Demo Data from VLDB 2026 / reviewers in the wild / expert
K. John Gough
dblp:57/1486 · also Kevin John Gough
· DBLP profile ↗
3ranked-venue papers
0as first author
0since 2021 · last 2003
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 3
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Software engineering, system software, and programming languages
1 paper |
Debugging and program repair · 77% Software maintenance and evolution · 23% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Debugging and program repair › software debugging
relative debugging |
0.0 | 1 | 2003 | Automating Relative Debugging · ASE 2003 |
Software maintenance and evolution
software evolution |
0.0 | 1 | 2003 | Automating Relative Debugging · ASE 2003 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | Automating Relative DebuggingabstractThe creation of a new program version based on an existing version is known as software evolution. In 1994, Abramson and Sosic proposed relative debugging to assist users to locate errors in programs developed with software evolutionary techniques. Relative debugging is a paradigm described by D. Abramson et al. (1996) that enables programmers to locate errors by comparing the developed (evolved) program with the original (existing) program as they are concurrently executed. The aim of the proposed research is to further enhance the currently defined paradigm by (partially or completely) automating the process of relatively debugging. We investigate the possibility of automatically identifying the data structures and program points, normally performed by the user, where values should be equivalent during program execution. Minimizing the user's involvement will reduce the cost of enhancing, maintaining and porting software, and has the potential to provide significant productivity gains on current practices in software development. Aaron Searle, K. John Gough, David Abramson 0001 |
ASE | 2 |
| 1995 | Decompilation of Binary ProgramsabstractAbstract The structure of a decompiler is presented, along with a thorough description of the different modules that form part of a decompiler, and the type of analyses that are performed on the machine code to regenerate high‐level language code. The phases of the decompiler have been grouped into three main modules: front‐end, universal decompiling machine, and back‐end. The front‐end is a machine‐dependent module that performs the loading, parsing and semantic analysis of the input program, as well as generating an intermediate representation of the program. The universal decompiling machine is a machine‐ and language‐independent module that performs data and control flow analysis of the program based on the intermediate representation, and the program's control flow graph. The back‐end is a language‐dependent module that deals with the details of the target high‐level language. In order to increase the readability of the generated programs, a decompiling system has been implemented which integrates a decompiler, dcc, and an automatic signature generator, dccSign. Signatures for libraries and compilers are stored in a database that is read by the decompiler; thus, the generated programs can make use of known library names, such as WriteLn() and printf(). dcc is a decompiler for the Intel 80286 architecture and the DOS operating system. dec takes as input binary programs from a DOS environment and generates C programs as output. Sample code produced by this decompiler is given. Cristina Cifuentes, K. John Gough |
Softw. Pract. Exp. | 2 |
| 1994 | Exception Handling: Expecting the Unexptected
Steven J. Drew, K. John Gough |
Comput. Lang. | 2 |