Industrial IoT Authors: William Schmarzo, Elizabeth White, Stackify Blog, Yeshim Deniz, SmartBear Blog

Related Topics: Industrial IoT

Industrial IoT: Article

Visiting the DOM

Extending the Visitor Pattern

It is well known that traversing the XML DOM is a sometimes difficult and often tedious task. Executing code based on data retrieved from the DOM is even more complex. This article will demonstrate one way to abstract much of the logic from this repetitive task. The implementation of patterns is a technique that is often used to help simplify and intellectually manage projects, and the Visitor Pattern is appropriate and useful to help solve this problem. Reflection also plays a key role, and is used to determine the executed code based on the DOM node names at runtime.

XML has proven itself to be useful for storing the data for many types of applications (www.oasis-open.org). However, when you get down to it, XML is just a highly structured text file. Applications that use XML as their input format must process the XML file in order to get the data from it. Currently, there are two primary APIs that applications can use to traverse an XML file: DOM and SAX.

Document Object Model
The Document Object Model (DOM) provides the most obvious way of accessing data in an XML file. An XML document is essentially a tree: the root element of the XML document is the root node of the tree, and child elements in the XML document are the children of the root node. The DOM API provides an application with a tree data-structure that directly mirrors the XML file. The DOM API provides the ability to traverse the tree from one node to the next: parent-to-child, child-to-sibling, child-to-parent, etc.

Application developers use the API to write code that traverses the tree and performs processing on the tree's nodes (e.g., extract some piece of data). The trouble with the DOM API is twofold. First (and obviously), application developers must write the code that traverses the tree. However, this is often an unnecessary re-invention of the wheel. Many applications traverse the tree in a standard depth-first approach. It is unfortunate that the developer must spend time writing the actual tree-walking code, when it has been written before by countless developers.

The second drawback of the DOM API is the integration of the tree-walking code with the node-processing code. One of the hallmarks of good software design is the separation of concerns. This means the developer tries to separate the logical pieces of the code into separate methods/functions/modules. The unfortunate design of the DOM API requires that the complex code that walks the XML tree must be interspersed with the, quite possibly, complex code to process individual nodes.

The following code fragment illustrates the complexity of processing XML nodes using the DOM API. In this example we traverse an XML tree grabbing all the "color" elements and swapping the black and white ones.

demoChildNodes = document.getElementsByTagName("color");
for (int i = 0;i < demoChildNodes.getLength(); i++) {


Simple API for XML (SAX)
The Simple API for XML (SAX), first published in 1998, was developed as an event-based API for processing XML. Hot on the heels of the XML specification itself, it was well received by the development community.

SAX works by processing the XML one node at a time, creating a streaming process opposed to a static one. Event handlers are added to an XML document much in the same way they are added to a user interface. Such events are triggered as the application processes the document. Using this technique creates a very fast processing method, with a much smaller memory profile. This makes SAX appropriate for tasks such as searching a document for a specific node, or making small change to the entire document such as search and replace.

The down side is the lack of directional control, the document can only be process red in a "top to bottom" direction. Tasks like reordering nodes and cross-referencing are not practical. Also, while the specific syntax for simple documents (or simple processing tasks) is not overwhelming, SAX does not scale well for more complicated solutions. Listing 1 is a short example (the code for this article is online at www.sys-con.com/xml/sourcec.cfm).

The other drawback to SAX is the granularity of the event handlers. SAX is "coarse-grained" in the sense that large structural XML components invoke the same handler. For example, all "element" nodes would invoke the startElement() method. Many applications require a "finer-grained" event handler. For example, invoke a specific method when an "employee" element is reached.

Visitor Pattern
The problem of separating data-structure traversal from data-structure analysis/process is well-known. One standard technique of ensuring a separation of these components is the Visitor Pattern. One way of understanding the Visitor Pattern is that it allows operations to be added to a class (the pattern is an object-oriented one) without having to actually change the class. However, in the context of tree-walking, the Visitor Pattern is best understood as providing the capability of applying an endless number of node processors to a tree without having to change the definition of the node itself: it separates the node-processing code from the node definition.

For example, assume we have a tree data structure encapsulated in a tree class. This class defines a root node class that has links to its child nodes. Using the Visitor Pattern, we can define a MyVisitor class that has a method visitNode() that performs some kind of processing at each node in the tree. However, the Visitor Pattern allows us to focus the method on the node-processing code itself, and not the tree-traversal code. Once these two classes are defined, we could "apply" our visitor to our tree with the code: my Tree.accept(my Visitor); This would start a depth-first traversal of the tree and at each Node the My Visitor.visitNode()method would be called, allowing us to apply processing to each node.

In the future, if we want to update the processing, we would only need to modify the MyVisitor class. The tree and node classes would remain untouched. If we want to perform a different kind of processing on the tree, we would simply define a MyOther Visitor class with a visitNode() method and then apply our new visitor to the tree with: myTree. accept(my Other Visitor). Once again, the existing tree and node classes are untouched.

Visiting the DOM
We have developed a prototype DOM visitor in Java that supports the Visitor Pattern. The implementation is quite straightforward. A visitoradapter class encapsulates the tree-walking code and provides for standard depth-first traversal. Obviously, this class can be overridden to provide for more complex tree traversals.

The other major component of the prototype is the alteration of the NodeImpl class and the Node interface inside org.w3c.dom, which provides for the implementation of a DOM Node. The only change necessary is the addition of an accept() method that takes a Visitor class as a parameter and invokes the appropriate visitXXX() method in the Visitor class (where XXX is the name of the element). The accept() method uses reflection to determine which method to call in the visitor. Using reflection, the visitor Pattern provides the kind of "fine-grained" visitation that most applications require.

