scholarly journals Decision Graphs and Their Application to Software Testing

2013 ◽  
Vol 2013 ◽  
pp. 1-12
Author(s):  
Robert Gold
Keyword(s):  
Software Engineering ◽  
Software Testing ◽  
Graphical Representation ◽  
Control Flow ◽  
Branch Covering ◽  
Flow Graphs

Control flow graphs are a well-known graphical representation of programs that capture the control flow but abstract from program details. In this paper, we derive decision graphs that reduce control flow graphs but preserve the branching structure of programs. As an application to software engineering, we use decision graphs to compare and clarify different definitions of branch covering in software testing.

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.

Measurement in Software Engineering

2020 ◽  
pp. 166-182
Author(s):  
Ruya Samli ◽  
Zeynep Behrin Güven Aydın ◽  
Uğur Osman Yücel
Keyword(s):  
Software Engineering ◽  
Software Testing ◽  
Software Metrics ◽  
Basic Process ◽  
Testing Tools ◽  
Software Metric ◽  
Development Life Cycle ◽  
Metric Set ◽  
Software Development Life Cycle

Measurement in software is a basic process in all parts of the software development life cycle because it helps to express the quality of a software. But in software engineering, measurement is difficult and not precise. However, researchers accept that any measure is better than zero measure. In this chapter, the software metrics are explained, and some software testing tools are introduced. The software metric sets of Chidamber and Kemerer Metric Set (CK Metric Set), MOOD Metric Set (Brito e Abreu Metric Set), QMOOD Metric Set (Bansiya and Davis Software Metric Set), Rosenberg and Hyatt Metric Set, Lorenz and Kidd Metric Set (L&K Metric Set) are explained. The software testing tools such as Understand, Sonargraph, Findbugs, Metrics, PMD, Coverlipse, Checkstyle, SDMetrics, and Coverity are introduced. Also, 17 literature studies are summarized.

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
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