Aligning technology and business: Applying patterns for legacy transformation

Abstract

Two key goals for aligning technology and business are to increase an organization's ability to change rapidly and to reduce the costs of technology. While many efforts are underway to improve application development, less emphasis has been placed on addressing key challenges posed by existing applications that resist rapid change. In this paper, we discuss techniques for accelerating change to legacy systems and for streamlining an application portfolio. Our approach takes business-driven application requirements, links them to analysis of an application portfolio, and identifies potential sequences of transformations to realize the targeted improvements. This paper describes our approach for mapping business requirements to application software, for using patterns to help translate business requirements to software requirements, and for using patterns to translate software requirements into potential solution designs. The paper describes how these techniques are applied to two stages of the software life cycle-initial analysis and detailed analysis-and summarizes experience gained from projects working with IBM clients.

Identifying services from legacy batch applications

“…Note that one of the candidate services computed by the algorithm, namely service 8, has no meaningful description and is, therefore, an undesirable service. Rows 1,5,7,12,14,15,and 17 show the ideal services from the programmer's perspective, whereas the other services (except the one in row 8) are variants of these ideal services.…”

“…Hess [12] proposes an approach for categorizing entire programs (not statements) within a batch application based on the systemlevel idioms and relationships they participate in. Structural transformations of batch applications are also discussed.…”

Upper-level Ontologies for Health Information Systems

“…In complementary fashion, Massingill [27] and Massingill et al [28] describe design patterns for parallel programming in computer science and Tambouratzis and Tambouratzis [46] identify patterns in neural networks. Patterns, too, are recognized as a useful way to capture lessons learned and to disseminate and apply practices that have proven successful [22]. According to Gamma et al [15], a pattern "is a solution to a problem in context".…”

Leveraging Artificial Intelligence–enabled Workflow Framework for Legacy Transformation

“…Digital transformation places special emphasis on legacy transformation as one of the cornerstones of successful transformation strategies [6]. While legacy transformation and modernization processes can be lengthy and costly as mentioned earlier, they can offer long term cost savings, increased efficiency, better resource utilization and the ability to adapt to the dynamic business needs of any given enterprise [7]. Therefore, enterprises need an optimal transformation approach that will enable them to part with legacy systems and take advantage of the possibilities offered by modern webbased technologies [8].…”