Heterogeneous Data Structure “r-Atrain”
Ranjit Biswas · Advances in computational intelligence and robotics book series · 2013
The data structure “r-Train” (“Train” in short) where r is a natural number is a new kind of powerful robust data structure that can store homogeneous data dynamically in a flexible way, in particular for large amounts of data. But a train cannot store heterogeneous data (by the term heterogeneous data, the authors mean data of various datatypes). In fact, the classical data structures (e.g., array, linked list, etc.) can store and handle homogeneous data only, not heterogeneous data. The advanced data structure “r-Atrain” (“Atrain” in short) is logically almost analogous to the data structure r-train (train) but with an advanced level of construction to accommodate heterogeneous data of large volumes. The data structure train can be viewed as a special case of the data structure atrain. It is important to note that none of these two new data structures is a competitor of the other. By default, any heterogeneous data structure can work as a homogeneous data structure too. However, for working with a huge volume of homogeneous data, train is more suitable than atrain. For working with heterogeneous data, atrain is suitable while train cannot be applicable. The natural number r is suitably predecided and fixed by the programmer depending upon the problem under consideration and also upon the organization/industry for which the problem is posed.