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September 8, 2021

Organizations globally are focusing on digital transformation since they play a crucial role in revamping businesses. The first step towards modernization involves studying the underlying business rules and logic of legacy applications thoroughly. The rapidly aging legacy technology base increases risks and is also expensive to maintain. It is difficult to diagnose and address critical issues if legacy applications are not analyzed and understood. The most compelling reasons for organizations to modernize their IT landscape is the inability of legacy systems to meet dynamic business requirements, and the fact that they lack minimal business intelligence. Nevertheless, it is important to analyze application codes and extract the buried business functionality since these help in rationalizing the organization’s legacy portfolio, enabling the understanding of dependencies among components. The valuable insights gained from this kind of an analysis can be leveraged to facilitate regular maintenance related activities. It will also aid in completely re-engineering the legacy application using modern technologies. Enterprises are keen to adopt automated solutions which make extracting and documenting the underlying business logic easy since legacy code bases are voluminous and complex, and there is an increasing dearth in the availability of skilled Subject Matter Experts (SMEs).

Technical Challenges and Solutions

Incomplete understanding of business rules will have a long-term impact and adversely affect maintenance and other support activities. Some challenges will need to be addressed to reap maximum benefits from the automated solution and these include a complete understanding of the business functionality built into the legacy applications. The challenges are as follows:

  • Presence of dead code: Unused or archived code in the code inventory is a burden on the memory and affects computational efficiency, so it needs to be identified and filtered out.
  • Missing sub-components: Due to security constraints, some dependent sub-components in the codebase are not directly included in the master code repository and must be identified and fetched from their respective libraries.
  • Syntax variations: Code with compiler-specific syntaxes can lead to conflicts, so there should be an automated solution that can customize and handle the variations in syntaxes.
  • Server responsiveness issues: Analyzing large systems with multi-million lines of codes across numerous applications can cause responsiveness and synchronization issues, especially when team members analyze the system simultaneously. Grouping the applications logically in separate workspaces can help in access control and better maintainability.
  • Inventory Segregation: The various application programs will need to be split based on their naming convention and their corresponding reusable components will need to be identified and referenced for better code maintenance.

Benefits of an Automated Approach

Analyzing applications to discover the transactional flow and the relationship of interdependent components can help organizations effectively manage and maintain their IT portfolio, increasing their chances of executing critical projects successfully without disrupting business operations. However, the sheer volume and complexity of legacy application codebases make manual implementation tedious and error prone. Automated product-based approach will help in generating the complete documentation of the application in the least possible amount of time, bringing down the total cost of ownership. The benefits have been mentioned below:

  • Instant customized reports: Cognitive insights generated from the analysis of the source code will be available in the repository. Hence, most custom report requirements can be fulfilled through an interactive User Interface (UI). It will not be necessary, for SMEs to manually analyze the source code.
  • Savings on effort: The insights available in the repository will significantly reduce the effort of the support team for day-to-day incident resolution.
  • Reduced turn-around time: In case of extensive, cross-application change requests, co-ordination between several application teams for impact analysis is time consuming. Such inter-team dependencies can be minimized significantly through automation, thereby reducing the total turn-around time.
  • Minimized manual intervention: Reports generated through automation helps minimize manual intervention, averting the risk of missing critical components or statements.
  • Simplified simultaneous user access: Hosting the automated solution on cloud in the client’s intranet eases simultaneous access by multiple users in the client network, by enabling logging in through web browsers.

Paving the Path towards Digital Transformation

The insights gained by scanning the source code should be updated periodically with the latest versions. The insights stored in the repository can be synced automatically, and new reports can be generated afresh as and when required. The extracted insights from the codebase can serve as the base for organizations seeking to modernize their legacy applications. A comprehensive knowledge repository built though automation can be used to build applications in the target modern technology, in alignment with business goals.

To know more about cognitive code analysis solution for your legacy applications, contact us at mastercraft.sales@tcs.com.

Alpana Shah is an Analyst for TCS MasterCraft™ TransformPlus, which is an intelligent automation product for deciphering legacy applications to modernize and migrate to cloud. With over 7.5 years of industry experience, she has managed the deployment and implementation of TCS MasterCraft™ TransformPlus in a wide variety of modernization projects, comprising more than 100 million lines of legacy code across various technologies. She holds a B.Tech degree in Information Technology from West Bengal University of Technology.

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