Control and Data Flow Execution of Java Programs
July 27, 2017 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Safeeullah Soomro, Zainab Alansari, Mohammad Riyaz Belgaum
arXiv ID
1708.07393
Category
cs.SE: Software Engineering
Citations
2
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Since decade understanding of programs has become a compulsory task for the students as well as for others who are involved in the process of developing software and providing solutions to open problems. In that aspect showing the problem in a pictorial presentation in a best manner is a key advantage to better understand it. We provide model and structure for Java programs to understand the control and data flow analysis of execution. Especially it helps to understand the static analysis of Java programs, which is an uttermost important phase for software maintenance. We provided information and model for visualization of Java programs that may help better understanding of programs for a learning and analysis purpose. The idea provided for building visualization tool is extracting data and control analysis from execution of Java programs. We presented case studies to prove that our idea is most important for better understanding of Java programs which may help towards static analysis, software debugging and software maintenance.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted