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There are two discussions here that need to be responded to thoroughly. Responses must be on APA format 150+words 1-2 legitimate verifiable sources per response.

CIS555 discussion 1 post responses.

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Respond to the colleagues posts regarding:

“Model Verification” Please respond to the following:

• Determine whether you would use theorem proving, the use of a catalogue of formal refinement patterns, or SAT solver technology to verify an engineering model. Support your position.

• From the e-Activity, determine whether or not you believe that a SAT solver will always be able to find a solution or verify a model. Support your position.

MH’s post states the following:

“Model Verification” Please respond to the following:

Determine whether you would use theorem proving, the use of a catalogue of formal refinement patterns, or SAT solver technology to verify an engineering model. Support your position.

As recommended by van Lamsweerde (2009), unless the goal were critical, I would likely avoid using any of these techniques because of their complexity (p. 603). However, if the circumstances required, I would likely choose to verify an engineering model using formal refinement patterns.

Theorem proving is a complicated, heavy-weight process that does not reliably indicate if verification fails (van Lamsweerde, 2009, p. 604). SAT solvers may not identify bugs in the system based on how they are bounded (van Lamsweerde, 2009, p. 609). Refinement patterns, while they do have drawbacks, are easier to employ and because the patterns are “proved once for all” (van Lamsweerde, 2009, p. 605).

From the e-Activity, determine whether or not you believe that a SAT solver will always be able to find a solution or verify a model. Support your position.

I believe that an SAT solver can always find a solution or verify a model. SAT solvers assign values to variables until it finds a solution that satisfies all system constraints, or until hits a conflict (Bryant, 2010). If it hits a conflict, it “undoes the assignment” and then continues the process until it identifies a solution (or proves that the problem cannot be satisfied based on the constraints.)

References

Bryant, R. E. (2010, May 12). Using a SAT solver to color a map [Video file]. Retrieved from http://www.youtube.com/watch?v=0gt503wK7AI.

van Lamsweerde, A. (2009). Requirements engineering: From system goals to UML models to software specifications. West Sussex, England: John Wiley.

CIS555 discussion 2 post responses.

Respond to the colleagues posts regarding:

“Model Synthesis” Please respond to the following:

• Examine the advantages and disadvantages of using the goal-driven model. Propose how you would assess the success factors of the goal-driven model synthesis.

• Examine the advantages and disadvantages of using a scenario-driven model synthesis approach as a formal specification of mission-critical goals, domain properties and operations. Propose how you would assess the success factors of the scenario-driven model synthesis.

MH’s post states the following:

Question:

Which approach would you use in your next project? a goal-driven model or a a scenario-driven model? And why?

• Examine the advantages and disadvantages of using the goal-driven model. Propose how you would assess the success factors of the goal-driven model synthesis.

• Examine the advantages and disadvantages of using a scenario-driven model synthesis approach as a formal specification of mission-critical goals, domain properties and operations. Propose how you would assess the success factors of the scenario-driven model synthesis.

Goal models capture how both functional and non-functional goals contribute positively or negatively to each other through the use of AND/OR diagrams. They support “various forms of early, declarative, and incremental reasoning for, e.g., goal refinement and completeness checking, conflict management, hazard analysis, threat analysis, requirements document generation, and so forth” (Damas, Lambeau, & van Lamsweerde, 2006, p. 197). Unfortunately, these models can be perceived as “too abstract by stakeholders”, “cover classes of intended behaviors [that] are left implicit”, and maybe hard to and make fully precise (Damas, Lambeau, & van Lamsweerde, 2006, p. 197).

“Scenarios capture typical examples or counterexamples of system behavior through sequences of interactions among agents” (Damas, Lambeau, & van Lamsweerde, 2006, p. 197). They are easy for stakeholders to understand because they “support an informal, narrative, and concrete style of description” (Damas, Lambeau, & van Lamsweerde, 2006, p. 197). On the other hand, scenarios may not cover all system behaviors, don’t explicitly define the intended system properties, and may incorporate premature design decisions

Both goal-driven model synthesis and scenario-driven model synthesis can produce state machines that can be used to animate models. These animations can be used to identify deficiencies in the requirements or to confirm the requirements will produce the desired outcomes.

References

Damas, C., Lambeau, B. & van Lamsweerde, A. (2006) Scenarios, goals, and state machines: A win-win partnership for model synthesis.” Proceedings of the 14th ACM SIGSOFT International Symposium on Foundations of Software Engineering – SIGSOFT ’06/FSE-14, ACM Press, 2006, p. 197. DOI.org (Crossref), doi:10.1145/1181775.1181800.

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