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January 1993 Reason Toexpect That to Theresearchcommunity
COMPUTING R ESEARCH N EWS The News Journal of the Computing Research Association January 1993 Vol. 5/No. 1 Membership of Congress changes significantly BY Fred W. Weingarten also was re-elected. He has proven to be attention on high-technology, the seniority for chair of that subcommit- CRA Staff an effective and well-informed chair, committee possibly will attract more tee. His attitude toward science and Although incumbents fared better in but given the turnover in the House members. But it will never have the technology is not well-known. and his rising political star, he may not attraction or political power of the the November elections than was Senate expected, the membership of Congress remain active in R&D policy. Boucher Energy and Commerce Committee, the has changed significantly. Congress has also served on the Energy and Com- Ways and Means Committee or the The Senate is stable because there 118 new members, and some key merce Subcommittee on Telecommuni- Appropriations Committee, which also was less turn-over and science is under members were defeated or retired, so cations and Finance, where he ex- will have openings. Unless they have the Commerce Committee, which is a there will be quite a bit of change in the pressed a great deal of interest in specific interests and expertise in plum. Vice President-elect Al Gore will membership of committees and stimulating the creation of a broadband, science and technology, members with be replaced as chair of the science subcommittees concerned with digital national information infrastruc- seniority and influence tend to gravitate subcommittee. -
Structured Programming - Retrospect and Prospect Harlan D
University of Tennessee, Knoxville Trace: Tennessee Research and Creative Exchange The aH rlan D. Mills Collection Science Alliance 11-1986 Structured Programming - Retrospect and Prospect Harlan D. Mills Follow this and additional works at: http://trace.tennessee.edu/utk_harlan Part of the Software Engineering Commons Recommended Citation Mills, Harlan D., "Structured Programming - Retrospect and Prospect" (1986). The Harlan D. Mills Collection. http://trace.tennessee.edu/utk_harlan/20 This Article is brought to you for free and open access by the Science Alliance at Trace: Tennessee Research and Creative Exchange. It has been accepted for inclusion in The aH rlan D. Mills Collection by an authorized administrator of Trace: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. mJNDAMNTL9JNNEPTS IN SOFTWARE ENGINEERING Structured Programming. Retrospect and Prospect Harlan D. Mills, IBM Corp. Stnuctured program- 2 ' dsger W. Dijkstra's 1969 "Struc- mon wisdom that no sizable program Ste red .tured Programming" articlel could be error-free. After, many sizable ming haxs changed ho w precipitated a decade of intense programs have run a year or more with no programs are written focus on programming techniques that has errors detected. since its introduction fundamentally alteredhumanexpectations and achievements in software devel- Impact of structured programming. two decades ago. opment. These expectations and achievements are However, it still has a Before this decade of intense focus, pro- not universal because of the inertia of lot of potentialfor gramming was regarded as a private, industrial practices. But they are well- lot of fo puzzle-solving activity ofwriting computer enough established to herald fundamental more change. -
Printed Program
rd International Conference 43 on Software Engineering goes Virtual PROGRAM May 25th –28th 2021 Co-located events: May 17th –May 24th Workshops: May 24th , May 29th –June 4th https://conf.researchr.org/home/icse-2021 @ICSEconf Table of Contents Conference overviews ............................................................... 3 Sponsors and Supporters ......................................................... 11 Welcome letter ........................................................................ 13 Keynotes ................................................................................. 18 Technical Briefings ................................................................. 28 Co-located events .................................................................... 35 Workshops .............................................................................. 36 New Faculty Symposium ........................................................ 37 Doctoral Symposium .............................................................. 39 Detailed Program - Tuesday, May 25th .................................................... 42 - Wednesday, May 26th ............................................... 53 - Thursday, May 27th .................................................. 66 - Friday, May 28th ....................................................... 80 Awards .................................................................................... 91 Social and Networking events ................................................. 94 Organizing Committee ........................................................ -
Testing for Trustworthiness in Scientific Software
