Assisting Bug Report Assignment Using Automated Fault Localisation: an Industrial Case Study
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SIGSOFT CFP-ICSE04.Qxd
General Chair Richard N. Taylor Call for Participation University of California, Irvine [email protected] ACM SIGSOFT 2004 Program Chair Matthew B. Dwyer Twelfth International Symposium on the Kansas State University Foundations of Software Engineering FSE-12 [email protected] Newport Beach Program Committee Ken Anderson, U Colorado, Boulder, USA October 31 - November 5, 2004 Annie Antón, North Carolina State U, USA Hyatt Newporter Hotel, Newport Beach, California, USA Joanne Atlee, U Waterloo, Canada Prem Devanbu, U California, Davis, USA http://www.isr.uci.edu/FSE-12/ Mary Jean Harrold, Georgia Tech, USA John Hatcliff, Kansas State U, USA Jim Herbsleb, Carnegie Mellon U, USA SIGSOFT 2004 brings together researchers and practitioners from academia and industry to André van der Hoek, U California, Irvine, exchange new results related to both traditional and emerging fields of software engineer- USA ing. SIGSOFT 2004 will feature four workshops, one day of tutorials organized through the Paola Inverardi, U L'Aquila, Italy Educator's Grant Program (EGP), a student resarch forum with posters, along with FSE-12. Gregor Kiczales, U British Columbia, Canada Jeff Kramer, Imperial College London, UK FSE-12 will be held Tuesday-Thursday, November 2-4. We are pleased to announce the Shriram Krishnamurthi, Brown U, USA keynotes: Shinji Kusumoto, Osaka U, Japan Axel van Lamsweerde, U Catholique de Alexander L. Wolf, University of Colorado at Boulder, Tues. Nov. 2 Louvain, Belgium Bashar Nuseibeh, The Open U, UK Joe Marks, Director, Mitsubishi Electric Research Laboratories, Cambridge, Wed. Nov. 3 Mauro Pezzé, U Milano-Bicocca, Italy SIGSOFT Distinguished Research Award winner, Thur. -
Development and Certification of Mixed-Criticality Embedded
Development and Certification of Mixed-criticality Embedded Systems based on Probabilistic Timing Analysis Irune Agirre Troncoso Computer Architecture Department Universitat Polit`ecnicade Catalunya A thesis submitted for the degree of PhD in Computer Architecture May 2018 Development and Certification of Mixed-criticality Embedded Systems based on Probabilistic Timing Analysis Irune Agirre Troncoso May 2018 Universitat Polit`ecnicade Catalunya Computer Architecture Department Thesis submitted for the degree of Doctor of Philosophy in Computer Architecture Advisor: Francisco J. Cazorla, Barcelona Supercomputing Center and IIIA-CSIC Co-advisor: Mikel Azkarate-askatsua, IK4-Ikerlan Technology Research Center The work reported in this Thesis has been conducted in collaboration between the Univer- sitat Polit`ecnicade Catalunya, the Dependable Embedded Systems department of IK4-Ikerlan Technology Research Center and the Computer Architecture and Operating Systems (CAOS) group of the Barcelona Supercomputing Center (BSC). i ii Abstract An increasing variety of emerging systems relentlessly replace or aug- ment the functionality of mechanical subsystems with embedded elec- tronics. For quantity, complexity, and use, the safety of such subsys- tems, often subject to regulation, is an increasingly important matter. Those systems are subject to safety certification to demonstrate sys- tem's safety by rigorous development processes and hardware/software constraints. The massive augment in embedded processors' complexity renders the arduous certification task significantly harder to achieve. The focus of this thesis is to address the certification challenges in multicore architectures: despite their potential to integrate several ap- plications on a single platform, their inherent complexity imperils their timing predictability and certification. For the former, Measurement- Based Probabilistic Timing Analysis (MBPTA) has recently emerged as an alternative to deal with hardware/software complexity. -
Improving Web Services Maintenance Through Regression Testing Divya Rohatgi, Prof
