Rest dissertation fielding

Visibility is improved because a monitoring system does not have to look beyond a single request datum in order to determine the full nature of the request. Reliability is improved because it eases the task of recovering from partial failures [ ]. Scalability is improved because not having to store state between requests allows the server component to quickly free resources, and further simplifies implementation because the server doesn't have to manage resource usage across requests.

Like most architectural choices, the stateless constraint reflects a design trade-off. The disadvantage is that it may decrease network performance by increasing the repetitive data per-interaction overhead sent in a series of requests, since that data cannot be left on the server in a shared context. In addition, placing the application state on the client-side reduces the server's control over consistent application behavior, since the application becomes dependent on the correct implementation of semantics across multiple client versions. In order to improve network efficiency, we add cache constraints to form the client-cache-stateless-server style of Section 3.

Cache constraints require that the data within a response to a request be implicitly or explicitly labeled as cacheable or non-cacheable. If a response is cacheable, then a client cache is given the right to reuse that response data for later, equivalent requests. The advantage of adding cache constraints is that they have the potential to partially or completely eliminate some interactions, improving efficiency, scalability, and user-perceived performance by reducing the average latency of a series of interactions.


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The trade-off, however, is that a cache can decrease reliability if stale data within the cache differs significantly from the data that would have been obtained had the request been sent directly to the server. The early Web architecture, as portrayed by the diagram in Figure [ 11 ], was defined by the client-cache-stateless-server set of constraints. That is, the design rationale presented for the Web architecture prior to focused on stateless client-server interaction for the exchange of static documents over the Internet.

The protocols for communicating interactions had rudimentary support for non-shared caches, but did not constrain the interface to a consistent set of semantics for all resources. Instead, the Web relied on the use of a common client-server implementation library CERN libwww to maintain consistency across Web applications. Developers of Web implementations had already exceeded the early design. In addition to static documents, requests could identify services that dynamically generated responses, such as image-maps [Kevin Hughes] and server-side scripts [Rob McCool].

Work had also begun on intermediary components, in the form of proxies [ 79 ] and shared caches [ 59 ], but extensions to the protocols were needed in order for them to communicate reliably. The following sections describe the constraints added to the Web's architectural style in order to guide the extensions that form the modern Web architecture. The central feature that distinguishes the REST architectural style from other network-based styles is its emphasis on a uniform interface between components Figure By applying the software engineering principle of generality to the component interface, the overall system architecture is simplified and the visibility of interactions is improved.

Implementations are decoupled from the services they provide, which encourages independent evolvability. The trade-off, though, is that a uniform interface degrades efficiency, since information is transferred in a standardized form rather than one which is specific to an application's needs. The REST interface is designed to be efficient for large-grain hypermedia data transfer, optimizing for the common case of the Web, but resulting in an interface that is not optimal for other forms of architectural interaction.

In order to obtain a uniform interface, multiple architectural constraints are needed to guide the behavior of components. REST is defined by four interface constraints: identification of resources; manipulation of resources through representations; self-descriptive messages; and, hypermedia as the engine of application state.

These constraints will be discussed in Section 5.

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In order to further improve behavior for Internet-scale requirements, we add layered system constraints Figure As described in Section 3. By restricting knowledge of the system to a single layer, we place a bound on the overall system complexity and promote substrate independence. Layers can be used to encapsulate legacy services and to protect new services from legacy clients, simplifying components by moving infrequently used functionality to a shared intermediary. Intermediaries can also be used to improve system scalability by enabling load balancing of services across multiple networks and processors.

The primary disadvantage of layered systems is that they add overhead and latency to the processing of data, reducing user-perceived performance [ 32 ]. For a network-based system that supports cache constraints, this can be offset by the benefits of shared caching at intermediaries. Placing shared caches at the boundaries of an organizational domain can result in significant performance benefits [ ].

Such layers also allow security policies to be enforced on data crossing the organizational boundary, as is required by firewalls [ 79 ]. The combination of layered system and uniform interface constraints induces architectural properties similar to those of the uniform pipe-and-filter style Section 3.

