Levering object-oriented knowledge for service-oriented proficiency

As more and more enterprise systems endeavour to interconnect seamlessly by using a service-oriented architecture (SOA) a number of challenges are beginning to surface as a result of the differences in understanding between object-orientated programming (OOP) and service-orientation in technical development teams. These differences are thus explored to determine the potential of subsidising gaps in knowledge through relational learning in order to better prepare development environments for service migration. It emerges that the principles of service-oriented programming can be used within OOP by selectively identifying the existing knowledge found within object-orientation and traditional programming methodologies. The benefit of this approach proposes to lever the expertise of object-oriented developers so as to build service-ready computer software and encourage the seamlessness of SOA

Rule-based quality heuristics formalization and identification

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Reengineering of Legacy Systems to Distributed Environments.

The object-oriented paradigm and client/server and distributed technologies have become widely used in the last decade. There is an increasing interest to migrate and reengineer legacy systems to these new hardware technologies and software development paradigms. Software engineers who wish to reengineer such legacy systems face challenges, such as lack of documentation and programs that are difficult to comprehend. Middleware technologies such as CORBA and DCOM make the development of new distributed systems, as well as the migration of legacy systems to distributed platforms, more feasible. Distribution of a system consists of two parts: (1) subsystem decomposition and (2) allocation of the subsystems to different sites. In this research, we define a reengineering environment that assists with the migration of legacy systems to distributed environments. We define a reengineering methodology that uses reverse engineering, software metrics, clustering, and data mining to migrate legacy systems to object-based distributed environments. The reengineering environment includes the methodology and an integrated set of tools that support the implementation of the methodology. The methodology consists of multiple phases. First, we use reverse engineering techniques for program comprehension and design recovery. We then decompose the system into a hierarchy of subsystems by defining relationships between the entities of the underlying paradigm of the legacy system. The decomposition is driven by data mining, software metrics, and clustering techniques. Next, if the underlying paradigm of the legacy system is not object-based, we perform object-based adaptations on the subsystems. We then create components by wrapping objects and defining an interface. Finally, we allocate components to different sites by specifying the requirements of the system and characteristics of the network as an integer-programming model that minimizes the remote communication. We use middleware technologies for the implementation of the distributed object system

Exploiting Design Heuristics for Automatic Problem Detection

Reengineering large systems requires support for detecting design problems automatically. A lot of rules and guidelines about good design can be found in the literature. Since these were originally intented to be used by human developers, it was not sure if they were suitable to be automated. We present our approach to formalize these rules, extract design information from legacy source code and to search for violations of these rules automatically by using our reengineering tool set Goose. It turnes out that a large fraction of these guidelines for good design can be formalized and are thus applicable for automatic detection. Different relations between guidelines support a selection of the most useful guidelines. 1 Introduction Reengineering object-oriented systems requires the detection of problems in their design which prohibit further enhancements to the system. A design problem is a fragment of the structure of a program which makes the program inflexible with respect t..