One of the most common misconceptions about software testing is that, once a program or software system has gone through testing, it is free of bugs. If you accept this assumption, it logically follows that, if any bugs are found by the end user, the software was not properly tested. Both of these statements are absolutely false.

The truth about software testing is that there is no way to prove that a program or system of any reasonable size is “bug free.” In order to prove that there are no faults (this is the technical term for “bug”) in a program, it is necessary to show that the program functions correctly under all possible conditions and in all states.

As an example, consider a very simple program that accepts a single value as input, and doesn’t read any external data during its execution. If the input value is boolean (true or false), there are two conditions that need to be tested: what happens when a value of true is passed in, and what happens when a value of false is passed in.

What if we expand our simple program so that it accepts two boolean values? Now there are four cases to test.

Input A | Input B |
---|---|

false | false |

false | true |

true | false |

true | true |

To illustrate just how quickly the number of cases required to prove a program fault free grows, let’s consider one last example. Let’s say we have a simple program that accepts a single character (letter, number, etc.) as input. How many test cases are required to prove that this program is free of defects? Twenty-six? What about numbers? What about punctuation marks?

To get to the actual answer, we have to consider the way that a single character is represented in the computer’s memory. Computers understand only ones and zeroes (binary), which means that every piece of data flowing through memory has to be stored as some kind of number. Character data is generally stored using the American Standard Code for Information Interchange (ASCII). This code provides a one-to-one mapping between each character and a number, allowing for the translation of characters and strings to and from a numeric format.

The range of numbers used by ASCII requires a single byte (a string of eight
ones or zeroes) to represent each character. That means that our single
character of input can be viewed as eight individual boolean values. As
illustrated above, in order to fully test the program we need to cover all
possible combinations of input values. **The total number of possible
combinations for eight boolean values is 256!**

If a simple program that accepts only a single character of data requires 256 test cases to be proven “bug free,” imagine how many test cases would be required for even a rudimentary application like Notepad. The truth is that the problem of proving the validity of all possible input scenarios rapidly approaches a level that is impossible to measure in any realistic time frame.

This is precisely why no software system can ever be proven free of faults, and why determining which combinations of input values to test is a crucial part of software testing. Effective testing involves finding those input combinations that are most likely to be encountered in real world use, and also those combinations which are most likely to reveal faults. There are many techniques for selectively choosing an effective and efficient set of test cases that have all been developed because of this fundamental problem in the nature of software testing.

In the world of software engineering, testing is really about reducing the probability of a system failure, not eliminating it as a possibility.

Adam Platt is a technologist with more than a decade of experience across the full stack. His passion for technology and penchant for rendering complex technical ideas into simple terms have made him an in-demand speaker. His resume includes BriForum, the PowerShell Summit, teaching engagements and more.

He is one of the 10 types of people who understand binary and he can solve a Rubik’s Cube.

Adam Platt is a technologist with more than a decade of experience across the full stack. His passion for technology and penchant for rendering complex technical ideas into simple terms have made him an in-demand speaker. His resume includes BriForum, the PowerShell Summit, teaching engagements and more.

He is one of the 10 types of people who understand binary and he can solve a Rubik’s Cube.