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4 Orchestrating Requirements and Testing Processes In this section we give a quick overview of the orchestration of requirements engineering process and testing process. The process can be understood as an instantiation of the more general and project wide integration presented in deliverable D2.2. The process illustrated in Figure 9 is exemplified in Appendix D based on the change requirement “Specification Evolution” of the POPS case study. The orchestration of the requirements engineering process and the test generation process is based on the identification of a set of concepts that are shared or mappable in the two domains: a shared concept is a concept that has the same semantics in both domains while a mappable concept is a concept that is related to one in the other domain. Table 2 illustrates the conceptual interface. When a concept is changed in a model then a corresponding change request is issued to the other model. Requirement concept Testing concept Kind of integration Goal Test Model (State Machine, OCL code) Action Test Model (State Machine, OCL code) Mapped concept Mapped concept Achievement level Test result Mapped concept Actor SUT Mapped concept Requirement Requirement Shared concept Table 2. Conceptual mapping We identify one shared concepts that is Requirement. A Requirement in both domains represents a statement by a stakeholder about what the system should do. The concepts of Actor, Goal and Process, are mapped on the Test Model. In particular, the concept of Actor is used to identify the system under test (SUT). The concepts of Goal and Process are used by the testing engineer to build the different types of Test Models. The goals and processes in the Requirement Model are identified by a unique name that is used to annotate the State Machine of the Test Model and the OCL code in order to achieve traceability between the Requirement Model and the Test Model. Mapping of a test case's result and status to a requirement achievement level allows the requirement engineer to quantify the requirement coverage after evolution. This correspondence is reported in Table 3: if the status of a test case after evolution is new, adapted or updated, and the test result is pass the requirement covered by the test case is fulfilled while it is denied (i.e. we have evidence that has not been achieved) if the test result is fail. A subtle case is present when a test case is part of <strong>D.3.3</strong> Algorithms for Incremental Requirements Models Evaluation and Transformation| version 1.19 | page 20/136
the stagnation suite (i.e. obsolete) and the test result is fail. Here the test covers requirements that have been deleted from the model and thus the corresponding behavior should no longer be present (for example a withdrawn authorization) so failing the test shows that the unwanted behavior is no longer present. Figure 9. Orchestrated process <strong>D.3.3</strong> Algorithms for Incremental Requirements Models Evaluation and Transformation| version 1.19 | page 21/136
Page 1 and 2: D.3.3 ALGORITHMS FOR INCREMENTAL RE
Page 3 and 4: 1.14 19 January Final 1.15 23 Janua
Page 5 and 6: Index DOCUMENT INFORMATION 1 DOCUME
Page 7 and 8: 1 Introduction This deliverable pre
Page 9 and 10: (Clause 6.4.3) processes of ISO/IEC
Page 11 and 12: 3 Orchestrating Requirements and Ri
Page 13 and 14: grey. The ADS-B introduction requir
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Page 17 and 18: are supported by the argumentation
Page 19: ADS-B Manage ADS-B signal ADS-B sig
Page 23 and 24: 5 A framework for modeling and reas
Page 25 and 26: sectors. And there is 42% of probab
Page 27 and 28: SDA(C) = {DA 2 , DA 4 , DA 8 , DA 1
Page 29 and 30: application contexts is saved if th
Page 31 and 32: Figure 14. ATM model state after qu
Page 33 and 34: References [1] Yudis Asnar, Fabio M
Page 35 and 36: Managing Changes with Legacy Securi
Page 37 and 38: Failure in the provisioning of corr
Page 39 and 40: propagated to the system designer a
Page 41 and 42: APPENDIX B D.3.3 Algorithms for Inc
Page 43 and 44: is sometimes difficult, especially
Page 45 and 46: Tactical Monitor air R controller t
Page 47 and 48: protected from harm. Since in CORAS
Page 49 and 50: CModel. The postcondtion checks the
Page 51 and 52: of ADS-B signal and Availability of
Page 53 and 54: extensions to i* to model and analy
Page 55 and 56: 3. Bzivin, J., Dup, G., Jouault, F.
Page 57 and 58: APPENDIX C D.3.3 Algorithms for Inc
Page 59 and 60: steps. Section V demonstrates the R
Page 61 and 62: that should be mitigated by the sys
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Page 65 and 66: TABLE IV PRIORITIZATION OF RISKS FO
Page 67 and 68: context. We believe that the Common
Page 69 and 70: Managing Evolution by Orchestrating
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1.1 The Contribution of this Paper
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Fig. 3. Integrated Change Managemen
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The requirement analysis is an iter
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Table 1. Conceptual Interface Requi
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Legend: Goals surrounded by dashed
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Table 5. Test Suite for GP-2.2 Tran
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6. P. K. Chittimalli and M. J. Harr
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Noname manuscript No. (will be inse
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Dealing with Known Unknowns: A Goal
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Understanding How to Manage Require
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Chatzoglou et al. [4] conducted a s
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Evolution Elicitation Probability E
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Table 2. Participants Background Pa
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for the defined success criteria. O
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Fig. 3. Codes Coverage ATM systems,
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The feedbacks provided by the ATM e
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3. P. Carlshamre, K. Sandahl, M. Li
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Quick fix generation for DSMLs Ábe
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• extensibility: the supported li
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Fig. 7. Overview of the Quick fix g
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Fig. 9. Evaluation results (|V(M I
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