Abstract
[Context and Motivation] A critical success factor in Requirements Engineering (RE) involves recognizing conflicts in Quality Requirements (QRs). Nowadays, Quality Attributes Relationship Matrix (QARM) is utilized to identify the conflicts in QRs. The static QARM represents how one Quality Attribute (QA) undermines or supports to achieve other QAs. [Question/Problem] However, emerging technology discovers new QAs. Requirements analysts need to invest significant time and non-trivial human effort to acquire knowledge for the newly discovered QAs and influence among them. This process involves searching and analyzing a large set of quality documents from literature and industries. In addition, the use of static QARMs, without knowing the purpose of the QRs in the system may lead to false conflict identification. Rather than taking all QAs, domain-specific QAs are of great concern for the system being developed. [Principal ideas/results] In this paper, we propose an approach which is aimed to build an adaptive QARM semi-automatically. We empirically evaluate the approach and report an analysis of the generated QARM. We achieve 85.67% recall, 59.07% precision and 69.14% F-measure to acquire knowledge for QAs. [Contributions] We provide an algorithm to acquire knowledge for domain-specific QAs and construct an adaptive QARM from available unconstrained natural language documents and web search engines.
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Notes
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In this work, the term “Interdependency” indicates the relationship among QAs (i.e. how QAs support or limit one or more QAs).
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Ontology is a formal description of the concept of sharing, stressing the link between real entities [24]. The ontology helps domain users- to suggest their NFRs effectively and requirements analysts- to understand and model the NFRs accurately. Building ontology based on domain knowledge gives a formal and explicit specification of a shared conceptualization.
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References
IEEE Computer Society, Software Engineering Standards Committee, and IEEE-SA Standards Board: IEEE recommended practice for software requirements specifications. Institute of Electrical and Electronics Engineers (1998)
Shah, U.S., Patel, S., Jinwala, D.: Specification of non-functional requirements: a hybrid approach. In: REFSQ Workshops (2016)
Guizzardi, R.S.S., Li, F.-L., Borgida, A., Guizzardi, G., Horkoff, J., Mylopoulos, J.: An ontological interpretation of non-functional requirements. In: FOIS, vol. 14, pp. 344–357 (2014)
Chung, L., Nixon, B.A., Yu, E., Mylopoulos, J.: Non-Functional Requirements in Software Engineering, 5th edn. Springer, Heidelberg (2012)
Egyed, A., Grunbacher, P.: Identifying requirements conflicts and cooperation: how quality attributes and automated traceability can help. IEEE Softw. 21(6), 50–58 (2004)
ISO/IEC 9126-1:2001 Software engineering product quality-part 1: quality model. International Organization for Standardization (2001)
Duque-Ramos, A., Fernández-Breis, J.T., Stevens, R., Aussenac-Gilles, N.: SQuaRE: A SQuaRE-based approach for evaluating the quality of ontologies. J. Res. Pract. Inf. Technol. 43(2), 159 (2011)
Mairiza, D., Zowghi, D., Nurmuliani, N.: Managing conflicts among non-functional requirements. In: Workshop on Requirements Engineering, pp. 11–19. University of Technology, Sydney (2009)
Sadana, V., Liu, XF.: Analysis of conflicts among non-functional requirements using integrated analysis of functional and non-functional requirements. In: 31st Annual International Computer Software and Applications Conference (COMPSAC 2007), vol. 1, pp. 215–218. IEEE (2007)
Abdul, H., Jamil, A., Imran, U.: Conflicts identification among non-functional requirements using matrix maps. World Acad. Sci. Eng. Technol. 44, 1004–1009 (2010)
Mairiza, D., Zowghi, D., Gervasi, V.: Conflict characterization and analysis of non functional requirements: an experimental approach. In: 12th International Conference on Intelligent Software Methodologies, Tools and Techniques (SoMeT), September 2013, pp. 83–91. IEEE (2013)
Carvalho, R., Andrade, R., Oliveira, K., Kolski, C.: Catalogue of invisibility requirements for UbiComp and IoT applications. In: 26th International Requirements Engineering Conference (RE), pp. 88–99. IEEE (2018)
Maia, M.E., Rocha, L.S., Andrade, R.: Requirements and challenges for building service-oriented pervasive middleware. In: Proceedings of the 2009 International Conference on Pervasive Services, pp. 93–102. ACM (2009)
Carvalho, R.M., de Castro Andrade, R.M., de Oliveira, K.M.: AQUArIUM - a suite of software measures for HCI quality evaluation of ubiquitous mobile applications. J. Syst. Softw. 136, 101–136 (2018)
Serrano, M.: Ubiquitous, pervasive and mobile computing: a reusable-models-based non-functional catalogue objectives of research. In: ER@ BR (2013)
Carvalho, R.M., de Castro Andrade, R.M., de Oliveira, K.M., de Sousa Santos, I., Bezerra, C.I.M.: Quality characteristics and measures for human-computer interaction evaluation in ubiquitous systems. Softw. Q. 25(3), 743–795 (2017). https://doi.org/10.1007/s11219-016-9320-z
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(6), 31–53 (2014)
Boehm, B.W., Brown, J.R., Kaspar, H.: Characteristics of Software Quality. North Holland, Amsterdam (1978)
McCall, J.A., Richards, P.K., Walters, G.F.: Factors in Software Quality. Volume I. Concepts and Definitions of Software Quality. General Electric Co., Sunnyvale (1977)
Grady, R.B., Caswell, D.L.: Software Metrics: Establishing a Company-Wide Program. Prentice Hall, Upper Saddle River (1987)
Dromey, R.G.: A model for software product quality. IEEE Trans. Softw. Eng. 21(2), 146–162 (1995)
Shah, U.S., Jinwala, D.C.: Resolving ambiguities in natural language software requirements: a comprehensive survey. ACM SIGSOFT Softw. Eng. Notes 40(5), 1–7 (2015)
Shah, U.S., Jinwala, D.C.: Resolving ambiguity in natural language specification to generate UML diagrams for requirements specification. Int. J. Softw. Eng. Technol. Appl. 1(2–4), 308–334 (2015)
Gruber, T.R.: A translation approach to portable ontology specifications. Knowl. Acquis. 5(2), 199–220 (1993)
Islam, A., Inkpen, D.: Semantic text similarity using corpus-based word similarity and string similarity. ACM Trans. Knowl. Discov. Data 2(2), 1–25 (2008). Article No. 10
Banerjee, S., Pedersen, T.: An adapted Lesk algorithm for word sense disambiguation using WordNet. In: Gelbukh, A. (ed.) CICLing 2002. LNCS, vol. 2276, pp. 136–145. Springer, Heidelberg (2002). https://doi.org/10.1007/3-540-45715-1_11
Jedlitschka, A., Ciolkowski, M., Pfahl, D.: Reporting experiments in software engineering. In: Shull, F., Singer, J., Sjøberg, D.I.K. (eds.) Guide to Advanced Empirical Software Engineering, pp. 201–228. Springer, London (2008). https://doi.org/10.1007/978-1-84800-044-5_8
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Shah, U., Patel, S., Jinwala, D. (2020). A Semi-automated Approach to Generate an Adaptive Quality Attribute Relationship Matrix. In: Madhavji, N., Pasquale, L., Ferrari, A., Gnesi, S. (eds) Requirements Engineering: Foundation for Software Quality. REFSQ 2020. Lecture Notes in Computer Science(), vol 12045. Springer, Cham. https://doi.org/10.1007/978-3-030-44429-7_17
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