An Introduction to Object-Oriented Programming
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Emery Berger Curriculum Vitae
College of Information and Computer Sciences Emery Berger University of Massachusetts Amherst [email protected] Amherst, MA 01003 http://www.emeryberger.com RESEARCH INTERESTS Design and implementation of programming languages, with a focus on automatically improving reliability, security, and performance. EDUCATION Ph.D., Computer Science, UNIVERSITY OF TEXAS AT AUSTIN, August 2002 Thesis: Memory Management for High-Performance Applications Advisor: Kathryn S. McKinley M.S., Computer Science, UNIVERSITY OF TEXAS AT AUSTIN, December 1991 B.S., Computer Science, UNIVERSITY OF MIAMI, May 1988 ACADEMIC EXPERIENCE Professor, UNIVERSITY OF MASSACHUSETTS AMHERST, 2014–present Visiting Researcher, UNIVERSITY OF WASHINGTON, 2018–9 Visiting Researcher, MICROSOFT RESEARCH, 2005, 2006, 2011, 2013, 2015, 2016, 2018–9 Associate Professor, UNIVERSITY OF MASSACHUSETTS AMHERST, 2008–2014 Associate Researcher, BARCELONA SUPERCOMPUTING CENTER, 2010–2013 Visiting Professor, UNIVERSITAT POLITÈCNICA DE CATALUNYA, 2008–2009 Assistant Professor, UNIVERSITY OF MASSACHUSETTS AMHERST, 2002–2008 Research Intern, MICROSOFT RESEARCH, Summer 2000 & 2001 Graduate Research Assistant, UNIVERSITY OF TEXAS AT AUSTIN, 1997–2002 PROFESSIONAL EXPERIENCE Systems Analyst, UNIVERSITY OF TEXAS AT AUSTIN, 1995–2000 Teacher, BENJAMIN FRANKLIN INTERNATIONAL SCHOOL, Barcelona, Spain, 1992–1994 Systems Analyst, APPLIED RESEARCH LABORATORIES: UT-AUSTIN, 1990–1992 Instructor, THE PRINCETON REVIEW, Austin, Texas, 1989–1990 Teaching Assistant, UNIVERSITY OF TEXAS AT AUSTIN, 1989–1990 -
Andrew W. Appel, Curriculum Vitae
Case 1:17-cv-02989-AT Document 855-3 *SEALED* Filed 09/01/20 Page 1 of 56 IN THE UNITED STATES DISTRICT COURT FOR THE NORTHERN DISTRICT OF GEORGIA ATLANTA DIVISION DONNA CURLING, ET AL., Plaintiffs, v. Civil Action No. 1:17-CV-2989-AT BRAD RAFFENSPERGER, ET AL., Defendants. DECLARATION OF ANDREW W. APPEL IN SUPPORT OF MOTION FOR PRELIMINARY INJUNCTION ANDREW W. APPEL, declares, under penalty of perjury, pursuant to 28 U.S.C. § 1746, that the following is true and correct: 1. My name is Andrew W. Appel. 2. I am the Eugene Higgins Professor of Computer Science at Princeton University, where I have been on the faculty since 1986 and served as Department Chair from 2009-2015. I have also served as Director of Undergraduate Studies, Director of Graduate Studies, and Associate Chair in that department. I have served as Editor in Chief of ACM Transactions on Programming Languages and Systems, the leading journal in my field. In 1998 I was elected a Fellow of the 1 ny-1984930 v3 Case 1:17-cv-02989-AT Document 855-3 *SEALED* Filed 09/01/20 Page 2 of 56 Association for Computing Machinery, the leading scientific and professional society in Computer Science. 3. I previously provided a Declaration in support of the Curling Plaintiffs’ Reply in Support of their Motion for Preliminary Injunction on December 13, 2019 (Dkt. No. 681-3). My 2019 Declaration is attached as Exhibit A. I have reviewed my 2019 Declaration and my previous findings and analyses remain the same; accordingly, I incorporate by reference my prior Declaration in its entirety, subject to the additional opinions I offer here. -
Objects and Classes in Python Documentation Release 0.1
Objects and classes in Python Documentation Release 0.1 Jonathan Fine Sep 27, 2017 Contents 1 Decorators 2 1.1 The decorator syntax.........................................2 1.2 Bound methods............................................3 1.3 staticmethod() .........................................3 1.4 classmethod() ..........................................3 1.5 The call() decorator.......................................4 1.6 Nesting decorators..........................................4 1.7 Class decorators before Python 2.6.................................5 2 Constructing classes 6 2.1 The empty class...........................................6 3 dict_from_class() 8 3.1 The __dict__ of the empty class...................................8 3.2 Is the doc-string part of the body?..................................9 3.3 Definition of dict_from_class() ...............................9 4 property_from_class() 10 4.1 About properties........................................... 10 4.2 Definition of property_from_class() ............................ 11 4.3 Using property_from_class() ................................ 11 4.4 Unwanted keys............................................ 11 5 Deconstructing classes 13 6 type(name, bases, dict) 14 6.1 Constructing the empty class..................................... 14 6.2 Constructing any class........................................ 15 6.3 Specifying __doc__, __name__ and __module__.......................... 15 7 Subclassing int 16 7.1 Mutable and immutable types.................................... 16 7.2 -
Beyond AOP: Toward Naturalistic Programming
