There is some curse on the software development processes. A curse that everyone knows but cannot escape. “Assumptions”

Assumption: a thing that is accepted as true or as certain to happen, without proof.

Oxford Languages

During design and implementation processes of software development projects, assumptions are made. These might be somehow normal. But if these assumptions are not based on some data or they are not known as same for every stakeholder in the project team, then assumptions turn into a dark curse and this dark curse might show its worst side without knowing when.

If we have a problem or a requirement in our business model, we also expect to solve it in a consistent way. When we think that we solved the problem but if it is happing again then it’s obvious that we couldn’t solve it as we expected. To minimize this issue and to have a consistent solution we use help of software solutions.

But with assumptions, sometimes, we are implementing these software solutions very hard and complex. This complexity is causing some other problems or solution times become too long. And as you know, these are not expected or wanted outcomes in any business.

We live in an era where change is inevitable and there are many unknown parameters. This fact is the best friend of assumptions. When we have a problem or requirement and if there are too many parameters, sometimes finding suitable values for parameters can be a difficult or time-consuming task for this era. But we must come up with a solution somehow, and this is where assumptions come into play. It’s not so bad, even necessary to make assumptions if we can base assumptions on some data. As all we know, we solved lots of mathematical questions in school, assuming x is equal to 3 or x is between 0-9.

Have some data…(at least a little)

We need to make assumptions according to some data. And then doing the implementations according to these data-based assumptions will easier and more legit. The outcome of assumptions won’t be a surprise. Doing a development with non-data-based assumption can create some output. But the consistency of this output will remain unknown. And this will create a risk in the solution as in the business.

So, we need to try to support our assumptions with some data in software solutions. Monitoring and gathering data, some proof-of-concept data or having answers for questions are the main source of data. And these are not one time job, should be done continuously while software solutions live.

Do documentation…

Everybody might have their own assumptions. If these assumptions are not documented well and not shared/known by some other stakeholder, then they are the potential root causes of some upcoming problems. There are some cases that some assumptions are made on other non-data-based assumptions. And if there is no additional document or data about these assumptions, these might be a grenade with pulled pin. Or every point of view of solution might be different. And this is not a good thing for consistency.

So, there should be some documentation for assumptions. Within this documentation, the reason and validity of the assumption should be described. It is crucial to make this document is up to date.

Don’t cause over-engineering…

Software developers are(might 😁) more focused on the solution than the problem time to time. Sometimes any kind of approach(?) might be implemented for the requirement/problem without thinking the exact problem. Because of this we have this “over-engineering” idiom in terminology. And when assumptions join with love of doing fancy things results might not be as expected. And, if we have “overestimation” as a side-dish then I guarantee that there is going to be some errors and problems in the journey.

Because of assumptions, unnecessary implementations and high complexity in code base will start to exist. And I am not sure if this is a good for any code base. Making everything as generic feature, unnecessary configurations or violation of YAGNI(You aren’t gonna need it) principle is just some basic example outcomes of making assumptions.

So, within implementation process, if we have questions or unknowns, instead of making assumptions we need to try to find answers for these. Because of the project’s current state maybe it is very hard to find answers. With above data and documentation approach we can have some assumptions with tests. If we can have tests for our assumed implementations, then it will be easier to manage assumptions.

Somehow assumptions can be inevitable. If they are inevitable, then we need to know how to handle them or know to make a good assumption. Briefly to have a consistent software solution;

  • Make assumptions based on some data.
  • Document your assumptions.
  • Test and try to validate your assumptions.

See you on next post, until then happy coding. And remember just because the sun has risen every day, it doesn’t mean that every day is bright. 🤓