DOCSLIB.ORG

A Computer Science Academic Vocabulary List

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
A Computer Science Academic Vocabulary List Portland State University PDXScholar Dissertations and Theses Dissertations and Theses 7-27-2020 A Computer Science Academic Vocabulary List David Roesler Portland State University Follow this and additional works at: https://pdxscholar.library.pdx.edu/open_access_etds Part of the Applied Linguistics Commons, and the Computer Sciences Commons Let us know how access to this document benefits ou.y Recommended Citation Roesler, David, "A Computer Science Academic Vocabulary List" (2020). Dissertations and Theses. Paper 5540. https://doi.org/10.15760/etd.7414 This Thesis is brought to you for free and open access. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of PDXScholar. Please contact us if we can make this document more accessible: [email protected]. A Computer Science Academic Vocabulary List by David Roesler A thesis submitted in partial fulfillment of the requirements for the degree of Master of Arts in Teaching English to Speakers of Other Languages Thesis Committee: Lynn Santelmann, Chair Susan Conrad Alissa Hartig Portland State University 2020 A COMPUTER SCIENCE ACADEMIC VOCABULARY LIST Abstract This thesis documents the development the Computer Science Academic Vocabulary List (CSAVL), a pedagogical tool intended for use by English-for-specific-purpose educators and material developers. A 3.5-million-word corpus of academic computer science textbooks and journal articles was developed in order to produce the CSAVL. This study draws on the improved methodologies used in the creation of recent lemma- based word lists such as the Academic Vocabulary List (AVL) (Gardner & Davies, 2014) and the Medical Academic Vocabulary List (MAVL) (Lei & Liu, 2016), which take into account the discipline-specific meanings of academic vocabulary. The CSAVL provides specific information for each entry, including part of speech and CS-specific meanings in order to provide users with clues as to how each item is used within the context of academic CS. Based on the comparative analyses performed in this study, the CSAVL was found to be a more efficient tool for reaching an minimal level of academic CS reading comprehension than the widely-used Academic Word List (AWL) (Coxhead, 2000), or the combination of the AWL with the Computer Science Word List (CSWL) (Minshall, 2013). Through coverage tests performed on a variety of corpora, CSAVL was shown to be representative of the written language of academic computer science and focused on the lemmas that are the most relevant to the context of written academic CS. i A COMPUTER SCIENCE ACADEMIC VOCABULARY LIST Acknowledgements I would like to thank Lynn Santelmann, Susan Conrad, Alissa Hartig, and Tanya Sydorenko of the Portland State University Department of Applied Linguistics for their feedback and support during this project. Their suggestions provided vital guidance in the development of this document. I would also like to thank Errin Beck, Julie Haun, and Alyx Cesar at the Portland State University Intensive English Language Program for providing me with the inspiration for the subject of this thesis. ii A COMPUTER SCIENCE ACADEMIC VOCABULARY LIST Table of Contents Abstract ................................................................................................................................ i Acknowledgements ............................................................................................................. ii List of Tables ..................................................................................................................... vi List of Figures ................................................................................................................... vii Glossary ........................................................................................................................... viii Chapter 1: Introduction ................................................................................................... 1 Chapter 2: Literature Review.......................................................................................... 5 2.1 Academic vocabulary ........................................................................................... 6 2.2 An overview of word lists .................................................................................... 8 2.3 Organizing and defining a ‘word’ ...................................................................... 12 2.4 Lexical coverage and comprehension ................................................................ 15 2.5 Developing a corpus ........................................................................................... 17 2.6 Creating and evaluating word lists ..................................................................... 21 2.7 Evaluations of GSL-based word lists ................................................................. 28 2.8 Evaluations of lemma-based word lists .............................................................. 33 2.9 The Computer Science Academic Word List (Minshall, 2013) ......................... 37 2.10 Research Purposes of the CSAVL project ......................................................... 40 Chapter 3: Methodology ............................................................................................... 43 3.1 Corpus design overview ..................................................................................... 44 3.2 Text types ........................................................................................................... 49 3.3 Journal article selection criteria.......................................................................... 55 3.4 Textbook selection criteria ................................................................................. 57 3.5 CSAC1 size and balance .................................................................................... 58 3.6 CSAC2 size and balance .................................................................................... 62 3.7 Data collection & manual processing................................................................. 66 3.8 Automated processing ........................................................................................ 69 3.9 Word selection criteria ....................................................................................... 