Beyond AOP: Toward Naturalistic Programming Cristina Videira Lopes, Paul Dourish, David H. Lorenz and Karl Lieberherr lopes, jpd @ ics.uci.edu lorenz, lieber @ ccs.neu.edu This paper has been accepted for publication in the proceedings of the OOPSLA Onward! track, 2003, and will be subjected to copyright. This document is still not in its final version, and should not be referenced or cited until its official publication. It has been made available to you in response to a personal request. Additional distribution requests should be made directly to the authors. PLEASE DO NOT DISTRIBUTE. Beyond AOP: Toward Naturalistic Programming Cristina Videira Lopes1, Paul Dourish1, David H. Lorenz2, Karl Lieberherr2 1University of California, Irvine 2Northeastern University School of Information and Computer Science College of Computer & Information Science Irvine, CA 92697 Boston, MA 02115 {lopes,jpd}@ics.uci.edu {lorenz,lieber}@ccs.neu.edu Abstract Software understanding (for documentation, maintenance or evolution) is one of the longest-standing problems in Computer Science. The use of “high-level” programming paradigms and object-oriented languages helps, but fundamentally remains far from solving the problem. Most programming languages and systems have fallen prey to the assumption that they are supposed to capture idealized models of computation inspired by deceptively simple metaphors such as objects and mathematical functions. Aspect-oriented programming languages have made a significant break through by noticing that, in many situations, humans think and describe in crosscutting terms. In this paper we suggest that the next break through would require looking even closer to the way humans have been thinking and describing complex systems for thousand of years using natural languages. -
Csci 658-01: Software Language Engineering Python 3 Reflexive
CSci 658-01: Software Language Engineering Python 3 Reflexive Metaprogramming Chapter 3 H. Conrad Cunningham 4 May 2018 Contents 3 Decorators and Metaclasses 2 3.1 Basic Function-Level Debugging . .2 3.1.1 Motivating example . .2 3.1.2 Abstraction Principle, staying DRY . .3 3.1.3 Function decorators . .3 3.1.4 Constructing a debug decorator . .4 3.1.5 Using the debug decorator . .6 3.1.6 Case study review . .7 3.1.7 Variations . .7 3.1.7.1 Logging . .7 3.1.7.2 Optional disable . .8 3.2 Extended Function-Level Debugging . .8 3.2.1 Motivating example . .8 3.2.2 Decorators with arguments . .9 3.2.3 Prefix decorator . .9 3.2.4 Reformulated prefix decorator . 10 3.3 Class-Level Debugging . 12 3.3.1 Motivating example . 12 3.3.2 Class-level debugger . 12 3.3.3 Variation: Attribute access debugging . 14 3.4 Class Hierarchy Debugging . 16 3.4.1 Motivating example . 16 3.4.2 Review of objects and types . 17 3.4.3 Class definition process . 18 3.4.4 Changing the metaclass . 20 3.4.5 Debugging using a metaclass . 21 3.4.6 Why metaclasses? . 22 3.5 Chapter Summary . 23 1 3.6 Exercises . 23 3.7 Acknowledgements . 23 3.8 References . 24 3.9 Terms and Concepts . 24 Copyright (C) 2018, H. Conrad Cunningham Professor of Computer and Information Science University of Mississippi 211 Weir Hall P.O. Box 1848 University, MS 38677 (662) 915-5358 Note: This chapter adapts David Beazley’s debugly example presentation from his Python 3 Metaprogramming tutorial at PyCon’2013 [Beazley 2013a]. -
The Use of UML for Software Requirements Expression and Management
The Use of UML for Software Requirements Expression and Management Alex Murray Ken Clark Jet Propulsion Laboratory Jet Propulsion Laboratory California Institute of Technology California Institute of Technology Pasadena, CA 91109 Pasadena, CA 91109 818-354-0111 818-393-6258 [email protected] [email protected] Abstract— It is common practice to write English-language 1. INTRODUCTION ”shall” statements to embody detailed software requirements in aerospace software applications. This paper explores the This work is being performed as part of the engineering of use of the UML language as a replacement for the English the flight software for the Laser Ranging Interferometer (LRI) language for this purpose. Among the advantages offered by the of the Gravity Recovery and Climate Experiment (GRACE) Unified Modeling Language (UML) is a high degree of clarity Follow-On (F-O) mission. However, rather than use the real and precision in the expression of domain concepts as well as project’s model to illustrate our approach in this paper, we architecture and design. Can this quality of UML be exploited have developed a separate, ”toy” model for use here, because for the definition of software requirements? this makes it easier to avoid getting bogged down in project details, and instead to focus on the technical approach to While expressing logical behavior, interface characteristics, requirements expression and management that is the subject timeliness constraints, and other constraints on software using UML is commonly done and relatively straight-forward, achiev- of this paper. ing the additional aspects of the expression and management of software requirements that stakeholders expect, especially There is one exception to this choice: we will describe our traceability, is far less so. -
Metaclasses: Generative C++