Testing for Trustworthiness in Scientific Software Daniel Hook Diane Kelly Queen's University Royal Military College of Canada Kingston Ontario Kingston Ontario Abstract expected – and correct – results. Weyuker notes that in Two factors contribute to the difficulty of testing many cases, an oracle is pragmatically unattainable. scientific software. One is the lack of testing oracles – With scientific software, this is almost always the case. a means of comparing software output to expected and Weyuker further comments that if the oracle is correct results. The second is the large number of tests unattainable, then “from the view of correctness testing required when following any standard testing … there is nothing to be gained by performing the technique described in the software engineering test.” For scientific software, this is a depressing and literature. Due to the lack of oracles, scientists use disturbing conclusion. However, there is instead a goal judgment based on experience to assess of trustworthiness rather than correctness that can be trustworthiness, rather than correctness, of their addressed by testing. software. This is an approach well established for In this paper, we first outline a typical development assessing scientific models. However, the problem of environment for scientific software, then briefly assessing software is more complex, exacerbated by discuss testing. This leads to a discussion of the problem of code faults. This highlights the need for correctness and trustworthiness from the view of the effective and efficient testing for code faults in scientist who develops and uses scientific software. We scientific software. Our current research suggests that then introduce new results from our analysis of a small number of well chosen tests may reveal a high samples of scientific software using mutation testing. -
Research Booklet 2020-21
RESEARCH BOOKLET 2020-21 TABLE OF CONTENTS CONTACT INFORMATION ............................................................................................................................................... III OVERVIEW OF RESEARCH IN COMPUTER SCIENCE AT UCF .................................................................................. V ................................................................................................................................................................................................ 0 FACULTY RESEARCH SUMMARIES ............................................................................................................................. 0 Ulas Bagci ........................................................................................................................................................................ 1 Ladislau Bölöni ................................................................................................................................................................ 1 Mainak Chatterjee ............................................................................................................................................................ 2 Guoxing Chen ................................................................................................................................................................... 2 Carolina Cruz-Neira .......................................................................................................................................................... -
Pdf: Software Testing
Software Testing Gregory M. Kapfhammer Department of Computer Science Allegheny College [email protected] I shall not deny that the construction of these testing programs has been a major intellectual effort: to convince oneself that one has not overlooked “a relevant state” and to convince oneself that the testing programs generate them all is no simple matter. The encouraging thing is that (as far as we know!) it could be done. Edsger W. Dijkstra [Dijkstra, 1968] 1 Introduction When a program is implemented to provide a concrete representation of an algorithm, the developers of this program are naturally concerned with the correctness and performance of the implementation. Soft- ware engineers must ensure that their software systems achieve an appropriate level of quality. Software verification is the process of ensuring that a program meets its intended specification [Kaner et al., 1993]. One technique that can assist during the specification, design, and implementation of a software system is software verification through correctness proof. Software testing, or the process of assessing the func- tionality and correctness of a program through execution or analysis, is another alternative for verifying a software system. As noted by Bowen, Hinchley, and Geller, software testing can be appropriately used in conjunction with correctness proofs and other types of formal approaches in order to develop high quality software systems [Bowen and Hinchley, 1995, Geller, 1978]. Yet, it is also possible to use software testing techniques in isolation from program correctness proofs or other formal methods. Software testing is not a “silver bullet” that can guarantee the production of high quality software systems. -
Experience Doing Software Fault Prediction in an Industrial Environment)
