Test Generation

Test Design Automation – The Crux of Test Automation

Introduction: This blog post is an attempt to address the question of whether model-based testing (MBT) or also called Test Design Automation (TDA) has a bright future in the testing industry. Well, before that, this blog acknowledges that readers have some background knowledge in the field of software testing. The TDA extensively considers the ...

Is Artificial Intelligence Changing The Future Of Testing Industry?

Is Artificial Intelligence Changing The Future Of Testing Industry? Current Testing Landscape: Manual and automated testing– these two primary testing warriors work in tandem to uncover software faults and defects. AI promises to handle repetitive, monotonous tasks, freeing up time for more essential work. AI software ...

Creator 4.0 — Faster and More Capable Than Ever Before

The stuff that I often write about pertains to performance of test generation. The reason for this is quite clear: performance has been and still is one of the biggest stumbling blocks in deploying model based testing and automated test design in an industrial context. We, as a technology provider, are not the only one affected by this. In fact ...

Solving a Game of Sudoku Using a Test Generator

OK I admit that this is a bit farfetched. I don’t ever recall a test manager whose biggest concern would have been how to efficiently solve and test Sudokus. I was simply in a mood of having some fun and what would be better than working with a Sudoku problem. I bet that you have firsthand experience on solving those and just like me, you have ...

The Many Faces of Conformiq Test Generation Technology

Quite often when people talk about MBT (Model Based Testing) they intuitively assume that model is always something with “boxes and arrows”; that is the model in MBT needs to be graphical and it is constructed out of some kind of nodes or vertices which are then connected using arrows of some sort. To some, model may simply mean a state chart or ...

Why Applying One Testing Design Method is Not Enough

Every now and then Conformiq Designer and Creator are compared against other testing tools that employ one type of test design heuristic, for example a combinatorial testing tool for generating optimized pair-wise test data. The capability of generating such combinatorial data combinations is one testing method that in practice has been observed ...

Test Design Techniques

Test design concerns making the decisions on (1) what to and what not to test, (2) how to stimulate the system and with what data values, and (3) how the system should react and respond to the stimuli. It is a separate task from test execution and is done before executing the tests against the system. Test design techniques, on the other hand, are ...

Conditional Coverage Heuristics

Some time ago I wrote a short blog post about equivalence partitioning and boundary value analysis. Now with new version of Conformiq Designer coming out very soon we have introduced quite a few new testing heuristics and coverage options that are based on equivalence class partitioning I wanted to write about how Conformiq can use these new ...

Combinatorial Test Data Generation with Conformiq

Suppose a system model states that when a message comes in, it is forwarded out unchanged. This particular message has a number of fields, some of them integers, some strings. For some reason there is cause to suspect that the forwarding feature in the real implementation might be flawed, so we would like to have a number of different message ...

Distributed Test Generation

As detailed in a blog post I wrote a couple of months ago, the core of Conformiq DesignerTM is a custom crafted  semantics driven, symbolic state space exploration  algorithm for test generation from system models (because this is really the only known solution that robustly generates both test inputs and outputs from a system model without user ...

Performance of Test Generation

Test generation from system models is computationally very hard: Just generating input sequences that cover all the statements of a system model is theoretically an undecidable problem, meaning it can be never solved completely. This does not mean there couldn’t be an algorithm that handles most of the industrially relevant problem instances, but ...