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KBRE: a framework for knowledge-based requirements engineering

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Abstract

Detecting inconsistencies is a critical part of requirements engineering (RE) and has been a topic of interest for several decades. Domain knowledge and semantics of requirements not only play important roles in elaborating requirements but are also a crucial way to detect conflicts among them. In this paper, we present a novel knowledge-based RE framework (KBRE) in which domain knowledge and semantics of requirements are central to elaboration, structuring, and management of captured requirements. Moreover, we also show how they facilitate the identification of requirements inconsistencies and other-related problems. In our KBRE model, description logic (DL) is used as the fundamental logical system for requirements analysis and reasoning. In addition, the application of DL in the form of Manchester OWL Syntax brings simplicity to the formalization of requirements while preserving sufficient expressive power. A tool has been developed and applied to an industrial use case to validate our approach.

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Notes

  1. In our model, expressions in Manchester Syntax can be translated into description logics automatically and vice versa.

  2. In description logics, roles represent binary relationships between classes.

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Acknowledgements

We thank the anonymous reviewers for the helpful discussions and comments. This work is supported by the ARC Grant DP0987380.

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Authors and Affiliations

  1. Faculty of Information and Communication Technology, Swinburne University of Technology, Melbourne, VIC, Australia

    Tuong Huan Nguyen, Bao Quoc Vo, Markus Lumpe & John Grundy

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  1. Tuong Huan Nguyen
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  2. Bao Quoc Vo
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Correspondence to Tuong Huan Nguyen.

Appendix

Appendix

1.1 ReInDetector description

In this section, we present a scenario to demonstrate the functionality of REInDetector. The scenario in this demonstration is part of the traveler social networking use case which was taken in the evaluation section. The steps through this demonstration are described as followed.

  1. 1.

    In the first step, the requirement F24_IfGrpCommNoForum is added (assume that it has not been added) (cf. Fig. 10).

    Fig. 10
    figure 10

    Adding new requirements

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  2. 2.

    In this step, we show the value of domain knowledge and semantics and how they can help in detecting requirements inconsistencies. We use

    • F22_SupForum : System needs to provide a forum for discussions ( System SubClassOf supportFeature SOME Forum ).

    • F26_SupUserGroup : System supports the creation of user groups to facilitate the connection ( System SubClassOf supportFeature SOME UserGroup ).

    • F24_IfGrpCommNoForum : If the system supports any type of group communication, then no forum is needed ( supportFeature SOME GroupCommunication NOT (SubClassOf supportFeature SOME Forum) ).

    But without a proper characterization of the associated relationship between the capture concepts, no problems can manifest (cf. Fig. 11). We wish to emphasize this point here, in particular, to motivate the need for proper knowledge representation in RE.

    Fig. 11
    figure 11

    Requirements set with inconsistent goals

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  3. 3.

    Next, we demonstrate how the ontology editor can be used to define concepts, roles, instances, domain knowledge, rules, and constraints (cf. Fig. 12) In particular, we show how “UserGroup” can be defined as a sub-concept of “GroupCommunication”.

    Fig. 12
    figure 12

    Defining semantics with ontology editor

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  4. 4.

    Next, we show how to use the reasoner in analyzing requirements to identify inconsistencies and how the provided explanations may help requirements engineers get more insights into the problem (cf. Fig. 13).

    Fig. 13
    figure 13

    A scenario of inconsistency

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  5. 5.

    In the next step, we present the requirement query support provided by REInDetector. We particularly make a query to analyze a partial set of requirements which does not contains all requirements involved in the inconsistency. The results from the reasoner indicates that there is no inconsistency in this set of requirements (cf. Figure 14).

    Fig. 14
    figure 14

    Requirement query service

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  6. 6.

    In the final step of the demonstration, we show how the identified inconsistency can be resolved. In this case, that is done by removing one of the inconsistent requirements ( F24_IfGrpCommNoForum ) (cf. Fig. 15)

    Fig. 15
    figure 15

    All inconsistencies resolved

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1.2 Availability

REInDetector, accompanied with a demo scenario and user quick-start guide are available for download at: http://www.ict.swin.edu.au/personal/huannguyen/REInDetector.html

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Nguyen, T.H., Vo, B.Q., Lumpe, M. et al. KBRE: a framework for knowledge-based requirements engineering. Software Qual J 22, 87–119 (2014). https://doi.org/10.1007/s11219-013-9202-6

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