UCF Dept. of Computer Science and the College of Engineering and Computer Science I Know Where You're Hiding! (Experience Doing Software Fault Prediction in an Industrial Environment) When validating a software system, it would obviously be very valuable to know in advance which files in the next release ofa large software system are most likely to contain the largest numbers of faults. To accomplish this, we developed negative binomial regression models and used them to predict the expected number of faults in each file of the next release of large industrial software systems. The predictions are based on code char- acteristics and fault and modification history data. This talk will discuss what we have learned from applying the modelsev to eral large industrial systems, each with multiple years of field exposure. I will also discuss our success in making accurate predictions and some of the issues that had to be considered. University Distinguished Professor, College of Engineering and Computer Science, University of Central Florida Elaine Weyuker is a University Distinguished Professor, College of Engineering and Computer Science, University of Central Florida. Before joining UCF, Elaine was a Fellow and Distinguished Member of the Technical Staff at AT&T Labs and Bell Labs, a Professor of Computer Science at the Courant Institute of Mathematical Sciences of New York Universi- ty, a Lecturer at the City University of New York, a Systems Engineer at IBM, and a programmer at Texaco, as well as having served as a consultant for several large international companies. Her research expertise includes techniques and tools to improve the quality of software systems through systematic validation activities, including the development of testing, assessment and software faultprediction models. -
Engineering Software Under Statistical Quality-Control
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange The Harlan D. Mills Collection Science Alliance 11-1990 Engineering Software Under Statistical Quality-Control R. H. Cobb Harlan D. Mills Follow this and additional works at: https://trace.tennessee.edu/utk_harlan Part of the Software Engineering Commons Recommended Citation Cobb, R. H. and Mills, Harlan D., "Engineering Software Under Statistical Quality-Control" (1990). The Harlan D. Mills Collection. https://trace.tennessee.edu/utk_harlan/14 This Article is brought to you for free and open access by the Science Alliance at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in The Harlan D. Mills Collection by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. Engineering Software under Statistical Quality Control Richard H. Cobb and Harlan D. Mills, Software Engineering Technology Thecosbof ociety has been developing soft- culty producing reliable software there is continuing to develop ware for less than one human gen- a demand for even more complex, larger Seration. We have accomplished a software systems. failure-lden 8offws1ye great deal in this first generation when These problems are symptoms of a pre with its associated compared to the accomplishments of cess that is not yet under intellectual con- other disciplines:During the first genera- trol. An activity is under intellectual con- low prductivity are tion of civil engineering, the right triangle trol when the people performing it use a unaamptable. hadn't been invented; accountants did theoretically sound process that gives C1-r- not discover doubleentry concepts in the each of them a high probability of obtain- early generations of their field. -
Coverage Testing in a Production Software Development Environment Kent Bortz Regis University
Regis University ePublications at Regis University All Regis University Theses Fall 2006 Coverage Testing in a Production Software Development Environment Kent Bortz Regis University Follow this and additional works at: https://epublications.regis.edu/theses Part of the Computer Sciences Commons Recommended Citation Bortz, Kent, "Coverage Testing in a Production Software Development Environment" (2006). All Regis University Theses. 416. https://epublications.regis.edu/theses/416 This Thesis - Open Access is brought to you for free and open access by ePublications at Regis University. It has been accepted for inclusion in All Regis University Theses by an authorized administrator of ePublications at Regis University. For more information, please contact [email protected]. Regis University School for Professional Studies Graduate Programs Final Project/Thesis Disclaimer Use of the materials available in the Regis University Thesis Collection (“Collection”) is limited and restricted to those users who agree to comply with the following terms of use. Regis University reserves the right to deny access to the Collection to any person who violates these terms of use or who seeks to or does alter, avoid or supersede the functional conditions, restrictions and limitations of the Collection. The site may be used only for lawful purposes. The user is solely responsible for knowing and adhering to any and all applicable laws, rules, and regulations relating or pertaining to use of the Collection. All content in this Collection is owned by and subject to the exclusive control of Regis University and the authors of the materials. It is available only for research purposes and may not be used in violation of copyright laws or for unlawful purposes. -
