We have found many programming problems for which neither procedural nor object-oriented programming techniques are sufficient to clearly capture some of the important design decisions the program must implement. This forces the implementation of those design decisions to be scattered throughout the code, resulting in “tangled” code that is excessively difficult to develop and maintain. We present an analysis of why certain design decisions have been so difficult to clearly capture in actual code. We call the properties these decisions address aspects, and show that the reason they have been hard to capture is that they cross-cut the system's basic functionality. We present the basis for a new programming technique, called aspect-oriented programming, that makes it possible to clearly express programs involving such aspects, including appropriate isolation, composition and reuse of the aspect code. The discussion is rooted in systems we have built using aspect-oriented programming.

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Aspect-Oriented Programming

Aspect-oriented programming (AOP) is a technique for improving separation of concerns in software design and implementation. AOP works by providing explicit mechanisms for capturing the structure of crosscutting concerns. This tutorial shows how to use AOP to implement crosscutting conerns in a concise modular way. It works with AspectJ, a seamless aspect-oriented extension to the Java(tm) programming language, and with AspectC, an aspect-oriented extension to C in the style of AspectJ. It also includes a description of their underlying model, in terms of which a wide range of AOP languages can be understood.

Aspect-oriented programming

Aspect] is a simple and practical aspect-oriented extension to Java With just a few new constructs, AspectJ provides support for modular implementation of a range of crosscutting concerns. In AspectJ's dynamic join point model, join points are well-defined points in the execution of the program; pointcuts are collections of join points; advice are special method-like constructs that can be attached to pointcuts; and aspects are modular units of crosscutting implementation, comprising pointcuts, advice, and ordinary Java member declarations. AspectJ code is compiled into standard Java bytecode. Simple extensions to existing Java development environments make it possible to browse the crosscutting structure of aspects in the same kind of way as one browses the inheritance structure of classes. Several examples show that AspectJ is powerful, and that programs written using it are easy to understand.

An overview of AspectJ

CORBA is a commercial standard for distributed object computing which shows great promise in the development of distributed programs. Its interface description language (IDL) enables objects to be developed independently of the underlying programming language, operating system, or computer architecture on which they will execute. While this is sufficient in many environments, programs deployed in a wide-area distributed system encounter conditions which are much more hostile and varying than those operating in a single address space or within a single local area network. In this paper we discuss four major problems we have observed in our developing and deploying wide-area distributed object applications and middleware. First, most programs are developed ignoring the variable wide area conditions. Second, when application programmers do try to handle these conditions, they have great difficulty because these harsh conditions are different from those of the local objects they are used to dealing with. Third, IDL hides information about the tradeoffs any implementation of an object must make. Fourth, there is presently no way to systematically reuse current technology components which deal with these conditions, so code sharing becomes impractical. In this paper we also describe our architecture, Quality of Service for CORBA Objects (QuO), which we have developed to overcome these limitations and integrate their solution by providing QoS abstractions to CORBA objects. First, it makes these conditions first class entities and integrates knowledge of them over time, space, and source. Second, it reduces their variance by masking. Third, it exposes key design decisions of an object's implementation and how it will be used. Fourth, it supports reuse of various architectural components and automatically generates others. © 1997 John Wiley & Sons, Inc.

Architectural support for quality of service for CORBA objects

There is provided a method of determining latency in a remote network element of a telecommunications network. In one embodiment, the method comprises receiving a message at a network element, the message comprising a time stamp of the time at which it was sent from a source network element. On receiving the message, the network element obtains another time stamp, and so may determine the time for the message to be sent between the network elements. In further embodiments, a source network element may gain an implicit indication of the workload of the remote network element by sending a first message to the remote network element and determining a length of time before the remote network element sends a second message back to the source network element.

