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From Static to Agile Documentation: How the Latest Advances Can Save You Time and Sanity

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Software application documentation has long been passed over as a tedious and time consuming task. Spending hours noting every change and how those changes affect the rest of the application or other applications means less time spent on innovative work. However, the benefits of having and updating this documentation are well-known including helping to train personnel, debugging etc. And when it comes to legacy applications, documentation becomes even more essential to avoid knowledge transfer loss and to serve as a foundation for successful modernization efforts. Given the importance of this work, how can organizations ensure they reap the benefits without feeling like they’re stuck in a never-ending battle to keep the documentation up to date? 

AI powered tools exist today that reduce time spent and improve the quality of documentation

Automated & AI powered reverse engineering tools have existed on the market for quite some time. Organizations have found ways to use algorithms to extract information about logic, dependencies, and more from an application and then display that information in a variety of formats. This allows IT teams and their counterparts to develop a deep understanding of their applications. These technical documentation software and tools heavily reduce the amount of time needed to create documentation, which is particularly helpful for legacy applications where no current documentation may exist. For example, EvolveWare’s Intellisys platform has documentation & analysis capabilities that automate 100% of metadata extraction and reduce the time and effort in generating this documentation by at least 90% as compared to traditional methods. 

This automation also mitigates the risk of doing this work manually. Pouring over thousands if not millions of lines of code frequently written in multiple programming languages is prone to missing information and unnecessary mistakes. In fact in a survey we commissioned last year on the state of application modernization, we found that while 41% of respondents were very confident about their understanding of their legacy applications prior to starting a modernization project, that percentage dropped to just 28% for respondents that had already started a project. This indicates that gaps in their knowledge surfaced while performing modernization work, typically resulting in costly delays or project pivots. 

Moving from static documentation to agile documentation

Now that’s all well and good in terms of getting to a starting point, but then what? Developers will continue to make changes to these applications as regulations, environmental conditions, or business policies change. That means that the documentation generated at one point will quickly become out of date. 

Well, today we have the ability to continuously update that documentation with the Intellisys platform. While organizations always had the option of refreshing their documentation by re-processing their source code through a tool, they would only see the new documentation and had no visibility into where changes occurred or what those exact changes were. Having that visibility is particularly important when working on a modernization project that  takes place over a couple of years and modernization work is occurring concurrently with changes made to the existing production version of the application. In order to make sure the modernization team doesn’t have to go over work they’ve already done and potentially lose sight of important updates that need to be incorporated into a new application, highlighting the details around these updates is important. The Intellisys platform’s agile documentation capabilities do just that, generating reports to showcase the impact of changes made to the application. This further mitigates modernization risks and ensures successful transformations. 

Advances in AI technology will only continue to facilitate documentation upkeep

Agile documentation is the current “state-of-the-art” technology for automated documentation generation and maintenance. But with the advent and eventual maturation of technologies such as Generative AI, these processes could become even more seamless and require less manual intervention. The journey to get there will require access to large amounts of legacy code to train the large language models (LLMs) that power these advances. But with that access, organizations could theoretically take advantage of models that can explain code in plain English and update documentation in a fraction of the time currently required. The promise of that future is bright, but organizations who need to move off of their legacy applications sooner rather than later have more than enough intelligent automation at their disposal to start the process now.

 

To learn more about Intellisys’ agile documentation capabilities, click here or contact us with any questions you may have.

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