Page History
...
While functional testing is a common entry point for Test Case Designer implementations, and we have multiple articles describing the benefits achieved, integration testing (both system-to-system and E2E) is often even more applicable because of the increase in scale and number of dependencies (and, consequently, in number of important possible interactions).
However, with that increase comes the greater difficulty in decision-making which leads , leading to the major challenge in testing complex systems – “how much testing is enough?”
...
We will describe how these benefits come to life on the generalized example of the Guidewire suite implementation at a large insurance client (specifically, the “Auto Policy Bind and Rewrite” workflow).
...
| Info |
|---|
Note 1: The variation % of 70 is used for example purposes and highly depends on the project infrastructure, rule complexity, etc. But that value is fairly common across the implementations we have seen. Note 2: The execution/design split is almost never rarely 100 to 0 in either direction, so the decision is more between, e.g., 70/30 or 30/70. Note 3: Release history and changes to the functional/integration testing changes could alter the approach decisions throughout the project lifecycle. |
...
- prioritize parameters that affect more than 1 system;
- prioritize values heavily involved in business rule/integration triggers;
- consider using value expansions for less impactful options.
Drop-down menus in the Policy Creation system itself could be responsible for the majority most of the variation various ideas to get you started. Often though, additional insights into the optimal values to use for elements such as dates, payment methods, or user/agent profiles will need to be added.
Therefore, the stakeholders from each involved system should provide input about a) integration factors that matter to them (e.g., “given our objectives in this set of tests, it is important to include policy duration and payment methods, but not delivery preferences”), and b) the appropriate level of detail for those (e.g., “when it comes to payment methods, it is the category of payment method that’s most important to vary; be sure to include some scenarios with ACH and some with Credit Card).
Those 2 point points apply whether it is billing…
...
But don’t overdo it here – don’t add extra tests to ensure that 20 different types of credit cards are tested combinatorially because that would result in more tests than we need; instead, just sprinkle in a few common types of credit cards into the test set.
When it comes to transactions like Change or Rewrite, the value nature in “strategic” E2E models shifts to declarative or directional rather than imperative:
...
I.e., the E2E scenarios generated from the inputs above would be highly-valuable (because they would result in covering the most important kinds of variation in E2E scenarios) but they would be “incomplete” – they would not specify what exact kind of SNI is added, which exact coverage(s) are is increased, the precise amount(s) they would be increased by, etc. Making such values more robust would be part of the transition to “No -> Design” approach from the decision tree above.
...
Such nesting also allows test designers to “connect” TCD models in a way , since the same profile can be reused in the models responsible for parallel (create Umbrella policies) or sequential (test Renewals later) steps.
Value expansions can further serve as a test data specification , if needed:
| Info |
|---|
| For maintenance reasons, we recommend keeping TCD values at the category level (especially dates) and setting up execution in a way that would calculate the actual date/would, query the credit database given the score range/etc. |
Repetitive model elements can be handled by appending the “extra detail” to the parameter name (e.g., "- Original State"):
vs
For convenience, we suggest keeping the parameters in the flow order on the first screen. For the same purpose, elements like this can serve as visual dividers on the Parameters/Scenarios screens and are optional:
...
| Info |
|---|
| Implementing system logic via TCD constraints would occur at this step, but there are no aspects unique to E2E testing about constraint - handling, so we are skipping it. |
...
When it comes to efficiently covering all critical interactions in a system using as few test tests as possible, the TCD test generation algorithm will dramatically outperform humans in speed, accuracy, thoroughness, and number of tests used. Even if there are more than 10,000 critical interactions in a system, for example, the algorithm will cover every single one, guaranteed. And do so in just several minutes using as few tests as mathematically possible. No human brain could come close. And production data wouldn’t come close.
...
All 3 high-priority E2E scenarios after being entered into Test Case Designer
For It would be best to let the TCD algorithm handle the factors which that are not explicitly specified, you should preferably let the TCD algorithm handle them. In other words, . In other words, if your model contains 10 parameters but the special edge-case requires 4 specific values, then specify only those 4. TCD will fill in the blanks automatically and, while doing so, identify the most varied, highest-coverage, least-wastefully repetitive 6 values possible.