Metaclasses: Generative C++ Document Number: P0707 R3 Date: 2018-02-11 Reply-to: Herb Sutter ([email protected]) Audience: SG7, EWG Contents 1 Overview .............................................................................................................................................................2 2 Language: Metaclasses .......................................................................................................................................7 3 Library: Example metaclasses .......................................................................................................................... 18 4 Applying metaclasses: Qt moc and C++/WinRT .............................................................................................. 35 5 Alternatives for sourcedefinition transform syntax .................................................................................... 41 6 Alternatives for applying the transform .......................................................................................................... 43 7 FAQs ................................................................................................................................................................. 46 8 Revision history ............................................................................................................................................... 51 Major changes in R3: Switched to function-style declaration syntax per SG7 direction in Albuquerque (old: $class M new: constexpr void M(meta::type target, -
Anomaly-Free Component Adaptation with Class Overriding Atanas Radenski Chapman University, [email protected]
Chapman University Chapman University Digital Commons Mathematics, Physics, and Computer Science Science and Technology Faculty Articles and Faculty Articles and Research Research 2004 Anomaly-Free Component Adaptation with Class Overriding Atanas Radenski Chapman University, [email protected] Follow this and additional works at: http://digitalcommons.chapman.edu/scs_articles Part of the Programming Languages and Compilers Commons Recommended Citation Radenski, A. Anomaly-Free Component Adaptation with Class Overriding. Journal of Systems and Software, Elsevier Science, Vol. 71, Issues 1-2, 2004, 37-48. doi: 10.1016/S0164-1212(02)00137-1 This Article is brought to you for free and open access by the Science and Technology Faculty Articles and Research at Chapman University Digital Commons. It has been accepted for inclusion in Mathematics, Physics, and Computer Science Faculty Articles and Research by an authorized administrator of Chapman University Digital Commons. For more information, please contact [email protected]. Anomaly-Free Component Adaptation with Class Overriding Comments This is a pre-copy-editing, author-produced PDF of an article accepted for publication in Journal of Systems and Software, volume 71, issues 1-2, 2004 following peer review. The definitive publisher-authenticated version is available online at DOI:10.1016/S0164-1212(02)00137-1 The rC eative Commons license below applies only to this version of the article. Creative Commons License This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License. Copyright Elsevier This article is available at Chapman University Digital Commons: http://digitalcommons.chapman.edu/scs_articles/211 Page 1: Atanas Radenski: Anomaly-Free Component Adaptation with Class Overriding Anomaly-Free Component Adaptation with Class Overriding Atanas Radenski Chapman University Department of Computer Science, Mathematics, and Physics One University Drive Orange, CA 92866, U.S.A. -
Verified Three-Way Program Merge
Verified Three-Way Program Merge MARCELO SOUSA, University of Oxford, United Kingdom ISIL DILLIG, University of Texas at Austin, United States SHUVENDU K. LAHIRI, Microsoft Research, United States Even though many programmers rely on 3-way merge tools to integrate changes from different branches, such tools can introduce subtle bugs in the integration process. This paper aims to mitigate this problem by defining a semantic notion of conflict-freedom, which ensures that the merged program does not introduce new unwanted behaviors. We also show how to verify this property using a novel, compositional algorithm that combines lightweight summarization for shared program fragments with precise relational reasoning for the modifications. Towards this goal, our method uses a 4-way differencing algorithm on abstract syntax trees to represent different program versions as edits applied to a shared program with holes. This representation allows our verification algorithm to reason about different edits in isolation and compose them toobtain an overall proof of conflict freedom. We have implemented the proposed technique in a new tool called SafeMerge for Java and evaluate it on 52 real-world merge scenarios obtained from Github. The experimental results demonstrate the benefits of our approach over syntactic conflict-freedom and indicate that SafeMerge is both precise and practical. CCS Concepts: • Software and its engineering → Formal software verification; Additional Key Words and Phrases: Three-way program merge, relational verification, product programs ACM Reference Format: Marcelo Sousa, Isil Dillig, and Shuvendu K. Lahiri. 2018. Verified Three-Way Program Merge. Proc. ACM Program. Lang. 2, OOPSLA, Article 165 (November 2018), 29 pages. -
Meta-Class Features for Large-Scale Object Categorization on a Budget
