Abstract
In order to obtain a most effective return on a software project investment, then at least one requirements inspection shall be completed. A formal requirement inspection identifies low quality knowledge representation content in the requirements document. In software development projects where natural language requirements are produced, a requirements document summarizes the results of requirements knowledge analysis and becomes the basis for subsequent software development. In many cases, the knowledge content quality of the requirements documents dictates the success of the software development. The need for determining knowledge quality of requirements documents is particularly acute when the target applications are large, complicated, and mission critical. The goal of this research is to develop knowledge content quality indicators of requirements statements in a requirements document prior to informal inspections. To achieve the goal, knowledge quality properties of the requirements statements are adopted to represent the quality of requirements statements. A suite of complexity metrics for requirements statements is used as knowledge quality indicators and is developed based upon natural language knowledge research of noun phrase (NP) chunks. A formal requirements inspection identifies low quality knowledge representation content in the requirements document. The knowledge quality of requirements statements of requirements documents is one of the most important assets a project must inspect. An application of the metrics to improve requirements understandability and readability during requirements inspections can be built upon the metrics shown and suggested to be taken into account.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abney, S.: Parsing by chunks. In: Berwick, R., Abney, S., Tenny, C. (eds.) Principle-Based Parsing. Kluwer Academic Publishers, Dordrecht (1991)
Basili, V.R.: Qualitative Software Complexity Models: A Summary, Tutorial on Models and Methods for Software Management and Engineering. IEEE Computer Society Press, Los Alamitors (1980)
Bøegh, J.: A new standard for quality requirements. IEEE Softw. 25(2), 57–63 (2008)
Briand, L.C., Daly, J.W., Wust, J.K.: A unified framework for cohesion measurement in object-oriented systems. IEEE Trans. Softw. Eng. 3(1), 65–117 (1998)
Briand, L.C., Daly, J.W., Wust, J.K.: A unified framework for coupling measurement in object-oriented systems. IEEE Trans. Softw. Eng. 25, 91–121 (1999)
Cant, S., Jeffery, D.R., Henderson-Sellers, B.: A conceptual model of cognitive complexity of elements of the programming process. Inf. Softw. Technol. 37(7), 351–362 (1995)
Chung, L., do Prado Leite, J.C.S.: On non-functional requirements in software engineering. In: Borgida, A.T., Chaudhri, V.K., Giorgini, P., Yu, E.S. (eds.) Conceptual Modeling: Foundations and Applications. LNCS, vol. 5600, pp. 363–379. Springer, Heidelberg (2009)
Costello, R.J., Liu, D.-B.: Metrics for requirements engineering. J. Syst. Softw. 29(1), 39–63 (1995)
Darcy, D.P., Kemerer, C.F., Software Complexity: Toward a Unified Theory of Coupling and Cohesion, 8 February 2002
Davis, A., Overmyer, S., Caruso, J., Dandashi, F., Dinh, A.: Identifying and measuring quality in a software requirements specification. In: Proceedings of the First International Software Metrics Symposium, 21–22 May, pp. 141–152 (1993)
Demarco, T.: Controlling Software Projects. Yourdon Press, Englewood Cliffs (1982)
Din, C.Y.: Requirements content goodness and complexity measurement based on NP chunks. Ph.D. thesis, George Mason University, Fairfax, VA, 2007, Reprinted by VDM Verlag Dr. Muller (2008)
Din, C.Y., Rine, D.C.: Requirements content goodness and complexity measurement based on NP chunks. In: Proceedings, Complexity and Intelligence of the Artificial Systems: Bio-inspired Computational Methods and Computational Methods Applied in Medicine, WMSCI 2008 Conference (2008)
Din, C.Y., Rine, D.C.: Requirements metrics for requirements statements stored in a database. In: Proceedings of the 2012 International Conference on Software Engineering Research and Practice, SERP 2012, July 16–19, pp. 1–7 (2012)