Structured Programming - Retrospect and Prospect
University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange The Harlan D. Mills Collection Science Alliance 11-1986 Structured Programming - Retrospect and Prospect Harlan D. Mills Follow this and additional works at: https://trace.tennessee.edu/utk_harlan Part of the Software Engineering Commons Recommended Citation Mills, Harlan D., "Structured Programming - Retrospect and Prospect" (1986). The Harlan D. Mills Collection. https://trace.tennessee.edu/utk_harlan/20 This Article is brought to you for free and open access by the Science Alliance at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in The Harlan D. Mills Collection by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. mJNDAMNTL9JNNEPTS IN SOFTWARE ENGINEERING Structured Programming. Retrospect and Prospect Harlan D. Mills, IBM Corp. Stnuctured program- 2 ' dsger W. Dijkstra's 1969 "Struc- mon wisdom that no sizable program Ste red .tured Programming" articlel could be error-free. After, many sizable ming haxs changed ho w precipitated a decade of intense programs have run a year or more with no programs are written focus on programming techniques that has errors detected. since its introduction fundamentally alteredhumanexpectations and achievements in software devel- Impact of structured programming. two decades ago. opment. These expectations and achievements are However, it still has a Before this decade of intense focus, pro- not universal because of the inertia of lot of potentialfor gramming was regarded as a private, industrial practices. But they are well- lot of fo puzzle-solving activity ofwriting computer enough established to herald fundamental more change. -
Database Test Data Generation
Test Data Generation for Relational Database Applications David Chays Department of Computer and Information Science Technical Report TR-CIS-2005-01 01/12/2005 TEST DATA GENERATION FOR RELATIONAL DATABASE APPLICATIONS DISSERTATION Submitted in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY (Computer & Information Science) at the POLYTECHNIC UNIVERSITY by D. Chays January 2004 Approved : Department Head Copy No. Approved by the Guidance Committee : Major : Computer & Information Science Phyllis Frankl Professor of Computer & Information Science Gleb Naumovich Assistant Professor of Computer & Information Science Filippos Vokolos Assistant Professor of Computer & Information Science Minor : Electrical Engineering Shivendra Panwar Professor of Electrical Engineering Microfilm or other copies of this dissertation are obtainable from UMI Dissertations Publishing Bell & Howell Information and Learning 300 North Zeeb Road P.O. Box 1346 Ann Arbor, Michigan 48106-1346 iv VITA David Chays was born in Brooklyn, New York in November 1972. He received his B.S. degree in Computer Science from Brooklyn College of the City University of New York in 1995 and his M.S. degree in Computer Science from Polytechnic University in Brooklyn, New York, in 1998. After pass- ing the Ph.D. Qualifying Exam at Polytechnic University in 1999, he began working on the database application testing project leading to his thesis, under the supervision of Phyllis Frankl. His research interests are in the areas of software testing, database systems, and computer security. The work presented in this thesis was supported by teaching fellowships from the department of Computer and Information Science at Polytechnic University and grants from the National Science Foundation and the Department of Education. -
Empirical Software Engineering at Microsoft Research
Software Analytics Harlan D. Mills Award Acceptance Speech Nachi Nagappan © Microsoft Corporation About Me • My name is Nachiappan. I also go by Nachi. • https://nachinagappan.github.io/ • Graduated with a PhD with Laurie Williams. • I read a lot of Franco-Belgian comics (Bande dessinées) • Attend Comic conventions • Miniature railroad modeling (HO and G). © Microsoft Corporation 3 © Microsoft Corporation 4 © Microsoft Corporation Courtney Miller Jenna Butler Danielle Gonzalez Rangeet Pan Yu Huang Jazette Johnson Paige Rodeghero Rini Chattopadhyay 5 © Microsoft Corporation Courtney Miller Jenna Butler Danielle Gonzalez Rangeet Pan Yu Huang Jazette Johnson Paige Rodeghero Rini Chattopadhyay 6 © Microsoft Corporation What metrics are the If I increase test coverage, will that best predictors of failures? actually increase software quality? What is the data quality level Are there any metrics that are indicators of used in empirical studies and failures in both Open Source and Commercial how much does it actually domains? matter? I just submitted a bug report. Will it be fixed? Should I be writing unit tests in my software How can I tell if a piece of software will have vulnerabilities? project? Is strong code ownership good or Do cross-cutting concerns bad for software quality? cause defects? Does Distributed/Global software Does Test Driven Development (TDD) development affect quality? produce better code in shorter time? 7 © Microsoft Corporation History of Software Analytics 1976: Thomas McCabe code complexity 1971: Fumio Akiyama 1981: