{"title":"The Gap Between Industry and CS Education","authors":"Titus Winters","doi":"10.1145/3502718.3534205","DOIUrl":null,"url":null,"abstract":"Industry practitioners and CS educators seem to operate in different worlds these days. My fellow industry leaders often have surprising ideas about what all can be covered in a 4 year degree program. We are seemingly unaware of the huge challenge in making novices into algorithmic thinkers and programmers, to say nothing of imparting mastery in the ever-expanding array of computing sub-disciplines. At the same time, the day-to-day operations in industry have a very different set of core skills and tools than what is traditionally presented in a CS curriculum. Communication skills, experimentation, reasoning, code comprehension, caching, threading, and concurrency models are a huge fraction of the toolkit for a software practitioner. Hashing is essential. Constants matter. Implementing data structures really doesn't. In practical terms, almost nobody should be using a linked list anymore. This talk will surface what I see as the disconnects on both sides, and suggestions for what we can do about it. (I will also probably be wrong, since I can only speak from my perspective and experience - but that's where important dialogues start.)","PeriodicalId":424418,"journal":{"name":"Proceedings of the 27th ACM Conference on on Innovation and Technology in Computer Science Education Vol. 1","volume":"239 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 27th ACM Conference on on Innovation and Technology in Computer Science Education Vol. 1","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3502718.3534205","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Industry practitioners and CS educators seem to operate in different worlds these days. My fellow industry leaders often have surprising ideas about what all can be covered in a 4 year degree program. We are seemingly unaware of the huge challenge in making novices into algorithmic thinkers and programmers, to say nothing of imparting mastery in the ever-expanding array of computing sub-disciplines. At the same time, the day-to-day operations in industry have a very different set of core skills and tools than what is traditionally presented in a CS curriculum. Communication skills, experimentation, reasoning, code comprehension, caching, threading, and concurrency models are a huge fraction of the toolkit for a software practitioner. Hashing is essential. Constants matter. Implementing data structures really doesn't. In practical terms, almost nobody should be using a linked list anymore. This talk will surface what I see as the disconnects on both sides, and suggestions for what we can do about it. (I will also probably be wrong, since I can only speak from my perspective and experience - but that's where important dialogues start.)
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工业与计算机科学教育之间的差距
如今,行业从业者和计算机科学教育者似乎处于不同的世界。我的同行行业领袖们经常对四年的学位课程能涵盖什么有令人惊讶的想法。我们似乎没有意识到将新手培养成算法思考者和程序员的巨大挑战,更不用说在不断扩大的计算子学科中传授精通知识了。与此同时,与传统的计算机科学课程相比,工业中的日常运营有一套非常不同的核心技能和工具。沟通技巧、实验、推理、代码理解、缓存、线程和并发模型是软件从业者工具包的很大一部分。哈希是必不可少的。常数问题。实现数据结构则不然。实际上,几乎没有人应该再使用链表了。这次演讲将揭示我所看到的双方的脱节,并就我们能做些什么提出建议。(我也可能是错的,因为我只能从我的观点和经验出发——但这是重要对话的开始。)
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