Din, C.Y., Rine, D.C.: Requirements Statements Content Goodness and Complexity Measurement. International Journal of Next-Generation Computing. 4(1) (2013)
Evangelist, W.: Software complexity metric sensitivity to program structuring rules. J. Syst. Softw. 3(3), 231–243 (1983)
Fagan, M.: Advances in Software Inspections. IEEE Trans. Softw. Eng. 12(7), 744–751 (1986)
Fanmuy, G., Fraga, A., Llorens, J.: Requirements Verification in the Industry. CSDM, Paris, France (2011)
Farbey, B.: Software quality metrics: considerations about requirements and requirement specifications. Inf. Softw. Technol. 32(1), 60–64 (1990)
Fenton, N.E., Neil, M.: Software metrics: roadmap. In: Proceedings of the International Conference on Software Engineering (ICSE), pp. 357–370 (2000)
Fenton, N.E., Pleeger, S.L.: Software Metrics: A Rigorous and Practical Approach, 2nd edn. International Thomson Computer Press, Boston (1997)
Genova, G., et al.: A framework to measure and improve the quality of textual requirements. Requirements Eng. 18(1), 25–41 (2013). doi:10.1007/s00766-011-0134-z. Url: http://dx.doi.org/10.1007/s00766-011-0134-z
Graesser, A.C., Mcnamara, D.S., Louwerse, M.M., Cai, Z.: Coh-Metrix: analysis of text on cohesion and language. Behav. Res. Methods Instrum. Comput. 36(2), 193–202 (2004)
Henderson-Sellers, B.: Object-Oriented Metrics textendash Measures of Complexity. Prentice Hall PTR, New Jersey (1996)
Kemerer, C.F.: Progress, obstacles, and opportunities in software engineering economics. Commun. ACM 41, 63–66 (1998)
Kitchenham, B.A., Pleeger, S.L., Fenton, N.E.: Towards a framework for software measurement validation. IEEE Trans. Softw. Eng. 21, 929–943 (1995)
Klemola, T.: A cognitive model for complexity metrics, vol. 13 (2000)
Mcnamara, D.S.: Reading both high and low coherence texts: effects of text sequence and prior knowledge. Can. J. Exp. Psychol. 55, 51–62 (2001)
Mcnamara, D.S., Kintsch, E., Songer, N.B., Kintsch, W.: Are good texts always better? Text coherence, background knowledge, and levels of understanding in learning from text. Cogn. Instr. 14, 1–43 (1996)
Pleeger, S.L.: Lessons learned in building a corporate metrics program. IEEE Softw. 10(3), 67–74 (1993)
Purao, S., Vaishnavi, V.: Product Metrics for Object-Oriented Systems. ACM Comput. Surv. 35(2), 191–221 (2003)
Rakitin, S.: Software verification and validation: a practitioner’s guide (Artech House Computer Library). Artech House Publishers, Norwood (1997). ISBN-10: 0890068895 ISBN-13: 978-0890068892
Ricker, M.: Requirements specification understandability evaluation with cohesion, context, and coupling. Ph.D. thesis, George Mason University, Fairfax, VA (1995)
Schneider, R.E., Buede D.,: Criteria for selecting properties of a high quality informal requirements document. In: Proceedings of the International Conference on Systems Engineering, Mid-Atlantic Regional Conference, INCOSE-MARC, 5–8 April 2000a, pp. 7.2-1–7.2-5 (2000)
Schneider, R.E., Buede D.: Properties of a high quality informal requirements document. In: Proceedings of the Tenth Annual International Conference on Systems Engineering, INCOSE, 16–20 July, 2000b, pp. 377–384 (2000)
Weyuker, E.: Evaluating software complexity measures. IEEE Trans. Softw. Eng. 14(9), 1357–1365 (1988)
Wnuk, K., Regnell, B., Berenbach, B.: Scaling up requirements engineering – exploring the challenges of increasing size and complexity in market-driven software development. In: Berry, D. (ed.) REFSQ 2011. LNCS, vol. 6606, pp. 54–59. Springer, Heidelberg (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rine, D.C., Fraga, A. (2015). Chunking Complexity Measurement for Requirements Quality Knowledge Representation. In: Fred, A., Dietz, J., Liu, K., Filipe, J. (eds) Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2013. Communications in Computer and Information Science, vol 454. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46549-3_16
Download citation
DOI: https://doi.org/10.1007/978-3-662-46549-3_16
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-46548-6
Online ISBN: 978-3-662-46549-3
eBook Packages: Computer ScienceComputer Science (R0)