2Cuerpo Académico Tecnología Educativa I+D+i, Facultad de Informática Mazatlán, Universidad Autónoma de Sinaloa, Mazatlán, Sinaloa, Mexico
3Departamento de Ingeniería en Computación e Informática, Facultad de Ingeniería, Universidad de Tarapacá, Arica, Chile
4Facultad de Informática Mazatlán, Universidad Autónoma de Sinaloa, Mazatlán, Sinaloa, Mexico
The data is available at Figshare: Aguilar-Calderón, Jose Alfonso (2021): Data Set for Systematic Mapping Study. figshare. Dataset. DOI 10.6084/m9.figshare.14888217.v2.
Integration of legacy and third-party software systems is almost mandatory for enterprises. This fact is based mainly on exchanging information with other entities (banks, suppliers, customers, partners, etc.). That is why it is necessary to guarantee the integrity of the data and keep these integration’s up-to-date due to the different global business changes is facing today to reduce the risk in transactions and avoid losing information. This article presents a Systematic Mapping Study (SMS) about integrating software units at the component level. Systematic mapping is a methodology that has been widely used in medical research and has recently begun to be used in Software Engineering to classify and structure the research results that have been published to know the advances in a topic and identify research gaps. This work aims to organize the existing evidence in the current scientific literature on integrating software units for external and data loose coupling. This information can establish lines of research and work that must be addressed to improve the integration of low-level systems.
Enterprises are typically made up of hundreds of home-made (in-house development) applications, purchased from third parties, legacy systems, or a combination of all of them, operating in multiple layers on different operating systems. Currently, the integration of systems acquired from third parties and legacies has become a major concern in companies. As a result, most of the applications used in the enterprise are heterogeneous, autonomous, and operate in a distributed environment. Heterogeneity has been considered one of the most severe problems to solve because it tends to cause interoperability problems. In particular, semantic conflicts, which occur when applications use different meanings for the same information item. The challenges are integration is not an easy job; the real challenges are made up of several business and technical issues (Hohpe & Woolf, 2004).