71 iii A COMPUTER SCIENCE ACADEMIC VOCABULARY LIST 3.10 Tokenization and part of speech tagging............................................................ 74 3.11 Extracting CSAVL candidate lemmas ............................................................... 75 3.12 Extracting CSAVL-S candidate lemmas ............................................................ 80 3.13 Additions to the CSAVL and CSAVL-S............................................................ 81 3.14 Removing undesired content from the CSAC2 .................................................. 82 3.15 Comparing structurally different word lists ....................................................... 84 3.16 Summary of methodology .................................................................................. 89 Chapter 4: Results ......................................................................................................... 91 4.1 Academic word list coverage comparisons ........................................................ 92 4.2 Supplemental CS word list coverage comparisons ............................................ 97 4.3 General word list coverage comparisons for minimum reading comprehension 99 4.4 Coverage across general, academic, and CS corpora ....................................... 105 4.5 Content comparison with technical dictionaries .............................................. 108 4.6 Word list content comparisons ......................................................................... 113 4.7 Coverage tests of overlapping content ............................................................. 119 4.8 Summary of results........................................................................................... 122 Chapter 5: Discussion ................................................................................................. 126 5.1 The coverage and efficiency of the CSAVL and CSAVL-S ............................ 127 5.2 Representativeness and technicality of the CSAVL and CSAVL-S ................ 132 5.3 The content of the CSAVL and CSAVL-S ...................................................... 134 5.4 Usage of the CSAVL and CSAVL-S ............................................................... 136 5.5 The limitations of the CSAVL project ............................................................. 143 5.6 Possibilities for future corpus and word list research ...................................... 145 5.7 Conclusion ........................................................................................................ 149 References ....................................................................................................................... 151 Appendix A: The Computer Science Academic Vocabulary List (CSAVL) ................. 151 Appendix B: The Computer Science Academic Vocabulary Supplemental List (CSAVL- S)…………… ................................................................................................................. 174 Appendix C: Textbook Usage Survey Data ................................................................... 184 Appendix D: Textbook Usage Counts ...........................................................................
Load more

Recommended publications
  • Tarjan Transcript Final with Timestamps
    A.M. Turing Award Oral History Interview with Robert (Bob) Endre Tarjan by Roy Levin San Mateo, California July 12, 2017 Levin: My name is Roy Levin. Today is July 12th, 2017, and I’m in San Mateo, California at the home of Robert Tarjan, where I’ll be interviewing him for the ACM Turing Award Winners project. Good afternoon, Bob, and thanks for spending the time to talk to me today. Tarjan: You’re welcome. Levin: I’d like to start by talking about your early technical interests and where they came from. When do you first recall being interested in what we might call technical things? Tarjan: Well, the first thing I would say in that direction is my mom took me to the public library in Pomona, where I grew up, which opened up a huge world to me. I started reading science fiction books and stories. Originally, I wanted to be the first person on Mars, that was what I was thinking, and I got interested in astronomy, started reading a lot of science stuff. I got to junior high school and I had an amazing math teacher. His name was Mr. Wall. I had him two years, in the eighth and ninth grade. He was teaching the New Math to us before there was such a thing as “New Math.” He taught us Peano’s axioms and things like that. It was a wonderful thing for a kid like me who was really excited about science and mathematics and so on. The other thing that happened was I discovered Scientific American in the public library and started reading Martin Gardner’s columns on mathematical games and was completely fascinated.
    [Show full text]
  • 1. Course Information Are Handed Out
    6.826—Principles of Computer Systems 2006 6.826—Principles of Computer Systems 2006 course secretary's desk. They normally cover the material discussed in class during the week they 1. Course Information are handed out. Delayed submission of the solutions will be penalized, and no solutions will be accepted after Thursday 5:00PM. Students in the class will be asked to help grade the problem sets. Each week a team of students Staff will work with the TA to grade the week’s problems. This takes about 3-4 hours. Each student will probably only have to do it once during the term. Faculty We will try to return the graded problem sets, with solutions, within a week after their due date. Butler Lampson 32-G924 425-703-5925 [email protected] Policy on collaboration Daniel Jackson 32-G704 8-8471 [email protected] We encourage discussion of the issues in the lectures, readings, and problem sets. However, if Teaching Assistant you collaborate on problem sets, you must tell us who your collaborators are. And in any case, you must write up all solutions on your own. David Shin [email protected] Project Course Secretary During the last half of the course there is a project in which students will work in groups of three Maria Rebelo 32-G715 3-5895 [email protected] or so to apply the methods of the course to their own research projects. Each group will pick a Office Hours real system, preferably one that some member of the group is actually working on but possibly one from a published paper or from someone else’s research, and write: Messrs.
