Recipes for Coffee: Compositional Construction of JAVA Control Flow Graphs in GROOVE

2018 ◽  
pp. 305-323
Author(s):  
Eduardo Zambon ◽  
Arend Rensink
Keyword(s):  
Control Flow ◽  
Flow Graphs

scholarly journals Neural reverse engineering of stripped binaries using augmented control flow graphs

2020 ◽  
Vol 4 (OOPSLA) ◽  
pp. 1-28 ◽  
Author(s):  
Yaniv David ◽  
Uri Alon ◽  
Eran Yahav
Keyword(s):  
Reverse Engineering ◽  
Control Flow ◽  
Flow Graphs

scholarly journals Generating Functionally Equivalent Programs Having Non-isomorphic Control-Flow Graphs

2017 ◽  
pp. 265-279 ◽  
Author(s):  
Rémi Géraud ◽  
Mirko Koscina ◽  
Paul Lenczner ◽  
David Naccache ◽  
David Saulpic
Keyword(s):  
Control Flow ◽  
Flow Graphs

A Unified Software Reengineering Approach towards Model Driven Architecture Environment

2011 ◽  
pp. 55-100
Author(s):  
Bing Qiao ◽  
Hongji Yang ◽  
Alan O’Callaghan
Keyword(s):  
Control Flow ◽  
Point Of View ◽  
Software System ◽  
Model Driven Architecture ◽  
Unified Framework ◽  
Software Reengineering ◽  
Model Driven ◽  
Incremental Development ◽  
Flow Graphs ◽  
And Control

When developing a software system, there are a number of principles, paradigms, and tools available to choose from. For a specific platform or programming language, a standard way can usually be found to archive the ultimate system; for example, a combination of an incremental development process, object-oriented analysis and design, and a well supported CASE (Computer-Aided Software Engineering) tool. Regardless of the technology to be adopted, the final outcome of the software development is always a working software system. However, when it comes to software reengineering, there is rather less consensus on either approaches or outcomes. Shall we use black-box or white-box reverse engineering for program understanding? Shall we produce data and control flow graphs, or some kind of formal specifications as the output of analysis? Each of these techniques has its pros and cons of tackling various software reengineering problems, and none of them on its own suffices to a whole reengineering project. A proper integration of various techniques capable of solving a specific issue could be an effective way to unravel a complicated software system. This kind of integration has to be done from an architectural point of view. One of the most exciting outcomes of recent efforts on software architecture is the Object Management Group’s (OMG) Model-Driven Architecture (MDA). MDA provides a unified framework for developing middleware-based modern distributed systems, and also a definite goal for software reengineering. This chapter presents a unified software reengineering methodology based on Model-Driven Architecture, which consists of a framework, a process, and related techniques.

scholarly journals Control-Flow Semantics for Assembly-Level Data-Flow Graphs

2006 ◽  
pp. 147-160 ◽  
Author(s):  
Wolfram Kahl ◽  
Christopher K. Anand ◽  
Jacques Carette
Keyword(s):  
Data Flow ◽  
Control Flow ◽  
Level Data ◽  
Data Flow Graphs ◽  
Flow Graphs

Generating Control Flow Graphs from NATURAL

2017 ◽  
pp. 395-402
Author(s):  
Strauss Cunha Carvalho ◽  
Renê Esteves Maria ◽  
Leonardo Schmitt ◽  
Luiz Alberto Vieira Dias
Keyword(s):  
Control Flow ◽  
Flow Graphs

System design language for the combination of data flow and control flow graphs

1983 ◽  
Vol 2 (6) ◽  
pp. 142 ◽  
Author(s):  
F.G. Heath ◽  
P.W. Foulk ◽  
D.Y. Li
Keyword(s):  
System Design ◽  
Data Flow ◽  
Control Flow ◽  
Design Language ◽  
Flow Graphs ◽  
And Control

Improving Similarity Measure for Java Programs Based on Optimal Matching of Control Flow Graphs

2015 ◽  
Vol 25 (07) ◽  
pp. 1171-1197 ◽  
Author(s):  
Dehong Qiu ◽  
Jialin Sun ◽  
Hao Li
Keyword(s):  
Graph Matching ◽  
Control Flow ◽  
Basic Block ◽  
New Approach ◽  
Java Program ◽  
Java Programs ◽  
Instruction Sequences ◽  
High Level ◽  
Flow Graphs ◽  
Basic Blocks

Measuring program similarity plays an important role in solving many problems in software engineering. However, because programs are instruction sequences with complex structures and semantic functions and furthermore, programs may be obfuscated deliberately through semantics-preserving transformations, measuring program similarity is a difficult task that has not been adequately addressed. In this paper, we propose a new approach to measuring Java program similarity. The approach first measures the low-level similarity between basic blocks according to the bytecode instruction sequences and the structural property of the basic blocks. Then, an error-tolerant graph matching algorithm that can combat structure transformations is used to match the Control Flow Graphs (CFG) based on the basic block similarity. The high-level similarity between Java programs is subsequently calculated on the matched pairs of the independent paths extracted from the optimal CFG matching. The proposed CFG-Match approach is compared with a string-based approach, a tree-based approach and a graph-based approach. Experimental results show that the CFG-Match approach is more accurate and robust against semantics-preserving transformations. The CFG-Match approach is used to detect Java program plagiarism. Experiments on the collection of benchmark program pairs collected from the students’ submission of project assignments demonstrate that the CFG-Match approach outperforms the comparative approaches in the detection of Java program plagiarism.

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