Improving Product Quality throughout the Software Development Lifecycle
Good, efficient communication is an important asset to the team. The pattern language MetaAutomation shows how to achieve this over the short and long term.
Imagine a test/QA team that creates a quality data store for the whole team with these properties:
- Compact records
- Validated data structures
- Performance data in line with check steps and results
- Check steps marked pass, fail, or blocked
For example, from an intranet site, any team member can query and do analysis directly on the data store. The pure, structured data shows exactly what checks were run and when, and how long each executed step took in milliseconds, as well as the check as a whole, even if the check itself was distributed for multi-tier steps or verifications in the check.
This level of quality detail starts when the system is up and running, and it extends throughout the software development lifecycle or through all iterations, depending on the process the team uses to develop and ship their product. Because the check steps are self-documenting, the steps laid out in the check artifact are as stable as the code that runs the check.
With focused, pure, and structured data on product quality, including all of the self-documenting steps of a given check, it’s clearly known what’s working and what the verifications are. Trust and communication are greatly improved, both among geographically distributed teams and among the test/QA team, developers, program managers, and leadership.
The quality of the company’s software assets, i.e., the product under development, is clearly expressed in great detail. This helps with Sarbanes-Oxley compliance as well, so the managers and investors are happy. And the test/QA team gets the exposure and respect it deserves.
Successes and failures in the business requirements of the product are archived in great detail over time, so improvement in quality in the product is evident. Product owners and leaders have a powerful asset to help them manage risk, and they know that failures in core behaviors of the product are fixed quickly, both in theory and in practice. It’s all there in the quality record.
By addressing the business value of programmatically driven verifications of software product quality, MetaAutomation radically increases the value of the quality role to the business.