Understanding Legacy Systems in the Light of Grounded Theory

  • Alex Severo Chervenski UNIPAMPA
  • Andréa Sabedra Bordin UNIPAMPA


Software systems developed over a long period of time require constant maintenance to remain useful to organizations. These systems, which tend to degrade and cause maintenance problems, are usually called legacy systems. The management of legacy systems involves understanding its characteristics, such as what it is, what problems it presents and which evolution strategies. From the literature perspective, there is a wide and diversified understanding of these characteristics. This article is intended to provide a more concise understanding of such features related to legacy systems. To achieve this goal, textual excerpts from the literature were collected and analyzed according to Grounded Theory (GT) procedures, resulting in a concise understanding supported by visual models. The results show that systems developed with obsolete technologies, some decades ago, that have incomplete or missing documentation, among others, are defining characteristics for a system to be considered legacy. Some characteristics cause financial problems, difficulty in maintaining the code, among others. It was also observed that there are several evolution strategies and that migration of legacies to the platform is a trend. It is hoped that this study will serve as support for the identification of elements that indicate whether a system is or is becoming a legacy, as well as the possible solutions to evolve them. In addition, the detailed data analysis process with GT procedures, which used a collaborative coding process with a tool developed for this purpose, can support researchers who need to use this type of method in their research in various areas of knowledge.
Palavras-chave: Software Evolution, Legacy Systems, Software Maintenance, Grounded Theory
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CHERVENSKI, Alex Severo; BORDIN, Andréa Sabedra. Understanding Legacy Systems in the Light of Grounded Theory. In: SIMPÓSIO BRASILEIRO DE ENGENHARIA DE SOFTWARE (SBES), 34. , 2020, Natal. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2020 .