Building applications, especially custom ones, carries with it the burden of answering the question: Does this do what the customer wants?
With complicated systems with many interacting features and business rules, answering this question can be daunting. In fact, evaluating the answer can be daunting too, from the perspective of the customer. Having the sales guy check some boxes in a questionnaire, or watching a demo just doesn’t leave you with the assurance that the application with handle all the business requirements, from either perspective, the vendors or the customer. Everyone I have spoken to who has sold complex software, or who has participated in the purchasing process of software has expressed the same doubt. They are just not sure that the tool will be a good fit. As we all know, that doubt does not always prevent the purchase of the software, as each organization has its own level of risk tolerance, and trust in the vendor’s brand or reputation. Often these other considerations can outweigh the amorphous doubt that some folks might feel. How can one quantify that doubt? Frankly, it’s a quandary.
This thought got us at Profit Point thinking… Wouldn’t it be great if there was another way to evaluate the goodness of fit or an application, or the appropriateness of the parameter settings, to match the business needs of an organization. Would it be great if there was a way to eliminate (or greatly reduce) the doubt, and replace it with facts. Either a business rule is obeyed or it is not. Either a decision is made according to the requirements, or it is not. Let’s eliminate the doubt, we thought, and the world would be a better place. (well a little bit anyway).
There are many processes for testing an application as it is being developed, with writing test scripts, and evaluating the results. All these are based on testing little pieces of code, to ensure that each function or sub routine does what it should do in each case of input data. These processes work fine in our opinion, but only when the sub of function is able to be considered independently form the others. When the system has functions that interact heavily, then this approach doesn’t reduce the doubt that the functions may conflict or compete in a way that the whole system suffers. How then to evaluate the whole system? Could we treat the entire application as one black box, and evaluate the important business cases, and evaluate the results? This is exactly what we have done, with the effect of reducing the doubt to zero about the suitability of the application for a business.
With several of our clients we have worked out what seems to be a great process of testing a complex software solution for suitability to the business requirement. In this case, the detailed level function testing methods were not open to us, since the solution relied on a Linear Programming technique.
This process is really just an amplification of the standard testing process.
- Define the test case, with the expected results
- Construct the test data
- Build or configure the application
- Run the Test using the Test Data and Evaluate the results – Pass or Fail
This is the standard process for testing small functions, where the expected results are clear and easy to imagine. However, in some systems where there many interacting rules and conflicting priorities, it may not be simple to know what the expected results should be without the help of the tool’s structure to evaluate them. Such is the case with many of our application, with layer upon layer of business rules and competing priorities… The very reason for using an LP based approach makes testing more complex.
In the revised process, we have, for each new business requirement:
- Construct the test case with the test data
- Build or configure the application
- Set the expected results using the results of the first pass build
- Re-factor the code and test until all test are passing
Profit Point’s Software Testing Process
In my next blog I will show you the simple excel based tools we use to facilitate the test evaluation.
In practice, the process works well, new versions of the application go into production without any surprises, and with full confidence of the application management team that all the business requirements are 100% met.
No doubt – no doubt a better process.
By Jim Piermarini