Volume 3, Issue 5, May-2016, pp. 261-265 ISSN (O): 2349-7084 International Journal of Computer Engineering In Research Trends Available online at: www.ijcert.org Improving Web Services Maintenance through Regression Testing Divya Rohatgi, Prof. (Col) Gurmit Singh 1. Research Scholar, Computer Science and Engineering Department Sam Higginbottom Institute of Agriculture, Technology and Sciences Deemed University, Allahabad, India 2. Professor, Computer Science and Engineering Department Sam Higginbottom Institute of Agriculture, Technology and Sciences Deemed University, Allahabad, India Abstract: - Software maintenance is considered to be the most expensive activity in software development and is used to ensure quality to the product. Regression Testing is a part of software maintainers which is done every time the software is changed. For software like Web services which represent a class of Service oriented architectures this activity is a challenging task. Since web services incorporate business functionality thus maintaining proper quality is an important concern. Due to inherent distributed, heterogeneous and dynamic in nature, regression testing is difficult and time consuming activity. Thus in order to reduce maintenance cost we have to reduce regression testing cost. Thus in this paper, we have given a comprehensive study of regression testing of web services exploring the challenges, approaches and tools used for them to ensure proper quality and inherently reducing the maintenance costs. Keywords – Software Engineering, Software Maintenance, Regression Testing, Web Service. —————————— —————————— 1. INTRODUCTION implications deriving from the adoption of the standardized stack of technology underlying web In today’s growing and competitive scenario Service– services (e.g., SOAP, WSDL, UDDI, etc.); oriented architectures are having a crucial role in the way in which systems are developed and designed. -
Improving Software Fault Prediction Using a Data-Driven Approach
Improving Software Fault Prediction Using a Data-Driven Approach André Sobral Gonçalves Thesis to obtain the Master of Science Degree in Information Systems and Computer Engineering Supervisor: Prof. Rui Filipe Lima Maranhão de Abreu Examination Committee: Chairperson: Prof. Daniel Jorge Viegas Gonçalves Supervisor: Prof. Rui Filipe Lima Maranhão de Abreu Members of the Committee: Prof. João Fernando Peixoto Ferreira September 2019 ii Acknowledgements Firstly, I want to thank my supervisor, Professor Rui Maranhão for his insight, guidance, patience and for having given me the opportunity to do research in such an interesting field. I am grateful to my family for their immense support, patience and love throughout the entire course. In particular, to my parents, João Carlos and Ana Maria Gonçalves, my brother, João Pedro Gonçalves, my parents-in-law, Carlos and Maria José Alves and my beautiful niece Olivia. I want to thank Carolina Alves, for all her love, care, kindness, determination and willingness to review countless times everything I needed. To my friends and colleagues, José Ferreira, Gustavo Enok, Fábio Almeida, Duarte Meneses, Delfim Costa for supporting me all this time. iii Abstract In software development, debugging is one of the most expensive tasks in the life cycle of a project. Repetitive, manual identification of faults in software, which are the source of errors and inefficiencies, is inherently time-consuming and error-prone. The solution to this problem is automated software diagnosis. This approach solves the issues mentioned previously as long as the accuracy of the diagnosis is credible. There are different tools and techniques which ensure this diagnosis, but they neglect valuable data. -
FINAL PROGRAM University of California, Irvine [email protected] Program Chair Matthew B
General Chair Richard N. Taylor FINAL PROGRAM University of California, Irvine [email protected] Program Chair Matthew B. Dwyer ACM SIGSOFT 2004 University of Nebraska-Lincoln [email protected] Twelfth International Symposium on the Program Committee Ken Anderson, U Colorado, Boulder, USA Foundations of Software Engineering FSE-12 Annie Antón, North Carolina State U, USA Joanne Atlee, U Waterloo, Canada Prem Devanbu, U California, Davis, USA Mary Jean Harrold, Georgia Tech, USA John Hatcliff, Kansas State U, USA Jim Herbsleb, Carnegie Mellon U, USA André van der Hoek, U Calif., Irvine, USA Paola Inverardi, U L'Aquila, Italy Gregor Kiczales, U British Columbia, Canada Jeff Kramer, Imperial College London, UK Shriram Krishnamurthi, Brown U, USA Shinji Kusumoto, Osaka U, Japan Axel van Lamsweerde, U Catholique de Louvain, Belgium Bashar Nuseibeh, The Open U, UK Mauro Pezzé, U Milano-Bicocca, Italy Gian Pietro Picco, Politecnico