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We Need to Talk!! – A Chatroom Application Using a Student-Designed Protocol

Published: 02 July 2019 Publication History

Abstract

This poster describes an assignment for a computer networks class in which students design and implement an application-layer protocol for a chatroom using a client-server architecture running over TCP-IP. Working collaboratively, students design a single protocol that will be implemented by all class members. The protocol is written in a style based on that used in a Request for Comments (RFC), the international standard for describing networking protocols. Students work in pairs to implement the protocol using a programming technology of their choice. This experience helps students to understand that different applications can communicate when they are all designed according to the same RFC specification.

Reference

[1]
Association for Computing Machinery (ACM) Joint Task Force on Computing Curricula and IEEE Computer Society. 2013. Computer Science Curricula 2013: Curriculum Guidelines for Undergraduate Degree Programs in Computer Science. ACM, New York, NY, USA. 999133.

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  1. We Need to Talk!! – A Chatroom Application Using a Student-Designed Protocol

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      cover image ACM Conferences
      ITiCSE '19: Proceedings of the 2019 ACM Conference on Innovation and Technology in Computer Science Education
      July 2019
      583 pages
      ISBN:9781450368957
      DOI:10.1145/3304221
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      New York, NY, United States

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      Published: 02 July 2019

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      Author Tags

      1. client--server
      2. computer networks
      3. computer science education
      4. protocols
      5. tcp-ip

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      Overall Acceptance Rate 552 of 1,613 submissions, 34%

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