Book Chapter10.1007/978-3-540-70592-5_25
Practical Object-Oriented Back-in-Time Debugging
Adrian Lienhard,Tudor Gîrba,Oscar Nierstrasz +2 more
- 07 Jul 2008
- pp 592-615
TL;DR: This paper proposes a practical approach that attempts to keep track of only the relevant data, and keeps object history information together with the regular objects in the application memory so that data not reachable from current application objects is garbage collected.
read more
Abstract: Back-in-time debuggers are extremely useful tools for identifying the causes of bugs. Unfortunately the "omniscient" approaches that try to remember allprevious states are impractical because they consume too much space or they are far too slow. Several approaches rely on heuristics to limit these penalties, but they ultimately end up throwing out too much relevant information. In this paper we propose a practical approach that attempts to keep track of only the relevant data. In contrast to other approaches, we keep object history information together with the regular objects in the application memory. Although seemingly counter-intuitive, this approach has the effect that data not reachable from current application objects (and hence, no longer relevant) is garbage collected. We describe the technical details of our approach, and we present benchmarks that demonstrate that memory consumption stays within practical bounds. Furthermore, the performance penalty is significantly less than with other approaches.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
BigDL: A Distributed Deep Learning Framework for Big Data
Jason Dai,Yiheng Wang,Xin Qiu,Ding Ding,Yao Zhang,Yanzhang Wang,Xianyan Jia,Cherry Li Zhang,Yan Wan,Zhichao Li,Jiao Wang,Shengsheng Huang,Zhongyuan Wu,Yang Wang,Yuhao Yang,Bowen She,Dongjie Shi,Qi Lu,Kai Huang,Guoqiong Song +19 more
TL;DR: This paper presents BigDL, a distributed deep learning framework for Apache Spark that allows deep learning applications to run on the Apache Hadoop/Spark cluster so as to directly process the production data, and as a part of the end-to-end data analysis pipeline for deployment and management.
185
First Infrastructure and Experimentation in Echo-debugging.
TL;DR: The echo-debugger, a tool to debug two different executions in parallel, and the Convergence Divergence Mapping (CDM) algorithm to locate all the control-flow divergences and convergences of these executions are proposed.
107
Back to the Future: Omniscient Debugging
Guillaume Pothier,Éric Tanter +1 more
TL;DR: This article presents TOD (trace oriented debugger), a prototype scalable omniscient debugger for Java, which aims at making omniscience debugging practical, at last.
89
Tardis: affordable time-travel debugging in managed runtimes
Earl T. Barr,Mark Marron +1 more
- 15 Oct 2014
TL;DR: Tardis provides affordable time-travel with an average overhead of only 7% during normal execution, a rate of 0.6MB/s of history logging, and a worst-case 0.68s time- travel latency on the authors' benchmark applications, making Tardis suitable for use as the default debugger for managed languages.
References
•Book
100 statistical tests
Gopal K. Kanji
- 01 Jan 1993
TL;DR: In this article, the authors introduce Statistical Testing Examples of Test Procedures List of Tests Classification of Tests The Tests List of Tables Tables Tables The Tests list of tables tables Table 1.1.
686
•Book
Why Programs Fail: A Guide to Systematic Debugging
Andreas Zeller
- 01 Oct 2005
TL;DR: The new edition of this award-winning productivity-booster is for any developer who has ever been frustrated by elusive bugs, andBrand new chapters demonstrate cutting-edge debugging techniques and tools, enabling readers to put the latest time-saving developments to work for them.
Implementing jalapeño in Java
Bowen Alpern,Clement Richard Attanasio,Anthony Cocchi,Derek Lieber,Stephen Edwin Smith,Ton Ngo,John Barton,Susan Flynn Hummel,Janice C. Sheperd,Mark F. Mergen +9 more
- 01 Oct 1999
TL;DR: Jalapeño is a virtual machine for Java#8482; servers written in Java that reduces the Java / non-Java boundary below the virtual machine rather than above it, and opens up more opportunities for optimization.
299
Efficient algorithms for bidirectional debugging
Bob Boothe
- 01 May 2000
TL;DR: This paper discusses the research into algorithms for creating anefficient bidirectional debugger in which all traditional forward movement commands can be performed with equal ease in the reverse direction and expects that adding these backwards movement capabilities to a debugger will greatly increase its efficacy as a programming tool.
113
Related Papers (5)
Christoph Hofer,Marcus Denker,Stéphane Ducasse +2 more
- 01 Jan 2006
Bob Boothe
- 01 May 2000
Guillaume Pothier,Éric Tanter +1 more