Although REST interaction is two-way, the large-grain data flows of hypermedia interaction can each be processed like a data-flow network, with filter components selectively applied to the data stream in order to transform the content as it passes [ 26 ]. Within REST, intermediary components can actively transform the content of messages because the messages are self-descriptive and their semantics are visible to intermediaries. REST allows client functionality to be extended by downloading and executing code in the form of applets or scripts.

This simplifies clients by reducing the number of features required to be pre-implemented. Allowing features to be downloaded after deployment improves system extensibility. However, it also reduces visibility, and thus is only an optional constraint within REST. The notion of an optional constraint may seem like an oxymoron. However, it does have a purpose in the architectural design of a system that encompasses multiple organizational boundaries. It means that the architecture only gains the benefit and suffers the disadvantages of the optional constraints when they are known to be in effect for some realm of the overall system.

For example, if all of the client software within an organization is known to support Java applets [ 45 ], then services within that organization can be constructed such that they gain the benefit of enhanced functionality via downloadable Java classes. At the same time, however, the organization's firewall may prevent the transfer of Java applets from external sources, and thus to the rest of the Web it will appear as if those clients do not support code-on-demand.

An optional constraint allows us to design an architecture that supports the desired behavior in the general case, but with the understanding that it may be disabled within some contexts. REST consists of a set of architectural constraints chosen for the properties they induce on candidate architectures. Although each of these constraints can be considered in isolation, describing them in terms of their derivation from common architectural styles makes it easier to understand the rationale behind their selection.

Figure depicts the derivation of REST's constraints graphically in terms of the network-based architectural styles examined in Chapter 3. REST ignores the details of component implementation and protocol syntax in order to focus on the roles of components, the constraints upon their interaction with other components, and their interpretation of significant data elements. It encompasses the fundamental constraints upon components, connectors, and data that define the basis of the Web architecture, and thus the essence of its behavior as a network-based application. Unlike the distributed object style [ 31 ], where all data is encapsulated within and hidden by the processing components, the nature and state of an architecture's data elements is a key aspect of REST.

The rationale for this design can be seen in the nature of distributed hypermedia. When a link is selected, information needs to be moved from the location where it is stored to the location where it will be used by, in most cases, a human reader. This is unlike many other distributed processing paradigms [ 6 , 50 ], where it is possible, and usually more efficient, to move the "processing agent" e.

A distributed hypermedia architect has only three fundamental options: 1 render the data where it is located and send a fixed-format image to the recipient; 2 encapsulate the data with a rendering engine and send both to the recipient; or, 3 send the raw data to the recipient along with metadata that describes the data type, so that the recipient can choose their own rendering engine. Each option has its advantages and disadvantages.

Option 1, the traditional client-server style [ 31 ], allows all information about the true nature of the data to remain hidden within the sender, preventing assumptions from being made about the data structure and making client implementation easier. However, it also severely restricts the functionality of the recipient and places most of the processing load on the sender, leading to scalability problems. Option 2, the mobile object style [ 50 ], provides information hiding while enabling specialized processing of the data via its unique rendering engine, but limits the functionality of the recipient to what is anticipated within that engine and may vastly increase the amount of data transferred.

Option 3 allows the sender to remain simple and scalable while minimizing the bytes transferred, but loses the advantages of information hiding and requires that both sender and recipient understand the same data types. REST provides a hybrid of all three options by focusing on a shared understanding of data types with metadata, but limiting the scope of what is revealed to a standardized interface.

REST components communicate by transferring a representation of a resource in a format matching one of an evolving set of standard data types, selected dynamically based on the capabilities or desires of the recipient and the nature of the resource. Whether the representation is in the same format as the raw source, or is derived from the source, remains hidden behind the interface. The benefits of the mobile object style are approximated by sending a representation that consists of instructions in the standard data format of an encapsulated rendering engine e.