Meta-Class Features for Large-Scale Object Categorization on a Budget Alessandro Bergamo Lorenzo Torresani Dartmouth College Hanover, NH, U.S.A. faleb, [email protected] Abstract cation accuracy over a predefined set of classes, and without consideration of the computational costs of the recognition. In this paper we introduce a novel image descriptor en- We believe that these two assumptions do not meet the abling accurate object categorization even with linear mod- requirements of modern applications of large-scale object els. Akin to the popular attribute descriptors, our feature categorization. For example, test-recognition efficiency is a vector comprises the outputs of a set of classifiers evaluated fundamental requirement to be able to scale object classi- on the image. However, unlike traditional attributes which fication to Web photo repositories, such as Flickr, which represent hand-selected object classes and predefined vi- are growing at rates of several millions new photos per sual properties, our features are learned automatically and day. Furthermore, while a fixed set of object classifiers can correspond to “abstract” categories, which we name meta- be used to annotate pictures with a set of predefined tags, classes. Each meta-class is a super-category obtained by the interactive nature of searching and browsing large im- grouping a set of object classes such that, collectively, they age collections calls for the ability to allow users to define are easy to distinguish from other sets of categories. By us- their own personal query categories to be recognized and ing “learnability” of the meta-classes as criterion for fea- retrieved from the database, ideally in real-time. -
Richard Paul Gabriel Educational Background
Richard Paul Gabriel Address: 3636 Altamont Way Redwood City, CA 94062 Telephone: Voice: (650)298-8735 Fax: (650)216-6755 E-Mail: rpg at dreamsongs.com Web: http://dreamsongs.com Educational Background Warren Wilson College 1995–1998 M.F.A. in Creative Writing (Poetry) Stanford University 1975–1981 Ph.D. in Computer Science University of Illinois 1973–1975 M.S. in Mathematics MIT 1972–1973 Graduate studies in Mathematics Northeastern University 1967–1972 B.A. in Mathematics Recent Experience Researcher, IBM Research, February 2007– Vice Chair, Aspect-Oriented Software Association (AOSA), 2011–2013 Member of the Editorial Board, Transactions on Pattern Languages of Programs, 2007– Chair of the Steering OOPSLA Committee, October 2008–October 2011 Notable Experience School Visitor, Australian National University, December 2010 President, Hillside Group, February 2002–November 2006 Distinguished Engineer, IBM Research February 2007–April 2011 Distinguished Engineer, Sun Microsystems, November 1998–January 2007 Principal Investigator, Sun Microsystems Laboratories July 2004–September 2006 Chief Scientist, Laboratory for Self-Sustaining Systems, July 2000–July 2004 Consultant, Aspen Smallworks, Sun Microsystems, February 1997–November 1998 Distinguished Computer Scientist, ParcPlace-Digitalk, Inc, Dec. 1993–Oct. 1996 Vice President of Development, ParcPlace Systems, Inc, June 1994–August 1995 Lucid Fellow, Lucid Inc, October 1992–November 1993 Chairman of the Board, Lucid Inc, October 1992–December 1994 Chief Technical Officer, Lucid Inc, August 1984–November 1993 Richard P. Gabriel 1 Consulting Full Professor of Computer Science, Stanford University, April 1991–August 2001 Founding Joint Editor-in-Chief, “Lisp and Symbolic Computation: An International Journal,” October 1986–1992 President and Chief Technical Officer, Lucid Inc, August 1984–October 1987 Founder, Lucid, Inc, August 1984 Noteworthy Accomplishments Wrote and promulgated the so-called “Gabriel Benchmarks” for the performance measurement of a variety of Lisp and Lisp-like systems. -
Metaclass Functions: Generative C++
Metaclass functions: Generative C++ Document Number: P0707 R4 Date: 2019-06-16 Reply-to: Herb Sutter ([email protected]) Audience: SG7, EWG Contents 1 Overview .............................................................................................................................................................2 2 Language: “Metaclass” functions .......................................................................................................................6 3 Library: Example metaclasses .......................................................................................................................... 18 4 Applying metaclasses: Qt moc and C++/WinRT .............................................................................................. 35 5 FAQs ................................................................................................................................................................. 41 R4: • Updated notes in §1.3 to track the current prototype, which now also has consteval support. • Added using metaclass function in the class body. Abstract The only way to make a language more powerful, but also make its programs simpler, is by abstraction: adding well-chosen abstractions that let programmers replace manual code patterns with saying directly what they mean. There are two major categories: Elevate coding patterns/idioms into new abstractions built into the language. For example, in current C++, range-for lets programmers directly declare “for each” loops with compiler support and enforcement.