Another benefit of the Visitor Pattern is that it combines useful features of both DOM and SAX. The Visitor Pattern is "event-driven" to the extent the specific methods are called when specific nodes are reached in the tree. Furthermore, within a specific visit method, one can use the DOM API to traverse the tree in nonlinear ways, overcoming a significant limitation of SAX.

Hopefully, you have already begun to see the ease of using the Visitor Pattern as it applies to the XML DOM. Using this Pattern the developer can define numerous DOM analyzers and processors and apply them to a DOM tree. All of the tree-walking code can be handled automatically through the adapter class.

For example, Listing 2 encodes games in a chess library.

Using a Visitor Pattern, one can intuitively visit the nodes in the XML tree and apply processing to selected elements (see Listing 3).

If other kinds of processing need to be done, then the developer must only declare a new visitor class (extending VisitorAdapter) and provide appropriate visitXXX() methods.

Extending the DOM API to support the Visitor Pattern means that XML application developers are freed from writing tree-traversal code and can focus their efforts on the processing of each XML element. Another benefit is that if several operations are required to use the same XML data, the development workload can be easily divided among several programmers. The processing workload can be split among several processors or threads as well.

Extending the Java/Xerces DOM implementation is straight-forward and we urge Sun to consider incorporating our changes into a future release of the API.


  • Gamma, Erich; Helm, Richard; Johnson, Ralph; Vlissides, John. (1995) Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley Professional.
  • Comments (0)

    Share your thoughts on this story.

    Add your comment
    You must be signed in to add a comment. Sign-in | Register

    In accordance with our Comment Policy, we encourage comments that are on topic, relevant and to-the-point. We will remove comments that include profanity, personal attacks, racial slurs, threats of violence, or other inappropriate material that violates our Terms and Conditions, and will block users who make repeated violations. We ask all readers to expect diversity of opinion and to treat one another with dignity and respect.

    IoT & Smart Cities Stories
    Nicolas Fierro is CEO of MIMIR Blockchain Solutions. He is a programmer, technologist, and operations dev who has worked with Ethereum and blockchain since 2014. His knowledge in blockchain dates to when he performed dev ops services to the Ethereum Foundation as one the privileged few developers to work with the original core team in Switzerland.
    Andrew Keys is Co-Founder of ConsenSys Enterprise. He comes to ConsenSys Enterprise with capital markets, technology and entrepreneurial experience. Previously, he worked for UBS investment bank in equities analysis. Later, he was responsible for the creation and distribution of life settlement products to hedge funds and investment banks. After, he co-founded a revenue cycle management company where he learned about Bitcoin and eventually Ethereal. Andrew's role at ConsenSys Enterprise is a mul...
    René Bostic is the Technical VP of the IBM Cloud Unit in North America. Enjoying her career with IBM during the modern millennial technological era, she is an expert in cloud computing, DevOps and emerging cloud technologies such as Blockchain. Her strengths and core competencies include a proven record of accomplishments in consensus building at all levels to assess, plan, and implement enterprise and cloud computing solutions. René is a member of the Society of Women Engineers (SWE) and a m...
    If a machine can invent, does this mean the end of the patent system as we know it? The patent system, both in the US and Europe, allows companies to protect their inventions and helps foster innovation. However, Artificial Intelligence (AI) could be set to disrupt the patent system as we know it. This talk will examine how AI may change the patent landscape in the years to come. Furthermore, ways in which companies can best protect their AI related inventions will be examined from both a US and...
    In his general session at 19th Cloud Expo, Manish Dixit, VP of Product and Engineering at Dice, discussed how Dice leverages data insights and tools to help both tech professionals and recruiters better understand how skills relate to each other and which skills are in high demand using interactive visualizations and salary indicator tools to maximize earning potential. Manish Dixit is VP of Product and Engineering at Dice. As the leader of the Product, Engineering and Data Sciences team at D...
    Bill Schmarzo, Tech Chair of "Big Data | Analytics" of upcoming CloudEXPO | DXWorldEXPO New York (November 12-13, 2018, New York City) today announced the outline and schedule of the track. "The track has been designed in experience/degree order," said Schmarzo. "So, that folks who attend the entire track can leave the conference with some of the skills necessary to get their work done when they get back to their offices. It actually ties back to some work that I'm doing at the University of San...
    When talking IoT we often focus on the devices, the sensors, the hardware itself. The new smart appliances, the new smart or self-driving cars (which are amalgamations of many ‘things'). When we are looking at the world of IoT, we should take a step back, look at the big picture. What value are these devices providing. IoT is not about the devices, its about the data consumed and generated. The devices are tools, mechanisms, conduits. This paper discusses the considerations when dealing with the...
    Bill Schmarzo, author of "Big Data: Understanding How Data Powers Big Business" and "Big Data MBA: Driving Business Strategies with Data Science," is responsible for setting the strategy and defining the Big Data service offerings and capabilities for EMC Global Services Big Data Practice. As the CTO for the Big Data Practice, he is responsible for working with organizations to help them identify where and how to start their big data journeys. He's written several white papers, is an avid blogge...
    Dynatrace is an application performance management software company with products for the information technology departments and digital business owners of medium and large businesses. Building the Future of Monitoring with Artificial Intelligence. Today we can collect lots and lots of performance data. We build beautiful dashboards and even have fancy query languages to access and transform the data. Still performance data is a secret language only a couple of people understand. The more busine...
    Enterprises have taken advantage of IoT to achieve important revenue and cost advantages. What is less apparent is how incumbent enterprises operating at scale have, following success with IoT, built analytic, operations management and software development capabilities - ranging from autonomous vehicles to manageable robotics installations. They have embraced these capabilities as if they were Silicon Valley startups.