The past year has been rough for many of us. With a global pandemic, political and environmental crises, as well as turmoil and uncertainty of everyday life it’s been hard for everyone. As college students, we understand how stressful life can be whether it’s about a 10 hour long job shift or a daunting calc final. It’s easy to look back and relive our nostalgic childhood, a past full of happy, carefree memories and days spent playing games like Mario Kart and Angry Birds. One game in particular was a global hit: causing a mass of people to spend time on their phones, sliding, dodging, and weaving their way through one of the most popular mobile games ever: Temple Run.

For our SwampHacks 2021 project we recreated this retro classic using Lua and Roblox Studio. But we didn’t just remake Temple Run. We made it better, adding in our school’s beloved president and mascot as well as a Gators logo and plenty of memorabilia. Of course, in our quest to recreate this epicly popular game we ran into plenty of challenges. Lua is a relatively uncommon language, with significantly less documentation and guides compared to easier and popular languages like Python and C++. Creating an AI as well as fixing a camera angle and using tons of different models took vast amounts of time and effort. Our biggest challenge was getting accustomed to the Lua language, as none of us had ever used the language before.

Additionally, our team consisted of first year students with little to no prior coding experience and what coding we have done has mainly been focused on output. The process of transitioning from simple output to complex game development involving 3d objects, AI, animation/movement and creating/implementing models was no easy task but we managed to get it done. Ultimately, while our game isn’t perfect we were able to create a different, yet satisfactory Temple Run. The thrill and anticipation of a good run is deeply ingrained in our game, and the nostalgic happy memories Temple Run is remembered for are just as existent in our improved version: SwampRun.

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