Skip to main content
SpringerLink
Log in

Multi-label Classifier to Deal with Misclassification in Non-functional Requirements

  • Conference paper
  • First Online:
Trends and Innovations in Information Systems and Technologies (WorldCIST 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1159))

Included in the following conference series:

Abstract

Automatic classification of software requirements is an active research area; it can alleviate the tedious task of manual labeling and improves transparency in the requirements engineering process. Several attempts have been made towards the identification and classification by type of functional requirements (FRs) as well as non-functional requirements (NFRs). Previous work in this area suffers from misclassification. This study investigates issues with NFRs in particular the limitations of existing methods in the classification of NFRs. The goal of this work is to minimize misclassification and help stakeholders consider NFRs in early phases of development through automatically classifying requirements. In this study, we have proposed an improved requirement detection and classification technique. The following summarizes the proposed approach:

(a) A newly created labelled corpus,

(b) Textual semantics to augment user requirements by word2vec for automatically extracting features, and

(c) A convolution neural network-based multi-label requirement classifier that classifies NFRs into five classes: reliability, efficiency, portability, usability, and maintainability.

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

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

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

Similar content being viewed by others

References

  1. Ibrahim, N., Wan Kadir, W.M.N., Deris, S.: Documenting requirements specifications using natural language requirements boilerplates. In: 2014 8th Malaysian Software Engineering Conference (MySEC), Langkawi, Malaysia, pp. 19–24. IEEE (2014)

    Google Scholar 

  2. Khatter, K., Kalia, A.: Impact of non-functional requirements on requirements evolution. In: 2013 6th International Conference on Emerging Trends in Engineering and Technology, Nagpur, India, pp. 61–68. IEEE (2013)

    Google Scholar 

  3. Mijanur Rahman, Md., Ripon, S.: Elicitation and modeling non-functional requirements – a POS case study. Int. J. Future Comput. Commun. 485–489 (2013). https://doi.org/10.7763/IJFCC.2013.V2.211

  4. Hussain, A., Mkpojiogu, E.O.C., Kamal, F.M.: The role of requirements in the success or failure of software projects. Int. Rev. Manage. Mark. 6(7), 306–311 (2016)

    Google Scholar 

  5. Younas, M., Wakil, K.N.D., Arif, M., Mustafa, A.: An automated approach for identification of non-functional requirements using Word2Vec model. Int. J. Adv. Comput. Sci. Appl. 10 (2019). https://doi.org/10.14569/IJACSA.2019.0100871

  6. Glinz, M.: On non-functional requirements. In: 15th IEEE International Requirements Engineering Conference (RE 2007), Delhi, pp. 21–26. IEEE (2007)

    Google Scholar 

  7. Berntsson Svensson, R., Gorschek, T., Regnell, B.: Quality requirements in practice: an interview study in requirements engineering for embedded systems. In: Proceedings of the 15th International Working Conference on Requirements Engineering: Foundation for Software Quality. pp. 218–232. Springer, Heidelberg (2009)

    Google Scholar 

  8. Zhang, M.-L., Zhou, Z.-H.: A review on multi-label learning algorithms. IEEE Trans. Knowl. Data Eng. 26, 1819–1837 (2014). https://doi.org/10.1109/TKDE.2013.39

    Article  Google Scholar 

  9. Helmy, W., Kamel, A., Hegazy, O.: Requirements engineering methodology in agile. Environment 9, 8 (2012)

    Google Scholar 

  10. Khan, F., Jan, S.R., Tahir, M., Khan, S., Ullah, F.: Survey: dealing non-functional requirements at architecture level. VFAST Trans. Softw. Eng. 9, 7 (2016). https://doi.org/10.21015/vtse.v9i2.410

  11. Binkhonain, M., Zhao, L.: A review of machine learning algorithms for identification and classification of non-functional requirements. Expert Syst. Appl. X 1, 100001 (2019). https://doi.org/10.1016/j.eswax.2019.100001