REST therefore gains the separation of concerns of the client-server style without the server scalability problem, allows information hiding through a generic interface to enable encapsulation and evolution of services, and provides for a diverse set of functionality through downloadable feature-engines. The key abstraction of information in REST is a resource. Any information that can be named can be a resource: a document or image, a temporal service e. In other words, any concept that might be the target of an author's hypertext reference must fit within the definition of a resource.

A resource is a conceptual mapping to a set of entities, not the entity that corresponds to the mapping at any particular point in time. More precisely, a resource R is a temporally varying membership function M R t , which for time t maps to a set of entities, or values, which are equivalent. A resource can map to the empty set, which allows references to be made to a concept before any realization of that concept exists -- a notion that was foreign to most hypertext systems prior to the Web [ 61 ].

Some resources are static in the sense that, when examined at any time after their creation, they always correspond to the same value set. Others have a high degree of variance in their value over time. The only thing that is required to be static for a resource is the semantics of the mapping, since the semantics is what distinguishes one resource from another. For example, the "authors' preferred version" of an academic paper is a mapping whose value changes over time, whereas a mapping to "the paper published in the proceedings of conference X" is static.

These are two distinct resources, even if they both map to the same value at some point in time. The distinction is necessary so that both resources can be identified and referenced independently. A similar example from software engineering is the separate identification of a version-controlled source code file when referring to the "latest revision", "revision number 1.


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This abstract definition of a resource enables key features of the Web architecture. First, it provides generality by encompassing many sources of information without artificially distinguishing them by type or implementation. Second, it allows late binding of the reference to a representation, enabling content negotiation to take place based on characteristics of the request.

The trade-off, though, is that a uniform interface degrades efficiency, since information is transferred in a standardized form rather than one which is specific to an application's needs. The REST interface is designed to be efficient for large-grain hypermedia data transfer, optimizing for the common case of the Web, but resulting in an interface that is not optimal for other forms of architectural interaction.

In order to obtain a uniform interface, multiple architectural constraints are needed to guide the behavior of components. REST is defined by four interface constraints: identification of resources; manipulation of resources through representations; self-descriptive messages; and, hypermedia as the engine of application state. These constraints will be discussed in Section 5. In order to further improve behavior for Internet-scale requirements, we add layered system constraints Figure As described in Section 3. By restricting knowledge of the system to a single layer, we place a bound on the overall system complexity and promote substrate independence.

Layers can be used to encapsulate legacy services and to protect new services from legacy clients, simplifying components by moving infrequently used functionality to a shared intermediary. Intermediaries can also be used to improve system scalability by enabling load balancing of services across multiple networks and processors. The primary disadvantage of layered systems is that they add overhead and latency to the processing of data, reducing user-perceived performance [ 32 ]. For a network-based system that supports cache constraints, this can be offset by the benefits of shared caching at intermediaries.

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Roy T. Fielding

Placing shared caches at the boundaries of an organizational domain can result in significant performance benefits [ ]. Such layers also allow security policies to be enforced on data crossing the organizational boundary, as is required by firewalls [ 79 ]. The combination of layered system and uniform interface constraints induces architectural properties similar to those of the uniform pipe-and-filter style Section 3.

Although REST interaction is two-way, the large-grain data flows of hypermedia interaction can each be processed like a data-flow network, with filter components selectively applied to the data stream in order to transform the content as it passes [ 26 ]. Within REST, intermediary components can actively transform the content of messages because the messages are self-descriptive and their semantics are visible to intermediaries.

REST allows client functionality to be extended by downloading and executing code in the form of applets or scripts. This simplifies clients by reducing the number of features required to be pre-implemented. Allowing features to be downloaded after deployment improves system extensibility. However, it also reduces visibility, and thus is only an optional constraint within REST. The notion of an optional constraint may seem like an oxymoron.

However, it does have a purpose in the architectural design of a system that encompasses multiple organizational boundaries. It means that the architecture only gains the benefit and suffers the disadvantages of the optional constraints when they are known to be in effect for some realm of the overall system. For example, if all of the client software within an organization is known to support Java applets [ 45 ], then services within that organization can be constructed such that they gain the benefit of enhanced functionality via downloadable Java classes.

