D.3.3 ALGORITHMS FOR INCREMENTAL ... - SecureChange
D.3.3 ALGORITHMS FOR INCREMENTAL ... - SecureChange
D.3.3 ALGORITHMS FOR INCREMENTAL ... - SecureChange
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application contexts is saved if the goals are fulfilled. These sequences are complex<br />
change reactions, which are evaluated by the user and applied on the model if<br />
selected.<br />
Figure 12. Quick fix generation algorithm<br />
The set of change operations in requirement engineering includes adding new actors,<br />
creating or removing trust relations etc. These operations can be defined using model<br />
transformation rules, each including a precondition and an action part. The<br />
precondition restricts the applicability of the operation (such as a trust relation can be<br />
created only between existing elements with the appropriate type).<br />
Once the user selects one of the generated quick fixes to be applied on the model,<br />
there is also a possibility of storing the quick fix as a complex change reaction. In order<br />
to create a reusable change reaction, its signature must be defined. The signature<br />
contains the list of elements that can be used as an application context for the change<br />
reaction. When applying the recorded change reaction using a given signature,<br />
undefined elements and variables not present in the signature but used in the<br />
sequence of operations are selected using pattern matching.<br />
Apart from the design space exploration approach, it is also possible to record change<br />
reactions for future use by recording manual changes performed by the user on in the<br />
editor. In this case, the framework could use inductive reasoning to determine the<br />
signature for the recorded change reaction.<br />
Further enhancement to the approach could include an automated initialization of<br />
capturing when a given event occurs (such as the appearance of a violation), then<br />
each performed action would be recorded until the violation is corrected. Thus the<br />
recording can be controlled using evolution triggers.<br />
This way of learning complex change reactions that can be used to respond to<br />
violations and evolution triggers leads to an inductive framework, where each change<br />
reaction further enhances the response capabilities of the quick fix generation tool, and<br />
increases the usefulness of this feature.<br />
<strong>D.3.3</strong> Algorithms for Incremental Requirements Models<br />
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