    Article  Google Scholar 

  12. Gries, S.Th., Berez, A.L.: Linguistic annotation in/for corpus linguistics. In: Ide, N., Pustejovsky, J. (eds.) Handbook of Linguistic Annotation, pp. 379–409. Springer, Netherlands, Dordrecht (2017)

    Chapter  Google Scholar 

  13. Robinson, W.N.: Two rule-based natural language strategies for requirements discovery and classification in open source software development projects (2012). https://doi.org/10.2753/MIS0742-1222280402

  14. Sharma, V.S., Ramnani, R.R., Sengupta, S.: A framework for identifying and analyzing non- functional requirements from text (2014). https://doi.org/10.1145/2593861.2593862

    Article  Google Scholar 

  15. Slankas, J., Williams, L.: Automated extraction of non-functional requirements in available documentation. In: 2013 1st International Workshop on Natural Language Analysis in Software Engineering, NaturaLiSE 2013 – Proceedings, pp. 9–16 (2013). https://doi.org/10.1109/NAturaLiSE.2013.6611715

  16. Abad, Z.S.H., Karras, O., Ghazi, P., Glinz, M., Ruhe, G., Schneider, K.: What works better? A study of classifying requirements. In: 2017 IEEE 25th International Requirements Engineering Conference (RE), pp. Lisbon, Portugal. pp. 496–501. IEEE (2017)

    Google Scholar 

  17. Sunner, D., Bajaj, H.: Classification of functional and non-functional requirements in agile by cluster neuro-genetic approach. Int. J. Softw. Eng. Appl. 10, 129–138 (2016). https://doi.org/10.14257/ijseia.2016.10.10.13

    Article  Google Scholar 

  18. Casamayor, A., Godoy, D., Campo, M.: Identification of non-functional requirements in textual specifications: A semi-supervised learning approach. Inf. Softw. Technol. 52, 436–445 (2010). https://doi.org/10.1016/j.infsof.2009.10.010

    Article  Google Scholar 

  19. Hussain, I., Kosseim, L., Ormandjieva, O.: Using linguistic knowledge to classify non-functional requirements in SRS documents. In: Kapetanios, E., Sugumaran, V., Spiliopoulou, M. (eds.) Natural Language and Information Systems, pp. 287–298. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  20. Mahmoud, M.: Software requirements classification using natural language processing and SVD. Int. J. Comput. Appl. 164, 7–12 (2017). https://doi.org/10.5120/ijca2017913555

    Article  Google Scholar 

  21. Cleland-Huang, J., Settimi, R., Zou, X., Solc, P.: Automated classification of non-functional requirements. Requirements Eng. 12, 103–120 (2007). https://doi.org/10.1007/s00766-007-0045-1

    Article  Google Scholar 

  22. Tsai, C.-F.: Bag-of-words representation in image annotation: a review. ISRN Artif. Intell. 2012, 1–19 (2012). https://doi.org/10.5402/2012/376804

    Article  Google Scholar 

  23. Zhang, W., Yang, Y., Wang, Q., Shu, F.: An empirical study on classification of non-functional requirements. In: Proceedings of the 23rd International Conference on Software Engineering & Knowledge Engineering (SEKE 2011) (2011)

    Google Scholar 

  24. Chong, T.Y., Banchs, R.E., Chng, E.S., Li, H.: Modeling of term-distance and term-occurrence information for improving n-gram language model performance, p. 5 (2013)

    Google Scholar 

  25. Lu, M., Liang, P.: Automatic classification of non-functional requirements from augmented app user reviews. In: Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering – EASE 2017, Karlskrona, Sweden, pp. 344–353. ACM Press (2017)

    Google Scholar 

  26. Kurtanovic, Z., Maalej, W.: Automatically classifying functional and non-functional requirements using supervised machine learning. In: 2017 IEEE 25th International Requirements Engineering Conference (RE), Lisbon, Portugal, pp. 490–495. IEEE (2017)

    Google Scholar 

  27. Baker, C., Deng, L., Chakraborty, S., Dehlinger, J.: Automatic multi-class non-functional software requirements classification using neural networks. In: 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC), Milwaukee, WI, USA, pp. 610–615. IEEE (2019)

