Authors:
Wanderley Augusto Radaelli Junior
;
Gleison Samuel do Nascimento
and
Cirano Iochpe
Affiliation:
Informatics Institute and Federal University of Rio Grande do Sul, Brazil
Keyword(s):
Legacy systems modernization, Reverse engineering, Business process, Business rules, Source code manipulation, Execution logs mining.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Process Management
;
Data Engineering
;
e-Business
;
Engineering Information System
;
Enterprise Engineering
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Society, e-Business and e-Government
;
Software Engineering
;
Symbolic Systems
;
Tools, Techniques and Methodologies for System Development
;
Web Information Systems and Technologies
Abstract:
Computer systems implement business processes from different organizations. Among the currently operating computer systems, much of it is classified as legacy system. Typically, legacy systems are complex applications that are still active, due to the high cost of modernization and a high degree of criticality. In recent years, were published several works addressing the importance of legacy systems modernization, emphasizing the extraction of the business process model implemented in these systems. Within this context, a key step is to extract knowledge from source code and / or systems execution logs, aiming to use this information in reverse engineering processes. In this work are presented and analyzed methods based on source code manipulation and system’s execution logs mining, which can be used to extract knowledge from legacy systems, prioritizing business rules identification. A comparison between the two different approaches is presented, as well as their positive and negati
ve characteristics. Our results include a list of desired features and a proposal of a method for legacy systems reverse engineering and business rules identification.
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