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I looked at my cards. 2 Aces. The best hand possible to have in poker on an empty board. At this point there is no risk that I can be beaten. I decide to exploit the situation. Get as much value as possible, but not letting my opponents know I have such a good hand. I don’t raise. 3 cards come on the board. I wait. The 4th card comes. I still wait. The fifth and last card comes and I make my move. I put all my money on the line and as it turns out, I got beaten by someone who has made a straight. How is this possible? I had the best hand, I evaluated the risk and still lost. The reason is obvious, the board changed 3 times, and with each extra card, my risk of losing also changed. And I did not adapt. I didn’t re-evaluate my risks and acted accordingly.
There are quite a few games that deal with risks and risk responses. Poker and Monopoly are a few examples. There are world championships held in these games and there is general consensus who are the best players in the world. Those players have game tactics. What if we can map those tactics to Risk Based Testing? Can we improve our process based on those successful game tactics? In this presentation, I will elaborate on a few game tactics and map them on the Risk Based Testing process. I will give concrete examples of similarities between them and demonstrate that they can be adapted to improve our test process.