Prices And Cost Savings

// Experience. Execution. Excellence.

COSTS of fixing bugs from production

A production bug is a very expensive bug to fix, hot-fixes are dangerous and can lead to new issues bigger than the one you are trying to fix
Having automated tests prevents new bugs in the development stage, at a commit level (each merge request is tested)
Blockers in production cause revenue blockage, clients leaving your product, image deterioration, etc..
It’s not a singular effort to fix a production bug, most time multiple developers work on the same fix, fix needs to be tested, deployment to production is time consuming.
While fixing production bugs, new features implementation is halted

Two columns

Vertical

Horizontal

"{{getWooProductName}}" has been added to your cart

We have sent your request information to your email.

Issued on: {{ $store.getters.getIssuedOn }}

Payment method: {{ $store.getters.getPaymentType }}

{{ item.title }}: {{ item.value }}

// Experience. Execution. Excellence.

A simple Calculator that calculates the amount of time a company spends via manual testing on doing a sanity/smoke for each development task.
We reduce this cost via an automated SANITY test suite that saves this time and money.
Building a Sanity/Smoke suite that tests basic functionalities takes around 3 weeks -> 1.5 months depending on the complexity of the product, and would be at an estimated price of around 6000 Euro
Depending on how many users stories and testers are working the ROI could occur after approx a month
We must take in consideration also the benefits of a feedback loop …. meaning that while it takes a manual tester an average of 3 hours, it takes the automated suite 5-10 minutes.

Two columns

Vertical

Horizontal

"{{getWooProductName}}" has been added to your cart

We have sent your request information to your email.

Issued on: {{ $store.getters.getIssuedOn }}

Payment method: {{ $store.getters.getPaymentType }}

{{ item.title }}: {{ item.value }}

// Experience. Execution. Excellence.

A simple Calculator that calculates the amount of time a company spends via manual testing on doing a full regression run .
We reduce this cost via an automated REGRESSION test suite that saves time and money.
Building a Sanity suite that has a satisfactory full coverage metric is more costly and can take up to 3+ month, it depends on complexity of product
Depending on the how often a full regression is run, but after approx 10 regression cycles you can see ROI increasing
We must also take in consideration the speed of feedback loop … meaning that while takes a manual tester to do a full regression in average 3 days , automated tests take for the same regression pack 30 minutes