp. 145–156,2015.

      [5] J. Eckhardt, A. Vogelsang, and D. M. Fernández, “Are "non-functional"requirements really non-functional?: An investigation of non-functionalrequirements in practice,†in Proc. ICSE, 2016, pp. 832–842.

      [6] L. Chung, B. A. Nixon, E. Yu, and J. Mylopoulos, Non-functionalrequirements in software engineering. Springer, 2012, vol. 5.

      [7] Cleland-Huang J, Heimdahl M, Huffman-Hayes J, Lutz R, Ma¨derP (2012) Trace queries for safety requirements in high assurancesystems. In: International conference on requirements engineering:foundation for software quality, pp 179–193

      [8] Mahmoud A (2015) An information theoretic approach forextracting and tracing non-functional requirements. In: Internationalrequirements engineering conference

      [9] Mihalcea R, Corley C, Strapparava C (2006) Corpus-based andknowledge-based measures of text semantic similarity. In:National conference on artificial intelligence, pp 775–78044.

      [10] Holzinger A, Yildirim P, Geier M, Simonic KM (2013) Qualitybasedknowledge discovery from medical text on the web. In:Pasi G, Bordogna G, Jain L (eds) Quality issues in the managementof web information. Springer, Berlin, pp 145–158

      [11] Huffman-Hayes J, Dekhtyar A, Sundaram S (2006) Advancingcandidate link generation for requirements tracing: the study ofmethods. IEEE Trans SoftwEng 32(1):4–19

      [12] Mahmoud A, Niu N (2015) On the role of semantics in automatedrequirements tracing. RequirEng 20(3):281–300

      [13] Lo D, Nagappan N, Zimmermann T (2015) How practitionersperceive the relevance of software engineering research. In: Jointmeeting on foundations of software engineering, pp 415–425

      [14] Arthur D, Vassilvitskii S (2007) K-means??: the advantages ofcareful seeding. In: Annual ACM-SIAM symposium on discretealgorithms, pp 1027–1035

      [15] Deißenbo¨ck F, Pizka M (2005) Concise and consistent naming.In: International workshop on program comprehension,pp 97–106

      [16] Bekkerman R, El-Yaniv R, Tishby N, Winter Y (2003) Distributionalword clusters vs. words for text categorization. J MachLearn Res 3:1183–1208

      [17] Deerwester S, Dumais S, Furnas G, Landauer T, Harshman R(1990) Indexing by latent semantic analysis. J Am SocInfSci41(6):391–407

      [18] Fatima Khalique, WasiHaider Butt, Shoab Ahmad Khan, “Creating Domain Non-Functional Requirements inSoftware Product Line Engineering using ModelTransformationsâ€, 2017 International Conference on Frontiers of Information Technology

      [19] Varun Gupta, Mohd. Talha Khan, Chetna Gupta, “Non-Functional Requirement PrioritizationApproach Based on Historical Similar Projectâ€, 2017, IEEE

      [20] Jovan Popović, NenadKorolija, ŽeljkoMarković, and Dragan Bojić, “The Influence of Non-functional Requirementsin UCP Method on the Accuracy of EffortEstimatesâ€, 2017, 25th Telecommunications forum TELFOR

      [21] Klérisson V. R. Paixão, Crícia Z. Felício, Fernanda M. Delfim and Marcelo de A. Maia, “On the Interplay between Non-FunctionalRequirements and Builds on Continuous Integrationâ€, 2017 IEEE/ACM 14th International Conference on Mining Software Repositories (MSR)

      [22] Rodrigo Veleda, Luiz MarcioCysneiros, “Towards a Tool to Help Exploring Existing Non-Functional Requirements Solution Patternsâ€, 2017 IEEE 25th International Requirements Engineering Conference Workshops

      [23] Niu N, Mahmoud A (2012) Enhancing candidate link generationfor requirements tracing: the cluster hypothesis revisited. In:IEEE international requirements engineering conference,pp 81–90

      [24] Hearst M, Pedersen J (1996) Reexamining the cluster hypothesis:scatter/gather on retrieval results. In: International ACM SIGIRconference on Research and development in information retrieval,pp 76–84

      [25] Anas Mahmoud, Grant Williams, “Detecting, classifying, and tracing non-functional softwarerequirementsâ€, Springer-Verlag London 2016

  • Downloads

  • How to Cite

    Hoshmand, H., & Singh Kang, S. (2018). Null function classification using NFR matrix and decision tree. International Journal of Engineering & Technology, 7(3), 1087-1090. https://doi.org/10.14419/ijet.v7i3.12495

    Received date: 2018-05-05

    Accepted date: 2018-05-07

    Published date: 2018-06-23