    [Show full text]
  • The Growth of Cryptography
    The growth of cryptography Ronald L. Rivest Viterbi Professor of EECS MIT, Cambridge, MA James R. Killian Jr. Faculty Achievement Award Lecture February 8, 2011 Outline Some pre-1976 context Invention of Public-Key Crypto and RSA Early steps The cryptography business Crypto policy Attacks More New Directions What Next? Conclusion and Acknowledgments Outline Some pre-1976 context Invention of Public-Key Crypto and RSA Early steps The cryptography business Crypto policy Attacks More New Directions What Next? Conclusion and Acknowledgments The greatest common divisor of two numbers is easily computed (using “Euclid’s Algorithm”): gcd(12; 30) = 6 Euclid – 300 B.C. There are infinitely many primes: 2, 3, 5, 7, 11, 13, . Euclid – 300 B.C. There are infinitely many primes: 2, 3, 5, 7, 11, 13, . The greatest common divisor of two numbers is easily computed (using “Euclid’s Algorithm”): gcd(12; 30) = 6 Greek Cryptography – The Scytale An unknown period (the circumference of the scytale) is the secret key, shared by sender and receiver. Euler’s Theorem (1736): If gcd(a; n) = 1, then aφ(n) = 1 (mod n) ; where φ(n) = # of x < n such that gcd(x; n) = 1. Pierre de Fermat (1601-1665) Leonhard Euler (1707–1783) Fermat’s Little Theorem (1640): For any prime p and any a, 1 ≤ a < p: ap−1 = 1 (mod p) Pierre de Fermat (1601-1665) Leonhard Euler (1707–1783) Fermat’s Little Theorem (1640): For any prime p and any a, 1 ≤ a < p: ap−1 = 1 (mod p) Euler’s Theorem (1736): If gcd(a; n) = 1, then aφ(n) = 1 (mod n) ; where φ(n) = # of x < n such that gcd(x; n) = 1.
    [Show full text]
  • The RSA Algorithm
    The RSA Algorithm Evgeny Milanov 3 June 2009 In 1978, Ron Rivest, Adi Shamir, and Leonard Adleman introduced a cryptographic algorithm, which was essentially to replace the less secure National Bureau of Standards (NBS) algorithm. Most impor- tantly, RSA implements a public-key cryptosystem, as well as digital signatures. RSA is motivated by the published works of Diffie and Hellman from several years before, who described the idea of such an algorithm, but never truly developed it. Introduced at the time when the era of electronic email was expected to soon arise, RSA implemented two important ideas: 1. Public-key encryption. This idea omits the need for a \courier" to deliver keys to recipients over another secure channel before transmitting the originally-intended message. In RSA, encryption keys are public, while the decryption keys are not, so only the person with the correct decryption key can decipher an encrypted message. Everyone has their own encryption and decryption keys. The keys must be made in such a way that the decryption key may not be easily deduced from the public encryption key. 2. Digital signatures. The receiver may need to verify that a transmitted message actually origi- nated from the sender (signature), and didn't just come from there (authentication). This is done using the sender's decryption key, and the signature can later be verified by anyone, using the corresponding public encryption key. Signatures therefore cannot be forged. Also, no signer can later deny having signed the message. This is not only useful for electronic mail, but for other electronic transactions and transmissions, such as fund transfers.
