Change is the law of life. However, in the field of software development, what we call a change, has always had people worried, at one point or the other. In the yesteryears, when Waterfall development was the norm, software development vendors had to form change management boards to deal with frequently changing client requirements. As these change management processes became more mature and elaborate, clients became either more adversarial or afraid of asking for a change. The end result – the time to market didn’t improve significantly, and matching clients’ expectations remained as tricky an endeavor, as it was earlier.

Thankfully, most organizations have now shifted from Waterfall to Agile software development and DevOps. These new methodologies have made people on all sides embrace changes with an open heart; at least, that’s the premise. However, changes can still get tricky.

Today, the software has become a living entity, always growing and evolving with numerous feature additions, bug fixes, and so on. With continuous integration and continuous delivery (CI/CD) processes, organizations are able to make quicker and more frequent releases. In larger projects with geographically dispersed teams, there are often multiple developers committing their code to the code repository in different time zones. Though there are many tools to manage projects, in distributed environments, code conflicts aren’t rare. While the shift-left approach with automated testing has reduced such conflicts, certain issues may still skip the test scope. In worst cases, a change introduced to the master branch can affect other features or lead to application downtime. This is why impact analysis is important in software testing.

What is Impact Analysis in Software Testing?

Risk impact analysis or Impact analysis refers to the analysis of the impact of changes intended to be introduced to the application. It’s not a new concept; when developers write code, they are expected to consider the impact of their code changes on existing features and product functionalities. They write unit tests to ensure that their code isn’t leading to any problems. Further, impact analysis can help teams to determine if they need to expand the test scope or write new test cases and assess the effort involved in the testing process.

Importance of Impact Analysis

It is seen that product managers employ a range of tools and techniques to release new features safely. Canary deployment, feature flagging, and rollover mechanisms can significantly reduce ‘release anxiety’ for product managers. However, most of these techniques help only to mitigate the damage. On the other hand, business impact analysis techniques can help managers assess all changes and plan better to reduce the chances of failure. Product managers and other business stakeholders who wish to be on top of their software development cycles can use impact analysis documents or reports to gauge potential risks. With modern change impact analysis and predictive delivery tools, they can estimate the costs (resource, time, effort) involved with every change and decide if and when to implement a change.

How to Conduct Impact Analysis?

Many times developers and QA teams lack visibility into the entire software development chain, which can lead to oversights. They can fail to identify the impact of their code changes across all associated features. This is where the Requirements Traceability Matrix (RTM) may offer a way forward. However, in large projects maintaining and updating RTMs over a period can become cumbersome. Thankfully, there are advanced tools that can help keep the RTM updated with automation and simplify compliance verification and impact analysis.

It is also important to note here that the ecosystem of DevOps and ALM tools is getting complicated every year. A dedicated tool or in house solution for RTM automation can be a big help; however, it will only add to the complexity in the long run. As organizations become more agile, many of them are able to do away with RTM documentation completely. On the other hand, some organizations would want to retain RTM for compliance. There’s a common way forward with intelligent application development platforms.

Such platforms can enable bidirectional traceability, which means one can track a change request or requirement to the associated test case and vice-versa. They help in assessing test scope vis-a-vis code changes for quicker code impact analysis. Further, a big advantage offered by rapid application development platforms like Klera is that they can integrate with your existing ecosystem of tools and processes, without any requirement to code. You can use pre-built intelligent bi-directional connectors in Klera to connect with Jira, BitBucket, SonarQube, and more.

As data becomes the new gold, DevOps and ALM teams need to leverage intelligent platforms that can collect data from all tools and sources within a project, providing a single pane of glass to monitor and analyze the application development lifecycle, end to end.