Detection of SOA Patterns

Abstract

The rapid increase of communications combined with the deployment of large scale information systems lead to the democratization of Service Oriented Architectures (SOA). However, systems based on these architectures (called SOA systems) evolve rapidly due to the addition of new functionalities, the modification of execution contexts and the integration of legacy systems. This evolution may hinder the maintenance of these systems, and thus increase the cost of their development. To ease the evolution and maintenance of SOA systems, they should satisfy good design quality criteria, possibly expressed using patterns. By patterns, we mean good practices to solve known and common problems when designing software systems. The goal of this study is to detect patterns in SOA systems to assess their design and their Quality of Service (QoS). We propose a three steps approach called SODOP (Service Oriented Detection Of Patterns), which is based on our previous work for the detection of antipatterns. As a first step, we define five SOA patterns extracted from the literature. We specify these patterns using "rule cards", which are sets of rules that combine various metrics, static or dynamic, using a formal grammar. The second step consists in generating automatically detection algorithms from rule cards. The last step consists in applying concretely these algorithms to detect patterns on SOA systems at runtime. We validate SODOP on two SOA systems: Home-Automation and FraSCAti that contain respectively 13 and 91 services. This validation demonstrates that our proposed approach is precise and efficient.

A Lightweight Approach for Specification and Detection of SOAP Anti-Patterns

“…Upadhyaya et al [39] presented an approach to detect 9 SOA patterns. Demange et al [40] presented an approach to detect five SOA patterns from two SOA based systems. It is revealed through the review of literature that the research on Service Oriented Architecture still needs to be explored.…”

Service Decoupler

“…Contribution. To overcome the limitations of the state-of-the-art, we are inspired by the classical façade pattern [Gamma et al 1994] and its service version [Erl 2009;Demange et al 2013]. The general idea of the classical façade is to offer a unified API for a set of software components.…”

Detection of REST Patterns and Antipatterns: A Heuristics-Based Approach

“…A few contributions are available on the detection of SOA (anti)patterns for various SOA standards, e.g., SCA (Service Component Architecture) [3,[9][10][11] and Web services [13]. To the best of our knowledge, the detection of REST (anti)patterns, in the literature deserves yet to receive attention.…”

“…Despite the presence of several technologyspecific approaches in SCA (Service Component Architecture) and Web services (e.g., [3,[9][10][11]13]), they are not applicable for detecting (anti)patterns in REST. Indeed, the key differences between REST architecture and other SOA standards prevents the application of these approaches because: (1) traditional serviceorientation is operations-centric, whereas REST is resources-centric, (2) RESTful services are on top of JSON (or XML) over HTTP, whereas traditional Web services are on top of SOAP over HTTP or JMS (Java Message Service), (3) Web services use WSDL (Web Service Definition Language) as their formal contracts; REST has no standardised contract except the human-readable documentations, (4) traditional services are the set of self-contained software artefacts where operations are denoted using verbs; resources in REST are denoted by nouns and are directlyaccessible objects via URIs, and (5) REST clients use the standard HTTP methods to interact with resources; Web services clients implement separate client-stubs to consume services.…”

“…Anti(patterns) might be introduced even in the early design phase of RESTful systems. Antipatterns in RESTful systems not only degrade their design but also make their maintenance and evolution difficult, whereas design patterns facilitate them [3,5,6].…”