What strategies can you use to balance software quality and time-to-market?

I generally recommend risk-based testing. Think through all of the scenarios, and think about what the consequences are if there is a bug in a certain area. Also, think about how testing in one area may reduce the risk of a bug in other, related areas without testing those related areas. Finally, think about the likelihood of a scenario occurring. As a concrete example, I worked on a loan application system. There were many scenarios, such as a boat trailer loan with 4 applicants, that were unlikely. In addition, a boat trailer loan was essentially the same code as other loans. Plus, if this rare case did have an error, the result was the customer would have to call and complete the form over the phone. We could skip some tests.

For us, testers play a crucial role: projects that exactly define the tests before anything else, run much more smoothly because many consistency issues and unspecified details are found much earlier in the process. We keep the mantra: prove that you will deliver the right stuff before you start the work.

Shift-left approach, to start testing as soon as possible; Start to prepare test automation even before the code is written: - could be possible in many cases, than you'll need just to adjust your tests to the actual code - tests writing approach became more flexible, less complex and easily adjustable; Prioritisation taking into account: - business value - critical (fragile) parts - safety

Few things to consider - - Shift left testing - Ensuring that testing time is incorporated as part of your overall development time and is part of the development cycle.- I favor a separate level of effort for testing each feature. - Bringing in early automation is must. - User acceptance testing if possible - Alpha Beta testing cycle - Using AI to identify scope of testing per release based on what changes are going in, state of the over all application, and state of the feature and regression around it the feature. - Risk Based testing - I used to let Product define the impact of a feature to the business to identify level of Risk.

In my experience , the requirements can be broken down into multiple stages like User Requirements, Functional Requirements, Functional specifications etc. in order to meet the different stakeholder needs. For example, a business user is more interested in looking at the business process within the requirements whereas an engineer will need to understand the business process and the engineering requirement to design a solution that meets the user needs.

During interviews with clients, I noticed that engineers quite often leave out critical parts of their chosen methodology (almost always Scrum nowadays). This leads to expected problems later on. For example: 'estimation' looks like a time waste: you have to do it anyway, so why estimate? But the estimation leads to a more clear definition of the work to be done (won't explain that here). And thinking about risks for every ticket (e.g. unexpected dependencies) helps with throughput and setbacks. So not only risk assessment at the start of the project, but keep doing it.

The readability of code quite often leads to an intense discussion. Because it is a trade-off between factors like time investment, audience expertise etc. So first define the audience, THEN find the middle spot (there is no sweet spot!) where every trade-off is considered. Don't go for the 'code should explain itself' people, because code is always much harder to read then english. Write the functionality in English comments, then write the functional code in between. Don't write down what the code does, but what the code should do. This way engineers can better understand if code can be reused as a building block for other parts.

Even though it is sometimes difficult to plan projects to the minute, do not leave QA to the last second. For some reason everyone thinks that QA is a magical process that just happens. A lot of planning and effort goes into testing, even a simple application. Always provide adequate time to test and fix the defects.

Language bindings and interoperability play a crucial role in enabling developers to leverage the strengths of different programming languages for specific domains. Python, known for its simplicity and ease of use, can be seamlessly integrated with Rust, a language celebrated for its performance and safety features. This combination allows developers to harness Python's readability and flexibility for high-level tasks, while leveraging Rust's speed and memory safety for performance-critical components. This interoperability fosters a collaborative environment where developers can focus on their domain-specific problems, leading to more efficient and reliable software solutions.