At the same time, however, the organization's firewall may prevent the transfer of Java applets from external sources, and thus to the rest of the Web it will appear as if those clients do not support code-on-demand. An optional constraint allows us to design an architecture that supports the desired behavior in the general case, but with the understanding that it may be disabled within some contexts. REST consists of a set of architectural constraints chosen for the properties they induce on candidate architectures.

Although each of these constraints can be considered in isolation, describing them in terms of their derivation from common architectural styles makes it easier to understand the rationale behind their selection. Figure depicts the derivation of REST's constraints graphically in terms of the network-based architectural styles examined in Chapter 3. REST ignores the details of component implementation and protocol syntax in order to focus on the roles of components, the constraints upon their interaction with other components, and their interpretation of significant data elements.

It encompasses the fundamental constraints upon components, connectors, and data that define the basis of the Web architecture, and thus the essence of its behavior as a network-based application. Unlike the distributed object style [ 31 ], where all data is encapsulated within and hidden by the processing components, the nature and state of an architecture's data elements is a key aspect of REST. The rationale for this design can be seen in the nature of distributed hypermedia. When a link is selected, information needs to be moved from the location where it is stored to the location where it will be used by, in most cases, a human reader.

This is unlike many other distributed processing paradigms [ 6 , 50 ], where it is possible, and usually more efficient, to move the "processing agent" e. A distributed hypermedia architect has only three fundamental options: 1 render the data where it is located and send a fixed-format image to the recipient; 2 encapsulate the data with a rendering engine and send both to the recipient; or, 3 send the raw data to the recipient along with metadata that describes the data type, so that the recipient can choose their own rendering engine.

Each option has its advantages and disadvantages. Option 1, the traditional client-server style [ 31 ], allows all information about the true nature of the data to remain hidden within the sender, preventing assumptions from being made about the data structure and making client implementation easier. However, it also severely restricts the functionality of the recipient and places most of the processing load on the sender, leading to scalability problems. Option 2, the mobile object style [ 50 ], provides information hiding while enabling specialized processing of the data via its unique rendering engine, but limits the functionality of the recipient to what is anticipated within that engine and may vastly increase the amount of data transferred.

Option 3 allows the sender to remain simple and scalable while minimizing the bytes transferred, but loses the advantages of information hiding and requires that both sender and recipient understand the same data types. REST provides a hybrid of all three options by focusing on a shared understanding of data types with metadata, but limiting the scope of what is revealed to a standardized interface. REST components communicate by transferring a representation of a resource in a format matching one of an evolving set of standard data types, selected dynamically based on the capabilities or desires of the recipient and the nature of the resource.

Whether the representation is in the same format as the raw source, or is derived from the source, remains hidden behind the interface. The benefits of the mobile object style are approximated by sending a representation that consists of instructions in the standard data format of an encapsulated rendering engine e. REST therefore gains the separation of concerns of the client-server style without the server scalability problem, allows information hiding through a generic interface to enable encapsulation and evolution of services, and provides for a diverse set of functionality through downloadable feature-engines.

The key abstraction of information in REST is a resource. Any information that can be named can be a resource: a document or image, a temporal service e.

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In other words, any concept that might be the target of an author's hypertext reference must fit within the definition of a resource. A resource is a conceptual mapping to a set of entities, not the entity that corresponds to the mapping at any particular point in time. More precisely, a resource R is a temporally varying membership function M R t , which for time t maps to a set of entities, or values, which are equivalent.

A resource can map to the empty set, which allows references to be made to a concept before any realization of that concept exists -- a notion that was foreign to most hypertext systems prior to the Web [ 61 ]. Some resources are static in the sense that, when examined at any time after their creation, they always correspond to the same value set.

Others have a high degree of variance in their value over time. The only thing that is required to be static for a resource is the semantics of the mapping, since the semantics is what distinguishes one resource from another. For example, the "authors' preferred version" of an academic paper is a mapping whose value changes over time, whereas a mapping to "the paper published in the proceedings of conference X" is static.

