In this paper, an approach for information systems reverse engineering is proposed and applied. The aim is to support a unified perspective to the reverse engineering process of both data and software. At the state of the art, indeed, many methods, techniques, and tools for software reverse engineering have been proposed to support program comprehension, software maintenance, and software evolution. Other approaches and tools have been proposed for data reverse engineering, with the aim, for example, to provide complete and up-to-date documentation of legacy databases. However, the two engineering communities often worked independently, and very few approaches addressed the reverse engineering of both data and software as information system's constituencies. Hence, a higher integration is needed to support a better co-evolution of databases and programs, in an environment often characterized by high availability of data and volatility of information flows. Accordingly, the approach we propose leverages the detection of object-relational mapping design patterns to build a conceptual schema of the software under analysis. Then, the conceptual schema is mapped to the domain model of the system, to support the design of the evolution of the information system itself. The approach is evaluated on two large-scale open-source enterprise applications.

Abstract-Software dependencies play a vital role in program comprehension, change impact analysis and other software maintenance activities. Traditionally, these activities are supported by source code analysis; however, the source code is sometimes inaccessible, and not all stakeholders have adequate knowledge to perform such analysis. For example, non-technical domain experts and consultants raise most maintenance requests; however, they cannot predict the cost and impact of the requested changes without the support of the developers.We propose a novel approach to predict software dependencies by exploiting coupling present in domain-level information. Our approach is independent of the software implementation; hence, it can be used to evaluate architectural dependencies without access to the source code or the database.We evaluate our approach with a case study on a large-scale enterprise system, in which we demonstrate how up to 68% of the source code dependencies and 77% of the database dependencies are predicted solely based on domain information.

SUMMARYReuse in object-oriented languages typically focuses on inheritance. Numerous techniques have been developed to provide finer-grained reuse of methods, such as flavors, mixins, and traits. These techniques, however, only deal with reuse at the level of classes. Class-based reuse is inherently static. Increasing use of reflection and meta-programming techniques in real-world applications underlines the need for more dynamic approaches. New approaches have shifted to object-specific reuse. However, these techniques fail to provide a complete solution to the composition issues arising during reuse. We propose a new approach that deals with reuse at the object level and that supports behavioral and state composition. We introduce a new abstraction called a talent that models features that are shared between objects of different class hierarchies. Talents provide a composition mechanism that is as flexible as that of traits but that is dynamic. Copyright

Abstract-Java Enterprise Applications (JEAs) are large systems that integrate multiple technologies and programming languages. Transactions in JEAs simplify the development of code that deals with failure recovery and multi-user coordination by guaranteeing atomicity of sets of operations. The heterogeneous nature of JEAs, however, can obfuscate conceptual errors in the application code, and in particular can hide incorrect declarations of transaction scope. In this paper we present a technique to expose and analyze the application transaction scope in JEAs by merging and analyzing information from multiple sources. We also present several novel visualizations that aid in the analysis of transaction scope by highlighting anomalies in the specification of transactions and violations of architectural constraints. We have validated our approach on two versions of a large commercial case study.

Abstract-Java Enterprise Applications (JEAs) are large systems that integrate multiple technologies and programming languages. With the purpose to support the analysis of JEAs we have developed MooseJEE an extension of the Moose environment capable to model the typical elements of JEAs.