    [Show full text]
  • A Library of Graph Algorithms and Supporting Data Structures
    Washington University in St. Louis Washington University Open Scholarship All Computer Science and Engineering Research Computer Science and Engineering Report Number: WUCSE-2015-001 2015-01-19 Grafalgo - A Library of Graph Algorithms and Supporting Data Structures Jonathan Turner This report provides an overview of Grafalgo, an open-source library of graph algorithms and the data structures used to implement them. The programs in this library were originally written to support a graduate class in advanced data structures and algorithms at Washington University. Because the code's primary purpose was pedagogical, it was written to be as straightforward as possible, while still being highly efficient. afalgoGr is implemented in C++ and incorporates some features of C++11. The library is available on an open-source basis and may be downloaded from https://code.google.com/p/grafalgo/. Source code documentation is at www.arl.wustl.edu/~jst/doc/grafalgo. While not designed as... Read complete abstract on page 2. Follow this and additional works at: https://openscholarship.wustl.edu/cse_research Part of the Computer Engineering Commons, and the Computer Sciences Commons Recommended Citation Turner, Jonathan, "Grafalgo - A Library of Graph Algorithms and Supporting Data Structures" Report Number: WUCSE-2015-001 (2015). All Computer Science and Engineering Research. https://openscholarship.wustl.edu/cse_research/242 Department of Computer Science & Engineering - Washington University in St. Louis Campus Box 1045 - St. Louis, MO - 63130 - ph: (314) 935-6160. This technical report is available at Washington University Open Scholarship: https://openscholarship.wustl.edu/ cse_research/242 Grafalgo - A Library of Graph Algorithms and Supporting Data Structures Jonathan Turner Complete Abstract: This report provides an overview of Grafalgo, an open-source library of graph algorithms and the data structures used to implement them.
    [Show full text]
  • Leonard (Len) Max Adleman 2002 Recipient of the ACM Turing Award Interviewed by Hugh Williams August 18, 2016
    Leonard (Len) Max Adleman 2002 Recipient of the ACM Turing Award Interviewed by Hugh Williams August 18, 2016 HW: = Hugh Williams (Interviewer) LA = Len Adelman (ACM Turing Award Recipient) ?? = inaudible (with timestamp) or [ ] for phonetic HW: My name is Hugh Williams. It is the 18th day of August in 2016 and I’m here in the Lincoln Room of the Law Library at the University of Southern California. I’m here to interview Len Adleman for the Turing Award winners’ project. Hello, Len. LA: Hugh. HW: I’m going to ask you a series of questions about your life. They’ll be divided up roughly into about three parts – your early life, your accomplishments, and some reminiscing that you might like to do with regard to that. Let me begin with your early life and ask you to tell me a bit about your ancestors, where they came from, what they did, say up to the time you were born. LA: Up to the time I was born? HW: Yes, right. LA: Okay. What I know about my ancestors is that my father’s father was born somewhere in modern-day Belarus, the Minsk area, and was Jewish, came to the United States probably in the 1890s. My father was born in 1919 in New Jersey. He grew up in the Depression, hopped freight trains across the country, and came to California. And my mother is sort of an unknown. The only thing we know about my mother’s ancestry is a birth certificate, because my mother was born in 1919 and she was an orphan, and it’s not clear that she ever met her parents.
    [Show full text]
  • RON RIVEST Viterbi Professor of Computer Science, MIT's Department of Electrical Engineering and Computer Science
    Feb 1st 10:30 am - noon, Newcomb Hall, South Meeting Room RON RIVEST Viterbi Professor of Computer Science, MIT's Department of Electrical Engineering and Computer Science Security of Voting Systems While running an election sounds simple, it is in fact extremely challenging. Not only are there millions of voters to be authenticated and millions of votes to be carefully collected, count- ed, and stored, there are now millions of "voting machines" containing millions of lines of code to be evaluated for security vulnerabilities. Moreover, voting systems have a unique requirement: the voter must not be given a "receipt" that would allow them to prove how they voted to some- one else---otherwise the voter could be coerced or bribed into voting a certain way. The lack of receipts makes the security of voting system much more challenging than, say, the security of banking systems (where receipts are the norm). We discuss some of the recent trends and innovations in voting systems, as well as some of the new requirements being placed upon voting systems in the U.S., and describe some promising directions for resolving the conflicts inherent in voting system requirements, including some approaches based on cryptography. Professor Rivest is the Viterbi Professor of Computer Science in MIT's Department of Electrical Engineering and Computer Science. He is a member of MIT's Computer Science and Artificial Intelligence Laboratory, and Head of its Center for Information Security and Privacy. Professor Rivest has research interests in cryptography, computer and network security, and algo- rithms. Professor Rivest is an inventor, with Adi Shamir and Len Adleman of the RSA public-key cryp- tosystem, and a co-founder of RSA Data Security.