These are two distinct resources, even if they both map to the same value at some point in time. The distinction is necessary so that both resources can be identified and referenced independently. A similar example from software engineering is the separate identification of a version-controlled source code file when referring to the "latest revision", "revision number 1.

This abstract definition of a resource enables key features of the Web architecture. First, it provides generality by encompassing many sources of information without artificially distinguishing them by type or implementation. Second, it allows late binding of the reference to a representation, enabling content negotiation to take place based on characteristics of the request. Finally, it allows an author to reference the concept rather than some singular representation of that concept, thus removing the need to change all existing links whenever the representation changes assuming the author used the right identifier.

REST uses a resource identifier to identify the particular resource involved in an interaction between components. REST connectors provide a generic interface for accessing and manipulating the value set of a resource, regardless of how the membership function is defined or the type of software that is handling the request. The naming authority that assigned the resource identifier, making it possible to reference the resource, is responsible for maintaining the semantic validity of the mapping over time i.

Traditional hypertext systems [ 61 ], which typically operate in a closed or local environment, use unique node or document identifiers that change every time the information changes, relying on link servers to maintain references separately from the content [ ]. Since centralized link servers are an anathema to the immense scale and multi-organizational domain requirements of the Web, REST relies instead on the author choosing a resource identifier that best fits the nature of the concept being identified. Naturally, the quality of an identifier is often proportional to the amount of money spent to retain its validity, which leads to broken links as ephemeral or poorly supported information moves or disappears over time.

REST components perform actions on a resource by using a representation to capture the current or intended state of that resource and transferring that representation between components. A representation is a sequence of bytes, plus representation metadata to describe those bytes. Other commonly used but less precise names for a representation include: document, file, and HTTP message entity, instance, or variant.

A representation consists of data, metadata describing the data, and, on occasion, metadata to describe the metadata usually for the purpose of verifying message integrity. Metadata is in the form of name-value pairs, where the name corresponds to a standard that defines the value's structure and semantics. Response messages may include both representation metadata and resource metadata: information about the resource that is not specific to the supplied representation.

Control data defines the purpose of a message between components, such as the action being requested or the meaning of a response. It is also used to parameterize requests and override the default behavior of some connecting elements. For example, cache behavior can be modified by control data included in the request or response message. Depending on the message control data, a given representation may indicate the current state of the requested resource, the desired state for the requested resource, or the value of some other resource, such as a representation of the input data within a client's query form, or a representation of some error condition for a response.

For example, remote authoring of a resource requires that the author send a representation to the server, thus establishing a value for that resource that can be retrieved by later requests. If the value set of a resource at a given time consists of multiple representations, content negotiation may be used to select the best representation for inclusion in a given message. The data format of a representation is known as a media type [ 48 ]. A representation can be included in a message and processed by the recipient according to the control data of the message and the nature of the media type.

Some media types are intended for automated processing, some are intended to be rendered for viewing by a user, and a few are capable of both. Likewise, a single resource can be the equivalent of a database stored procedure, with the power to abstract state changes over any number of storage items. They are not the same thing. Sometimes this manifests itself through predefined relationships between resources, specifying URI structure, or listing the possible response codes received from different resources in response to the standard 4 methods usually a combination of all those. But a second round of harping on the uniform interface — that every service has the same interface and so any service-specific interface specification only serves to increase coupling — sets them straight.

More formalization is needed. After all i still have a bad feeling of making such a claim myself. You, as a knowledgeable human being, are obviously able to decide on RESTfulness by inspecting an abstract description of the interface. Since i doubt that you are looking into a crystal ball, the following question crosses my mind: Is it possible for a machine to make such a decision? Would it be enough to pass it a sample transcript of a client server dialog?


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If that does not suffice, which other information would be necessary to decide on RESTfulness? After all programmers prefer to read code over prose. If you think it is not possible or very difficult, i would be interested why. This is essentially are more precise statement of my original interpretation, is it not? The state transitions are known a priori; the resouces on which you can perform the transitions are linked to. I still feel your answers to jdubray in 20 are unsatisfactory. The out of band communication is happening when defining the media type.