di Milano, Italy David Rosenblum, U College London, UK Gregg Rothermel, U Nebraska-Lincoln, USA Wilhelm Schäfer, U Paderborn, Germany Douglas Schmidt, Vanderbilt U, USA Peri Tarr, IBM T.J. Watson, USA Frank Tip, IBM T.J. Watson, USA Willem C. Visser, NASA Ames, USA http://www.isr.uci.edu/FSE-12/ Student and Diversity Programs Co-Chairs October 31 - November 5, 2004 Educators Grant Program and Tutorials Hyatt Newporter Hotel, Newport Beach, California, USA Mary Jean Harrold Georgia Tech [email protected] Mary Lou Soffa SIGSOFT 2004 brings together researchers and practitioners from academia and industry to University of Virginia exchange new results related to both traditional and emerging fields of software engineering. -
Curriculum Vitae James A
Curriculum Vitae James A. Jones General Information Bio Highlights Professor Jones is perhaps best known for the creation of the influential Tarantula technique that spawned a new field of \spectra-based" fault localization. For this work, he was awarded the prestigious ACM SIGSOFT Award in 2015. Also, he is a recipient of the prestigious National Science Foundation Faculty Early Career Development (CAREER) Award, which recognizes outstanding research and excellent education. Jones's research contributions span the duration of his undergrad, professional, graduate, and professorial career. Throughout this time, Jones created tools and techniques for software analysis (static and dynamic), techniques to help manage test suites for safety-critical software systems, techniques to support several aspects of software debugging and comprehension, and has studied the ways that software behaves in order to better model and predict it. Jones received the Ph.D. in Computer Science at Georgia Tech, advised by Professor Mary Jean Harrold. At UC Irvine, Jones leads the Spider Lab (http://spideruci.org) and advises Ph.D., Masters, and undergraduate students to study and improve software development and maintenance processes. Jones is a regular author and reviewer for top-tier research conferences (e.g., ICSE, FSE, ISSTA, ASE) and has co-organized events such as the 1st Working Conference on Software Visualization (VISSOFT) and the 10th Workshop on Dynamic Analysis (WODA). Contact Information University of California, Irvine Bren School of Information and Computer Sciences Department of Informatics Institute for Software Research Spider Lab Research Group (http://spideruci.org) 5214 Bren Hall, Irvine, CA 92697-3440 +1 (949) 824-0942 +1 (949) 824-4056 [email protected] http://jamesajones.com http://spideruci.org Jones, James A. -
Fault Diagnosis for Functional Safety in Electrified and Automated Vehicles
Fault Diagnosis for Functional Safety in Electrified and Automated Vehicles Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Tianpei Li, Graduate Program in Mechanical Engineering The Ohio State University 2020 Dissertation Committee: Prof. Giorgio Rizzoni, Advisor Prof. Manoj Srinivasan Prof. Ran Dai Prof. Qadeer Ahmed c Copyright by Tianpei Li 2020 Abstract Vehicle safety is one of the critical elements of modern automobile development. With increasing automation and complexity in safety-related electrical/electronic (E/E) systems, and given the functional safety standards adopted by the automo- tive industry, the evolution and introduction of electrified and automated vehicles had dramatically increased the need to guarantee unprecedented levels of safety and security in the automotive industry. The automotive industry has broadly and voluntarily adopted the functional safety standard ISO 26262 to address functional safety problems in the vehicle development process. A V-cycle software development process is a core element of this standard to ensure functional safety. This dissertation develops a model-based diagnostic method- ology that is inspired by the ISO-26262 V-cycle to meet automotive functional safety requirements. Specifically, in the first phase, system requirements for diagnosis are determined by Hazard Analysis and Risk Assessment (HARA) and Failure Modes and Effect Analysis (FMEA). Following the development of system requirements, the second phase of the process is dedicated to modeling the physical subsystem and its fault modes. The implementation of these models using advanced simulation tools (MATLAB/Simulink and CarSim in this dissertation) permits quantification of the fault effects on system safety and performance. -
Ada User Journal 66 Editorial 67 Quarterly News Digest 69 Conference Calendar 97 Forthcoming Events 103 Articles from the Industrial Track of Ada-Europe 2011 R
ADA Volume 32 USER Number 2 June 2011 JOURNAL Contents Page Editorial Policy for Ada User Journal 66 Editorial 67 Quarterly News Digest 69 Conference Calendar 97 Forthcoming Events 103 Articles from the Industrial Track of Ada-Europe 2011 R. Bridges, F. Dordowsky, H. Tschöpe “Implementing a Software Product Line for a complex Avionics System in Ada 83” 107 Ada Gems 116 Ada-Europe Associate Members (National Ada Organizations) 128 Ada-Europe 2011 Sponsors Inside Back Cover Ada User Journal Volume 32, Number 2, June 2011 66 Editorial Policy for Ada User Journal Publication Original Papers Commentaries Ada User Journal — The Journal for Manuscripts should be submitted in We publish commentaries on Ada and the international Ada Community — is accordance with the submission software engineering topics. These published by Ada-Europe. It appears guidelines (below). may represent the views either of four times a year, on the last days of individuals or of organisations. Such March, June, September and All original technical contributions are articles can be of any length – December. Copy date is the last day of submitted to refereeing by at least two inclusion is at the discretion of the the month of publication. people. Names of referees will be kept Editor. confidential, but their comments will Opinions expressed within the Ada Aims be relayed to the authors at the discretion of the Editor. User Journal do not necessarily Ada User Journal aims to inform represent the views of the Editor, Ada- readers of developments in the Ada The first named author will receive a Europe or its directors. -
Automated Test Cases Prioritization for Self-Driving Cars in Virtual
111 Automated Test Cases Prioritization for Self-driving Cars in Virtual Environments CHRISTIAN BIRCHLER, Zurich University of Applied Science, Switzerland SAJAD KHATIRI, Zurich University of Applied Science & Software Institute - USI, Lugano, Switzerland POURIA DERAKHSHANFAR, Delft University of Technology, Netherlands SEBASTIANO PANICHELLA, Zurich University of Applied Science, Switzerland ANNIBALE PANICHELLA, Delft University of Technology, Netherlands Testing with simulation environments help to identify critical failing scenarios emerging autonomous systems such as self-driving cars (SDCs) and are safer than in-field operational tests. However, these tests are very expensive and aretoo many to be run frequently within limited time constraints. In this paper, we investigate test case prioritization techniques to increase the ability to detect SDC regression faults with virtual tests earlier. Our approach, called SDC-Prioritizer, prioritizes virtual tests for SDCs according to static features of the roads used within the driving scenarios. These features are collected without running the tests and do not require past execution results. SDC-Prioritizer utilizes meta-heuristics to prioritize the test cases using diversity metrics (black-box heuristics) computed on these static features. Our empirical study conducted in the SDC domain shows that SDC-Prioritizer doubles the number of safety-critical failures that virtual tests can detect at the same level of execution time compared to baselines: random and greedy-based test case orderings. Furthermore, this meta-heuristic search performs statistically better than both baselines in terms of detecting safety-critical failures. SDC-Prioritizer effectively prioritize test cases for SDCs with a large improvement in fault detection while its overhead(upto 0.34% of the test execution cost) is negligible. -
Mary Lou Soffa: Curriculum Vitae
