TMAP describes 20 topics in two groups, the organizing topics (aimed at orchestrating, planning, preparing and controlling, usually for multiple teams) and the performing topics (aimed at operational quality engineering activities, usually within the scope of a team).
In the below table we will mention at least one possible use of GenAI per topic. Keep in mind that many more possibilities do exist.
| Organizing Topic | |
|---|---|
| Quality & Test Policy | For documenting a Quality & Test Policy nine different subjects have to be elaborated upon. GenAI can for example support in analyzing the mission and vision of the organization and based on those, generate the description for the subjects of the policy. |
| Responsibilities & Roles | GenAI can advise regarding balanced roles and responsibilities within a team, and identify missing roles or responsibilities. Based on team skills and project scope, AI can suggest a balanced role distribution to increase team effectiveness. |
| Monitoring & Control | GenAI can analyze data coming from monitoring activities. Based on predictive analysis (also known as forecasting), it can trigger control actions automatically, for example to mitigate risks before they turn into failures or to optimize performance. GenAI can also generate monitoring scripts and support in implementing a monitoring, contributing to faster and less time consuming monitoring mechanisms. |
| Anomaly Management | GenAI can support Root Cause Analysis by automatically classifying and prioritizing anomalies. Also it can analyze large numbers of anomalies to identify patterns and recurring root causes. This accelerates problem-solving and supports continuous improvement of the IT delivery process. |
| Reporting & Alerting | GenAI can generate reports, graphs and even real-time dashboards. For those AI summarizes relevant measurement data, and when specific thresholds are exceeded, create automatic alerts to trigger control actions. This way GenAI supports real-time insights into quality of products, processes and people involved in the IT delivery process. |
| Estimating | GenAI can compare a new story with a large set of reference stories to find the closest match and generate estimates based on that historical data, taking various parameters into consideration. |
| Planning | GenAI can help optimize planning of resources and scheduling tasks, by analyzing dependencies between user stories, and dependencies on required resources, while applying priorities and critical path analysis. |
| Infrastructure | GenAI can optimize the use of infrastructure based on historical and current data about the project. It can also support in generation of infrastructure-as-code scripts or analyze existing scripts to suggest improvements. |
| Tooling | GenAI can offer support in selecting tools by leveraging knowledge of the existing tool stack, other tools that are available on the market, and the project’s specific needs. Also AI can support (and largely automate) the deployment and maintenance of tools and frameworks. |
| Metrics | GenAI can provide guidance on selecting appropriate metrics, aligned with the improvement goals set by users or other stakeholders. Subsequently it can perform the relevant measurements to gather input for continuous improvement. |
| Continuous Improvement | Using the gathered measurements GenAI can guide improving both effectiveness and efficiency of the IT delivery process. Also GenAI can assist in analyzing the effects of improvement activities. Based on this analysis, it can support decisions on whether to continue, adapt, or enhance improvement initiatives. |
| Performing Topic | |
|---|---|
| Quality risk analysis & Test strategy | GenAI can generate an overview of requirements to serve as the starting point for risk analysis. It can also support drawing up the test strategy with choices for relevant test design techniques and test approaches (such functionality is already available in Sogeti’s GenAI Amplifier). |
| Acceptance criteria | GenAI can analyse transcripts of online meetings and generate acceptance criteria for the user stories or features. Additionally, it can provide advice on the completeness and correctness of acceptance criteria, for the total set of user stories and the combination with a definition of done. |
| Quality measures | TMAP distinguishes three groups of quality measures; to build the right quality from the start, to provide information about the quality level and to improve the quality of deliverables. GenAI can advise on which combination of quality measures could be applied. It can also support the execution of specific quality measures. |
| Reviewing | GenAI can analyze texts such as requirements, user stories, or program code, and provide automated feedback to enhance their quality. Also AI may be used as one of the team members in a 4 amigos session, thus using the combined skills of people and tools. |
| Test design | GenAI can support the application of test design techniques on a specific test basis to generate test cases. This is one of the first supports people often think of and experience shows that it still requires proper human oversight to ensure the correctness and completeness of the resulting test cases and test data. It can also help distinguish and prioritize test cases based on risk or business value. |
| Test data management | Strict privacy regulations have forced organizations to only use anonymized, or (even better) synthetic test data. GenAI is very suitable for the process of anonymization and it can also generate realistic synthetic test data. |
| Test automation | Writing and optimizing test automation code is basically a development skill and GenAI (especially Large Language Models) are very good at generating program code based on structured programming languages. It can also help analyze and resolve issues encountered during running of the test automation scripts. |
| Test execution | GenAI can orchestrate a test automation suite and schedule the execution of automated test cases, enabling continuous and efficient testing. |
| Investigate & Assess outcome | GenAI can analyze actual test results, compare them with expected outcomes, and—if necessary—support the writing of anomaly reports. |
Return to [Quality Engineering with GenAI] overview.