The only argument you marshall for media types in stead of fixed resources is that the media types can be shared across sites. Basically, how far ahead is the client looking? The difficulty in providing any trace criterion for REST is that what matters is how the client decides to take transitions. A client that has been pre-programmed to make a sequence of requests regardless of the response is going to produce the same network trace as one that examines each response and makes deliberate decisions based on the content. In terms of testing a specification, the hardest part is identifying when a RESTful protocol is actually dependent on out-of-band information or if the authors are just overspecifying things for the purpose of documentation.

What I look for are requirements on processing behavior that are defined outside of the media type specification. Usually, however, what they do is assume that the response has a specific structure beyond that defined by the media type. When the structure changes, the client will break. The media type identifies a specification that defines how a representation is to be processed.

That is out-of-band information all communication is dependent on some prior knowledge. What you are missing is that each representation contains the specific instructions for interfacing with a given service, provided in-band. The representation is specific to the application being performed by the agent. Each representation therefore provides the transitions that are available at that point in the application. There are plenty of examples in the linked data communities. More important to me is that the same design reflects good human-Web design, and thus we can design the protocols to support both machine and human-driven applications by following the same architectural style.

Fielding or not. So there is no need to be frustrated, people have taken the coined term and ran with it. This is how marketing will use it and so will everybody else. I wonder how the agent knows what the relationship types mean or whether this just applies if client and server have shared knowledge on the vocabulary, actually more the respective programmers. In other words, if the server introduces a new relationship type, the agent probably needs adaption, depending on its task. Do you agree? However, when I send out a message to API designers, I expect the audience to be reasonably competent in the field.

I have to talk to them as a […]. I have to admit that after reading this post, and the Roy Fielding post that inspired it, my interpretation of REST has totally been turned on its head. Both are […]. The post is worth reading for anyone who is into the REST architecture or […]. Now this must be quite hard to take and […]. I am not sure why you think that having an obscure URI format will somehow give you a secure call whatever that means.

Identifiers are public information. There are numerous examples of that in practice, and more in the future once browsers learn how to implement other authentication mechanisms. What about the usecase of a distributed queue? The queue should not care about the media types it is exchanging between senders and receivers, yet it can quite easily satisfy the addressability, uniform interface, and statelessness constraints of a RESTful architecture.

I hope I am explaining myself well. There are specific state transitions for the receiver, but why does the media type have to contain information on how to process a received message? I also think it is far easier to maintain and re-use over the long term. A distributed queue is an implementation choice. You can certainly implement some applications by having them interact with a queue-like resource in a RESTful manner.

Do you see the difference? All it needs to know is the meaning of those instructions and some idea of what it wants to do next, whether that purpose be user-driven, configuration-driven, or some sort of AI-driven. How could I explain this? Then how could they know how to handle the element with HTTP? It might be worth contrasting it with DDD, in my view similiarly complex and also looking at designing simple software with a long term viewpoint.

As with anything DDD suffers from misunderstandings and people sometimes focus too much on the unimportant aspects. Just my 2c as someone whose gradually coming to appreciate REST after many months of trying to get to grips with the great ideas behind it. In general, any protocol element that uses a URI for identification must allow any URI scheme to be used for the sake of that identification. Any effort spent describing what methods to use on what URIs of interest should be entirely defined within the scope of the processing rules for a media type and, in most cases, already defined by existing media types.

Servers must have the freedom to control their own namespace. Instead, allow servers to instruct clients on how to construct appropriate URIs, such as is done in HTML forms and URI templates, by defining those instructions within media types and link relations. Specification authors may use resource types for describing server implementation behind the interface, but those types must be irrelevant and invisible to the client. October 20, at am. Bjorg says:. Roy T. Fielding says:. BillHiggins says:. October 20, at pm. October 21, at am. TheOtherMarcus says:. October 21, at pm. Sam Ruby says:.