    Google Scholar 

  28. Roh, Y., Heo, G., Whang, S.E.: A survey on data collection for machine learning: a big data - AI integration perspective. arXiv:1811.03402 [cs, stat] (2018)

  29. Tsoumakas, G., Katakis, I.: Multi-label classification: an overview. Int. J. Data Warehouse. Min. 3, 1–13 (2007). https://doi.org/10.4018/jdwm.2007070101

    Article  Google Scholar 

  30. Cleland-Huang, J., Settimi, R., Xuchang, Z., Solc, P.: The detection and classification of non-functional requirements with application to early aspects. In: 14th IEEE International Requirements Engineering Conference (RE 2006), Minneapolis/St. Paul, MN, pp. 39–48. IEEE (2006)

    Google Scholar 

  31. Ormandjieva, O.: Ontology-based classification of non-functional requirements in software specifications: a new corpus and svm-based classifier (2013). https://doi.org/10.1109/COMPSAC.2013.64

    Article  Google Scholar 

  32. Singh, P., Singh, D., Sharma, A.: Rule-based system for automated classification of non-functional requirements from requirement specifications. In: 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), Jaipur, India, pp. 620–626. IEEE (2016)

    Google Scholar 

  33. Mahmoud, A., Williams, G.: Detecting, classifying, and tracing non-functional software requirements. Requirements Eng. 21, 357–381 (2016). https://doi.org/10.1007/s00766-016-0252-8

    Article  Google Scholar 

  34. Miguel, J.P., Mauricio, D., Rodríguez, G.: A review of software quality models for the evaluation of software products. Int. J. Softw. Eng. Appl. 5, 31–53 (2014). https://doi.org/10.5121/ijsea.2014.5603

    Article  Google Scholar 

  35. Pustejovsky, J., Stubbs, A.: Natural Language Annotation for Machine Learning. O’Reilly Media, Sebastopol (2013)

    Google Scholar 

  36. Hinze, A., Heese, R., Luczak-Rösch, M., Paschke, A.: Semantic enrichment by non-experts: usability of manual annotation tools. In: Cudré-Mauroux, P., Heflin, J., Sirin, E., Tudorache, T., Euzenat, J., Hauswirth, M., Parreira, J.X., Hendler, J., Schreiber, G., Bernstein, A., Blomqvist, E. (eds.) The Semantic Web – ISWC 2012, pp. 165–181. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  37. Nematzadeh, A., Meylan, S.C., Griffiths, T.L.: Evaluating vector-space models of word representation, or, the unreasonable effectiveness of counting words near other words. p. 6 (2017)

    Google Scholar 

  38. Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs] (2013)

Download references

Author information

Authors and Affiliations

  1. London South Bank University, 103 Borough Road, London, SE1 0AA, UK

    Maliha Sabir, Christos Chrysoulas & Ebad Banissi

Authors
  1. Maliha Sabir
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christos Chrysoulas
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ebad Banissi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Maliha Sabir , Christos Chrysoulas or Ebad Banissi .

Editor information

Editors and Affiliations

  1. Departamento de Engenharia Informática, Universidade de Coimbra, Coimbra, Portugal

    Álvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. FEUP, Universidade do Porto, Porto, Portugal

    Luís Paulo Reis

  4. DIMES, Università della Calabria, Arcavacata, Italy

    Sandra Costanzo

  5. Faculty of Electrical Engineering, University of Montenegro, Podgorica, Montenegro

    Irena Orovic

  6. Universidade Portucalense, Porto, Portugal

    Fernando Moreira

Rights and permissions

Reprints and permissions

Copyright information

© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sabir, M., Chrysoulas, C., Banissi, E. (2020). Multi-label Classifier to Deal with Misclassification in Non-functional Requirements. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S., Orovic, I., Moreira, F. (eds) Trends and Innovations in Information Systems and Technologies. WorldCIST 2020. Advances in Intelligent Systems and Computing, vol 1159. Springer, Cham. https://doi.org/10.1007/978-3-030-45688-7_49

Download citation

Publish with us

Policies and ethics

Search

Navigation