Tuesday, January 1, 2019

Retrospective X

Last year, I conducted a simple retrospective for 2017. Therefore, here is a retrospective for 2018.

2018 Achievements
  • Complete ten year blog on agile software application to game development
  • Streamline Sega Master System retro game development using devkitSMS
  • Enter Simpsons Trivia into Sega Master System annual coding competition
  • Port Simpsons Trivia to XNA then to PC, Andriod and iOS using MonoGame
  • Experiment additional platforms using MonoGame e.g. Mac, WP8 and UWP
  • Build 3D City adding MonoGame targets PC, Mac, WP8, Android, iOS, UWP
  • Test VR Unity plugins SteamVR, Oculus and AR Xamarin frameworks ARKit
  • Begin AI and Machine Learning format with TensorFlow on WinPC and Mac
Note: completing ten year blog post on various game development topics is an achievement!

2019 Objectives
  • Investigate sharing code options online: Git Submodules or Mercurial Subrepos
  • Explore Sega dev + debugging environment from Master System to MegaDrive
  • Expand MonoGame cross platform ideas trialing 3D models and custom effects
  • Continue AI and Machine Learning studies cross platform and cross languages

This blog was created in 2009 after the completion of my first independent game built using XNA: Henway. The goal was to discuss issues found during independent game development and provide potential solutions.

Ten years later and this blog has expanded ideas to modern agile software application in game development and the ability to scale game projects quickly cross multiple platforms while always being mindful of quality.

During this time, XNA has given way to other frameworks and engines but MonoGame has proved to be most successful in terms of applying these ideas to new titles such as Candy Kid, Simpsons Trivia plus 3D City.

Conversely, much time has also been spent especially during the past five years programming older systems. Writing low level code to run on real 8-bit hardware like the Sega Master System with limited memory and storage requires performance-critical algorithms to be written to achieve maximum frame rate at all times.

The future in Software Engineering looks exciting as LinkedIn opportunities include Blockchain Developer, Machine Learning Engineer and Machine Learning Specialist as part of the top five emerging jobs in 2018.

Therefore, frameworks like TensorFlow for example, used in machine learning applications available cross multiple platforms in both high + low level languages seem very aligned to approaches used in this blog J