MacPaint is a monochromatic raster image painting program that introduced many people to mouse-driven controls, tool palettes, and copy and paste integration with other applications. One of two launch applications for the Apple Macintosh in 1984, MacPaint is emblematic of the Macintosh’s early quirky revolutionary branding, focus on ease of use, and appeal to artistic customers. Using the source code, we examine the design and implementation of the application. We find that the buffer management and bucket filling algorithms demonstrate mechanical empathy with the 68k platform and leverage the limitations of the domain as a means to improve performance. We also find positive and negative aspects in the code style and architecture and its pliability for change. Finally, we dispute some claimed novel aspects of the program while also arguing for its significance and impact on the development of digital graphic systems.
Charles Dodgson (pen name Lewis Carroll) had difficulty remembering numbers, such as dates. He developed a cipher to help him remember numbers by embedding them in couplets or phrases. For example, the couplet “Brass trumpet and brazen bassoon, will speedily mark you a tune” encodes the specific gravity of brass (8.39) in the last four consonants: r k t n (y is treated as a vowel). In this article, we describe the cipher, present online tools for encoding and decoding, discuss how we implemented the algorithms in TypeScript, and the cipher’s relevancy to steganography.
The new generation of code assistance tools powered by Large Language Models (LLM)s may be useful in efficiently categorizing and translating historical software corpora. In this qualitative study, we examine LLM performance in explaining and translating FLOW-MATIC programs. We also test their reliability by injecting OCR-like errors into the text. Released in 1958, FLOW-MATIC targeted business applications and used a heavily English-inspired syntax that later influenced COBOL. We find that the models perform inconsistently for describing the key aspects of a program but fare better when translating business logic into SQL. LLMs appear robust against OCR-like errors in the source code, but we caution against relying on the current technology.
Chatbots Decoded: Exploring AI is a new exhibit from the Computer History Museum (CHM) opening November 20th, 2024. In development for more than a year, the exhibit covers both the history of chatbots and conversational interfaces as well as the social ramifications of the technology. While there is not an explanation for why GPUs rather than CPUs are so useful for learning or what “attention is all you need” means, both are alluded too and I think, many audiences, including children, will enjoy it.