A modern personal finance app that helps users to record transactions, manage budgets, view spending, and calculate net worth.

Modified tree structures are used to stored the categories and values of net worth items.

Each individual leaf is the fundamental element of the AssetsTypeTree expressed as a list.

• The idea behind a list representation of the tree is to use each leaf node to store the address of the leaf node in the tree by documenting the name of its parent and its parent's parent.
• Advantages of a list representation of the Tree structure
  1. A list representation of the tree is the best way to store the results of deserialization.
  2. A list is easier to manipulate in a java setting with the Tree processor objects.

A tree structure that stored the item name and address.

• The Type Tree provide a reference for the Value Tree to construct itself.
• The tree structure can be obtained through a deserialization of the database entity AssetsType.

A tree structure that is mostly used to store the value of each net worth item.

• The relationship of the Value trees' nodes are mapped from the Type trees' nodes as it stored the relationship between nodes.
• Each node is an AssetsValue object which contains the id, name, value, time.

A data processor is designed to retrieve data of a particular node or a collection of nodes.

• The Type Tree Processor is designed to be read-only as the business logic of Finance defines a fixed number of categories for net worth items.
• Usage:
  1. Used by the adapter of the Expandable List to retrieve the sub group of net worth items in order to format the data stored in AssetsTypeTree so that they are compatible with the Expandable List widgets.
  2. Used in the Breadth-First Search algorithm to retrieve the child nodes of a particular node.

The Value Tree Processor is used to manipulate the data stored in the Value tree structure.

• This processor contains methods to perform READ, EDIT, GROUP, DELETE on the data structure.
• This data source of the processor also stores all the data including the values and the Type tree.

The data stored in the Assets Value Processor is illustrated by the table below:

The following table shows the actions that can be performed on the Value tree structure:

Each leaf node contains the name of the leaf node, and the address of the node. A simple example below demonstrates the structure of a leaf node.

A node container is essentially a data carrier that contains the essential data of a node as well as its level in the tree structure. It enables a more efficient access of the level as well as essential data when constructing the Multi-Expandable list.

The node container is mainly used in the following two ways:

• Constructing the Expandable Lists:

  When the data of a certain level is needed, the Type Tree Processor will prepare the node container by putting each node of the particular level into a node container and recording its level. After the preparation is done, the group of node containers will be injected into the Expandable List Adapter. The mechanism in the adapter will assign the group to the corresponding level and retrieve the data in the node container and deliver them to the right widget on the UI.

• Retrieve the data from the input box and inject into the Tree Processor:

  Each node container will be "paired" with a Input box (EditText), and a TextListener will be added to the Input Box. Once change is detected, the value will be injected into an AssetsValue object and stored in the data source (list of AssetsValue objects) Value Tree Processor. The id from the node container will also be injected and used as an identifier of the node.

The example below shows the structure of a node container and the group under Retirement Accounts that will be used to construct a nested expandable list: