Insight
GLI EUROPE INTERVIEW Margit de Kever
increase of game complexity.”
In addition to return to player calculations, the second area that Margit’s team investigates concerns jurisdictional requirements. It’s a little non-specific in that each and every request is different due to the challenge presented by the huge variety of changes from one marketplace to the next. As Margit described, in Belgium you can’t have more than 70 Euros loss per hour, so there are additional calculations related to Belgium. “In Singapore, you have to have special screens that show the odds for the highest and the lowest winning combinations, which is an additional calculation,” she explains. “And multiple jurisdictions means multiple calculations.”
Once the mathematics team has completed their tasks, the third step is to review the work of their colleagues. Each project completed by one mathematician is reviewed by another. It's an insurance policy GLI insists upon to ensure that nothing is missed; nothing is overlooked. It's both quality assurance and an aspect that promotes peer scrutiny within the math’s team at the global level.
Finally, and perhaps saving the best till last, random number generator testing is a huge part of the work conducted by GLI. RNG testing falls entirely within the remit of the math’s department.Te team works directly with the
client, an aspect that Margit describes as an interactive part of her job. "I love the RNG testing process," confessed Margit. "One of the first projects I worked upon at GLI included a single line of code that had a tiny mistake, the interchanging of just two values, but that completely broke the RNG. It's so exciting when you find something like that, it's thrilling to find the error and determine the exact cause of the issue."
Te creation of games by developers is a combination of elements, from graphics, maths, game design, sound-effects and music. Te single ingredient at the core of every game, however, is the RNG. And most developers use the same one - an RNG called 'Twister,' or more accurately, the Mersenne Twister.
Mersenne Twister is, by far, today's most popular pseudorandom number generator. It is used by every widely distributed mathematical software package. It has been available as an option in MATLAB since it was invented and has been the default for almost a decade. Mersenne Twister was developed by professors Makoto Matsumoto and Takuji Nishimura of Hiroshima University almost 20 years ago and the source code is free to download, which makes it practically ubiquitous. As a random number generator, Twister works extremely well, which is another factor in its universal appeal, however, there are issues with using Twister in
gaming programs, which fundamentally comes down to interpretation.
Margit's explained: "Clients using Twister often ask why we need additional testing of the RNG when Twister is such a universally accepted program? One of the obvious reasons is that testing is a jurisdictional requirement that must be completed as part of the final outcome testing process, but in addition to that you also have issues with scale. Te core Twister RNG produces 32 bit random numbers, it's not perfect, but it's acceptably random for the gaming industry. However, when clients use this RNG they're taking the 32 bit random number and they’re applying that result, for example, to a roulette game, in which they only need 0-36 outcomes - that's were things can go wrong."
It's clear, speaking to Margit, that the GLI maths team relish the challenges of new code, new game features and new maths puzzles. It's the reason why 'final outcome testing' is an aspect of the testing process at which GLI excels – Margit and her team ‘live and breathe’ code. Margit explains that RNGs do not produce perfectly random outcomes in all cases, but rather acceptable randomness that meets requirements. It's a subtle but important distinction that gets to the heart of the necessity for testing. Imperfection and interpretation are the flaws in the development process that can break a game - both an unacceptable outcome
NEWSWIRE / INTERACTIVE /
247.COM P41
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86 |
Page 87 |
Page 88 |
Page 89 |
Page 90 |
Page 91 |
Page 92 |
Page 93 |
Page 94 |
Page 95 |
Page 96 |
Page 97 |
Page 98 |
Page 99 |
Page 100 |
Page 101 |
Page 102 |
Page 103 |
Page 104 |
Page 105 |
Page 106 |
Page 107 |
Page 108 |
Page 109 |
Page 110 |
Page 111 |
Page 112 |
Page 113 |
Page 114 |
Page 115 |
Page 116