Pro tip: one subtle trick for one-off testing in TCD is that Forced Interactions can overwrite Constraints , and vice versa. You can use that workaround for the scenarios that are deemed “very low probability” by the business, but are it still required needs to be tested from an IT standpoint.
The last point at in this step is to select an appropriate level of thoroughness for your needs. It is rare for E2E TCD models to utilize anything other than 2-way (at the “Strategic” level) or Mixed-strength (at any level). 3-way or higher coverage strengths would typically be overkill. The dropdown settings in Mixed-strength are generally chosen based on the following parameter logic:
- Does it impact 2+ systems and have numerous rules/dependencies associated with it? -> Include using at least a 2-way coverage selection.
- Does it impact 2+ systems and have few/no rules/dependencies associated with it? -> Include with 2-way selection given short value lists + value expansions or with 1-way otherwise.
- Does it impact only 1 system but have numerous rules/dependencies associated with it? -> Include with 1-way coverage selection and a fairly exhaustive list of values (because of the constraints).
- Does it impact only 1 system and have few/no rules/dependencies associated with it? -> Likely should not have been included in the model, but 1-way otherwise.
...
When end-to-end scenarios are created by hand, they often represent a very fragmented system view of the system and struggle with redundancy or omissions. Instead, Test Case Designer maximizes the interaction coverage in fewer scenarios and provides complete control and traceability for each of the steps in the test case's steps.
If we now analyze the coverage achieved across, e.g., 8 critical parameters and compare it with the typical manual solution, the results would often look like this:
...
| Info |
|---|
| Some teams may choose to execute directly from the test cases table. They would leverage the “Save As” dropdown on the Scenarios screen and skip this section. |
We are observing more & more teams switching to BDD , so we will be covering cover TCD Automate in this article, but most general principles also apply to Manual Scripts.
First, the overall script structure is completely up to you. The number of steps, length of each, number of parameters per each, etc. depend , depends on your guidelines for both test design and execution – . Test Case Case Designer has the flexibility to support a wide range of preferences.
Second, for the review and export efficiency, we will be using {[]} filters to separate Full Term and New Business scenarios (assuming they have different validation steps, for example purposes).
| Info |
|---|
| You can check the “Usage” button on the Automate screen for more details about the syntax rules. |
...
The sequential time aspect can be accounted for by “On Day X,…” parts of the steps. The system-to-system transition can be reflected in a similar manner as well as in commented-out lines. Parameters that didn’t “qualify” for model inclusion and static validations can be hard coded (i.e., you don’t need to include <> syntax in every line). Test data generated during the execution can be captured using steps like this:
...
Once the script is finalized, you can proceed to export the scenarios in the a format compatible with the test management tools and/or automation frameworks. E.g., without any extra actions, you can generate the CSV for Xray alongside Java files.
...
First, the “hard” Test Case Designer limits are 256 parameters and 5000 tests per model. Highly detailed models will require you to consider non-traditional TCD parameters (e.g., test data elements, more expected results) that can exhaust the limit fairly quickly, so prioritizing the prioritization of the scope and the balance between design & execution becomes even more critical.
Second, the extension requires more attention to how parameters & values are organized (e.g., value vs. value expansion, nested vs. standalone) and to mixed-strength settings. Keep in mind that even a single additional parameter – if it has with a long list of values and a 2-way strength setting – will result in a disproportionally large increase in the scenario count.
...
In conclusion, the combination of TCD features will allow you not only to quickly generate the optimal set of scenarios but also to quickly and answer the “how much testing is enough?” question with clarity & confidence.
The image above should be familiar from to our other educational materials. Hopefully, and hopefully, it underscores the notion that the process & methodology are not strongly dependent on the type of testing, type of system, industry, etc.
The goal of applying the Test Case Designer is to deal with such challenges of manual test creation as prolonged and error-prone scenario selection, gaps in test data coverage, tedious documentation, and excessive maintenance.
...