Method and arrangement in a telecommunication system

Object-oriented programs are easier to extend than programs which are not written in an object-oriented style, but object-oriented programs are still very rigid and hard to adapt and maintain. In this article, we introduce adaptive object-oriented programming as an extension to conventional object-oriented programming. Adaptive object-oriented programming facilitates expressing the elements-classes and methods-that are essential to an application by avoiding to make a commitment on the particular class structure of the application. Adaptive programs are speciied using propagation patterns which specify sets of related constraints on class structures. An adaptive program denotes an entire family of programs, as many programs as there are class structures which satisfy its constraints. A class structure which satisses the constraints of an adaptive program is said to customize the program. Adaptive programming, realized by the use of propagation patterns, ooers a new paradigm, extending the object-oriented paradigm by lifting programming to a higher level of abstraction.

Adaptive object-oriented programming using graph-based customization

Various embodiments predict performance of a system including a plurality of server tiers. In one embodiment, a first set of performance information is collected for a base allocation of computing resources across multiple server tiers in the plurality of sever tiers for a set of workloads. A set of experimental allocations of the computing resources is generated on a tier-by-tier basis. Each of the set of experimental allocations varies the computing resources allocated by the base allocation for a single server tier of the multiple server tiers. A second set of performance information associated with the single server tier for each of the set of experimental allocations is collected for a plurality of workloads. At least one performance characteristic of at least one candidate allocation of computing resources across the multiple server tiers is predicted for a given workload based on the first and second sets of performance information.

Prediction-based provisioning planning for cloud environments

In service-oriented computing, multiple services often exist to perform similar functions. In these situations, it is essential to have good ways for qualitatively ranking the services. In this paper, we present a new ranking method, ServiceRank, which considers quality of service aspects (such as response time and availability) as well as social perspectives of services (such as how they invoke each other via service composition). With this new ranking method, a service which provides good quality of service and is invoked more frequently by others is more trusted by the community and will be assigned a higher rank. ServiceRank has been implemented on SOAlive, a platform for creating and managing services and situational applications. We present experimental results which show noticeable differences between the quality of service of commonly used mapping services on the Web. We also demonstrate properties of ServiceRank by simulated experiments and analyze its performance on SOAlive.

https://researcher.watson.ibm.com/researcher/files/us-aruni/ICSOC2009.pdf

Combining Quality of Service and Social Information for Ranking Services

A method, system, and computer program for delivering messages and data to competing consumers. One aspect of the invention includes a message delivery system including a destination messaging engine, one or more receiver messaging engines, and a message pool. The destination messaging engine is configured to distribute data from one or more producers. The receiver messaging engines are configured to request data from the destination messaging engine and transmit the data to one or more consumers. The message pool is configured to store data from the producers, with the destination messaging engine arbitrating data in the message pool among the receiver messaging engines.

Mechanism for delivering messages to competing consumers in a point-to-point system

Service network analysis is an essential aspect of web service discovery, search, mining and recommendation. Many popular web service networks are content-rich in terms of heterogeneous types of entities, attributes and links. A main challenge for ranking services is how to incorporate multiple complex and heterogeneous factors, such as service attributes, relationships between services, relationships between services and service providers or service consumers, into the design of service ranking functions. In this paper, we model services, attributes, and the associated entities, such as providers, consumers, by a heterogeneous service network. We propose a unified neighborhood random walk distance measure, which integrates various types of links and vertex attributes by a local optimal weight assignment. Based on this unified distance measure, a reinforcement algorithm, ServiceRank, is provided to tightly integrate ranking and clustering by mutually and simultaneously enhancing each other such that the performance of both can be improved. An additional clustering matching strategy is proposed to efficiently align clusters from different types of objects. Our extensive evaluation on both synthetic and real service networks demonstrates the effectiveness of ServiceRank in terms of the quality of both clustering and ranking among multiple types of entity, link and attribute similarities in a service network.

https://www.cc.gatech.edu/~lingliu/papers/2013/ServiceRank.pdf

Ignacio Silva-Lepe

Papers

Adaptive object-oriented programming using graph-based customization

Prediction-based provisioning planning for cloud environments

Combining Quality of Service and Social Information for Ranking Services

Mechanism for delivering messages to competing consumers in a point-to-point system

Ranking Services by Service Network Structure and Service Attributes