    [Show full text]
  • IACR Fellows Ceremony Crypto 2010
    IACR Fellows Ceremony Crypto 2010 www.iacr.org IACR Fellows Program (°2002): recognize outstanding IACR members for technical and professional contributions that: Advance the science, technology, and practice of cryptology and related fields; Promote the free exchange of ideas and information about cryptology and related fields; Develop and maintain the professional skill and integrity of individuals in the cryptologic community; Advance the standing of the cryptologic community in the wider scientific and technical world and promote fruitful relationships between the IACR and other scientific and technical organizations. IACR Fellows Selection Committee (2010) Hugo Krawczyk (IBM Research) Ueli Maurer (IBM Zurich) Tatsuaki Okamoto (NTT research), chair Ron Rivest (MIT) Moti Yung (Google Inc and Columbia University) Current IACR Fellows Tom Berson Ueli Maurer G. Robert Jr. Blakley Kevin McCurley Gilles Brassard Ralph Merkle David Chaum Silvio Micali Don Coppersmith Moni Naor Whitfield Diffie Michael O. Rabin Oded Goldreich Ron Rivest Shafi Goldwasser Martin Hellman Adi Shamir Hideki Imai Gustavus (Gus) Simmons Arjen K. Lenstra Jacques Stern James L. Massey New IACR Fellows in 2010 Andrew Clark Ivan Damgård Yvo Desmedt Jean-Jacques Quisquater Andrew Yao Ivan Damgard IACR Fellow, 2010 For fundamental contributions to cryptography, for sustained educational leadership in cryptography, and for service to the IACR. Jean-Jacques Quisquater IACR Fellow, 2010 For basic contributions to cryptographic hardware and to cryptologic education and for
    [Show full text]
  • Oral History Interview with Martin Hellman
    An Interview with MARTIN HELLMAN OH 375 Conducted by Jeffrey R. Yost on 22 November 2004 Palo Alto, California Charles Babbage Institute Center for the History of Information Technology University of Minnesota, Minneapolis Copyright 2004, Charles Babbage Institute Martin Hellman Interview 22 November 2004 Oral History 375 Abstract Leading cryptography scholar Martin Hellman begins by discussing his developing interest in cryptography, factors underlying his decision to do academic research in this area, and the circumstances and fundamental insights of his invention of public key cryptography with collaborators Whitfield Diffie and Ralph Merkle at Stanford University in the mid-1970s. He also relates his subsequent work in cryptography with Steve Pohlig (the Pohlig-Hellman system) and others. Hellman addresses his involvement with and the broader context of the debate about the federal government’s cryptography policy—regarding to the National Security Agency’s (NSA) early efforts to contain and discourage academic work in the field, the Department of Commerce’s encryption export restrictions (under the International Traffic of Arms Regulation, or ITAR), and key escrow (the so-called Clipper chip). He also touches on the commercialization of cryptography with RSA Data Security and VeriSign, as well as indicates some important individuals in academe and industry who have not received proper credit for their accomplishments in the field of cryptography. 1 TAPE 1 (Side A) Yost: My name is Jeffrey Yost. I am from the Charles Babbage Institute and am here today with Martin Hellman in his home in Stanford, California. It’s November 22nd 2004. Yost: Martin could you begin by giving a brief biographical background of yourself—of where you were born and where you grew up? Hellman: I was born October 2nd 1945 in New York City.
