Decision tree model is the model for computational complexity and communication complexity. In computational complexity, the focus is in the classification of computational problems in accordance with their integral difficulty and then relates the classes to each other. These problems are usually solving by mechanical application of mathematical steps for example algorithm. An integral difficulty on the other hand, is a problem whose solution requires significant resources to be achieved despite of the algorithm applied. On the other hand, in communication complexity the amount of communication needed to for any distributed computations is quantified. It is a method where one wants to minimize the amount of energy used by decreasing the amount of the electrical signals required between the different existing modules during a distributed computation.
Conservative approach method in accounting refers to the branch of accounting where an extremely high degree of verification is required before any legal claims are made. It requires the recognition of any probability of a loss as it is revealed and any incurred expenditure. This means that they take into consideration future losses instead of profits. There is deferment of revenues until they are verified. This kind of strict revenue-recognition criteria tends to be the most common forms of accounting conservatism. It is very useful in cases where there is need to provide guidance where uncertainties and estimation procedural needs arise.
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In this case therefore, computational complexity can be the best option for use in conservative approach method. This is because there is need to compute and account for large amount of data as well as account for the losses and the expenditure used. There is need to compare any integral difficulty in the existing problem and then relate to each other before any legal claims are made. The use of complex mathematical steps like algorithm to come up with a solution can be accounted for.
References
Anderson, D., Sweeney, D., Williams, T., Camm, J., Cochran, J., Fry, M., & Ohlmann, J. (2016). Quantitative methods for business. (13thed.). Australia, Cengage Learning.