Mary Lou Soffa Department of Computer Science 421 Rice Hall Phone: (434) 982-2277 85 Engineer’s Way Fax: (434) 982-2214 P.O. Box 400740 Email: [email protected] University of Virginia Homepage: http://www.cs.virginia.edu/ Charlottesville, VA 22904 Research Interests Optimizing compilers, software engineering, program analysis, instruction level parallelism, program debugging and testing tools, software systems for the multi-core processors, testing cloud applications, testing for machine learning applications Education Ph.D. in Computer Science, University of Pittsburgh, 1977 M.S. in Mathematics, Ohio State University B.S. in Mathematics, University of Pittsburgh, Magna Cum Laude, Phi Beta Kappa Academic Employment Owen R.Cheatham Professor of Sciences, Department of Computer Science, University of Virginia, 2004-present Chair, Department of Computer Science, University of Virginia, 2004-2012 Professor, Department of Computer Science, University of Pittsburgh, 1990-2004 Graduate Dean in Arts and Sciences, University of Pittsburgh, 1991-1996 Visiting Associate Professor, Department of Electrical Engineering and Computer Science, University of California at Berkeley, 1987 Associate Professor, Department of Computer Science, University of Pittsburgh, 1983-1990 Assistant Professor, Department of Computer Science, University of Pittsburgh, 1977-1983 Honors/Awards SEAS Distinguished Faculty Award, 2020 NCWIT Harrold - Notkin Research and Mentoring Award, 2020 University of Virginia Research Award, 2020 Distinguished Paper, A Statistics-Based -
Anglia Ruskin University a Type-Safe Apparatus
ANGLIA RUSKIN UNIVERSITY A TYPE-SAFE APPARATUS EXECUTING HIGHER ORDER FUNCTIONS IN CONJUNCTION WITH HARDWARE ERROR TOLERANCE JONATHAN RICHARD ROBERT KIMMITT A thesis in partial fulfilment of the requirements of Anglia Ruskin University for the degree of Doctor of Philosophy This research programme was carried out in collaboration with The University of Cambridge Submitted: October 2015 Acknowledgements This dissertation was self-funded and prepared in part fulfilment of the requirements of the degree of Doctor of Philosophy under the supervision of Dr David Greaves of The University of Cambridge, and Dr George Wilson and Professor Marcian Cirstea at Anglia Ruskin University, without whose help this dissertation would not have been possible. I am grateful to Dr John O’Donnell of The University of Glasgow and Dr Anil Madhavapeddy of The University of Cambridge for their willingness to examine the degree. Dedication Dedicated to my wife Christine Kimmitt i ANGLIA RUSKIN UNIVERSITY ABSTRACT FACULTY OF SCIENCE AND TECHNOLOGY DOCTOR OF PHILOSOPHY A TYPE-SAFE APPARATUS EXECUTING HIGHER ORDER FUNCTIONS IN CONJUNCTION WITH HARDWARE ERROR TOLERANCE JONATHAN RICHARD ROBERT KIMMITT October 2015 The increasing commoditization of computers in modern society has exceeded the pace of associated developments in reliability. Although theoretical computer science has advanced greatly in the last thirty years, many of the best techniques have yet to find their way into embedded computers, and their failure can have a great potential for disrupting society. -
Dissertation Towards Model-Based Regression
DISSERTATION TOWARDS MODEL-BASED REGRESSION TEST SELECTION Submitted by Mohammed Al-Refai Department of Computer Science In partial fulfillment of the requirements For the Degree of Doctor of Philosophy Colorado State University Fort Collins, Colorado Summer 2019 Doctoral Committee: Advisor: Sudipto Ghosh Co-Advisor: Walter Cazzola James M. Bieman Indrakshi Ray Leo Vijayasarathy Copyright by Mohammed Al-Refai 2019 All Rights Reserved ABSTRACT TOWARDS MODEL-BASED REGRESSION TEST SELECTION Modern software development processes often use UML models to plan and manage the evolu- tion of software systems. Regression testing is important to ensure that the evolution or adaptation did not break existing functionality. Regression testing can be expensive and is performed with limited resources and under time constraints. Regression test selection (RTS) approaches are used to reduce the cost. RTS is performed by analyzing the changes made to a system at the code or model level. Existing model-based RTS approaches that use UML models have some limitations. They do not take into account the impact of changes to the inheritance hierarchy of the classes on test case selection. They use behavioral models to perform impact analysis and obtain traceability links between model elements and test cases. However, in practice, structural models such as class diagrams are most commonly used for designing and maintaining applications. Behavioral models are rarely used and even when they are used, they tend to be incomplete and lack fine-grained details needed to obtain the traceability links, which limits the applicability of the existing UML- based RTS approaches. The goal of this dissertation is to address these limitations and improve the applicability of model-based RTS in practice.