    [Show full text]
  • Alan Mathison Turing and the Turing Award Winners
    Alan Turing and the Turing Award Winners A Short Journey Through the History of Computer TítuloScience do capítulo Luis Lamb, 22 June 2012 Slides by Luis C. Lamb Alan Mathison Turing A.M. Turing, 1951 Turing by Stephen Kettle, 2007 by Slides by Luis C. Lamb Assumptions • I assume knowlege of Computing as a Science. • I shall not talk about computing before Turing: Leibniz, Babbage, Boole, Gödel... • I shall not detail theorems or algorithms. • I shall apologize for omissions at the end of this presentation. • Comprehensive information about Turing can be found at http://www.mathcomp.leeds.ac.uk/turing2012/ • The full version of this talk is available upon request. Slides by Luis C. Lamb Alan Mathison Turing § Born 23 June 1912: 2 Warrington Crescent, Maida Vale, London W9 Google maps Slides by Luis C. Lamb Alan Mathison Turing: short biography • 1922: Attends Hazlehurst Preparatory School • ’26: Sherborne School Dorset • ’31: King’s College Cambridge, Maths (graduates in ‘34). • ’35: Elected to Fellowship of King’s College Cambridge • ’36: Publishes “On Computable Numbers, with an Application to the Entscheindungsproblem”, Journal of the London Math. Soc. • ’38: PhD Princeton (viva on 21 June) : “Systems of Logic Based on Ordinals”, supervised by Alonzo Church. • Letter to Philipp Hall: “I hope Hitler will not have invaded England before I come back.” • ’39 Joins Bletchley Park: designs the “Bombe”. • ’40: First Bombes are fully operational • ’41: Breaks the German Naval Enigma. • ’42-44: Several contibutions to war effort on codebreaking; secure speech devices; computing. • ’45: Automatic Computing Engine (ACE) Computer. Slides by Luis C.
    [Show full text]
  • Contents 1 a Brief Introduction to Cryptography
    RSA Catherine Easton July 2007 VIGRE REU at the University of Chicago, Apprentice Program Abstract This paper examines the mathematics of the RSA code through a simple example. Contents 1 A Brief Introduction to Cryptography 1 2 RSA 2 2.1 Keys needed in RSA . 2 2.2 RSA Encryption . 2 2.3 RSA decryption . 4 1 A Brief Introduction to Cryptography In the classical explanation of cryptography, Alice wishes to write a message to Bob, but Eve continues to intercept her messages. Alice and Bob decide to encrypt their messages. Alice and Bob can meet in person and exchange a key. With this informa- tion, they can both encrypt and decrypt messages to each other. Even if Eve manages to intercept a message, she will not be able to gain any information from it, seeing as it is encoded and she does not know the key necessary for decryption. This scenario uses private-key cryptography. Now, however, let us assume that it is impossible for Alice and Bob to meet, and that they are therefore unable to exchange the key. Obviously, Alice cannot send Bob the key, seeing as their messages are being intercepted by Eve, who would then know the key as well. To overcome this barrier, Alice and Bob must use public-key cryptography. Bob selects both an encryption function and a cor- responding decryption function. He sends only the encryption function to Alice. 1 She then uses the encryption function to encrypt her message. Once her message is encrypted, Alice herself is unable to decrypt it.
    [Show full text]
  • “MIT Unlocks Cryptography for the Masses” How MIT People Played a Major Role in the Early Development of Public Key Cryptography
    “MIT Unlocks Cryptography for the Masses” How MIT people played a major role in the early development of public key cryptography. by Ed Radlo ‘67 May 30, 2020 1 Why is PKC important? It’s what made it possible to conduct confidential (encrypted) communications over open (unsecure) networks, most notably the Internet. • enabled e-commerce • enabled confidential (encrypted) e-mails over unsecure networks PKC is a two-sided coin: encryption and authentication. • Running the algorithm in forward gives encryption. • Running the algorithm in reverse gives authentication. Authentication, implemented by digital signatures, gives three things: 1. mathematical proof that the message hasn’t been altered 2. mathematical proof that the nominal sender was the actual sender 3. the sender can’t repudiate that s/he sent the message 2 History of Encryption Has been around for thousands of years. • Used by Egyptians and Phoenicians in 2000 B.C. • Mostly military applications. • Same key used for encryption and decryption (symmetric cryptography). • PKC is asymmetric cryptography. In the 1970’s, computers became increasingly widespread. • DES was the first widely used commercial encryption algorithm developed by IBM symmetric NBS (now NIST) made it a government standard in 1977 NSA made it intentionally weak o government had a monopoly until 1970’s o fear that encryption would get in the wrong hands 3 The Public Key Revolution PKC per se invented by Whitfield Diffie and Martin Hellman in 1976. • Whit Diffie – MIT ‘65 • Marty Hellman – assistant professor of Electrical Engineering at MIT (1969 – 1971) Three parts to the invention: 1. key broken into two – public portion and private portion computationally infeasible to derive the private key from the public key Rivest and Hellman also credit Ralph Merkle with this part 2.
    [Show full text]