At Ease with Your Warnings: The Principles of the Salutogenesis Model Applied to Automatic Static Analysis
November 23, 2016 Β· Declared Dead Β· π IEEE International Conference on Software Analysis, Evolution, and Reengineering
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Jan-Peter Ostberg, Stefan Wagner
arXiv ID
1611.08004
Category
cs.SE: Software Engineering
Cross-listed
cs.PL
Citations
9
Venue
IEEE International Conference on Software Analysis, Evolution, and Reengineering
Last Checked
4 months ago
Abstract
The results of an automatic static analysis run can be overwhelming, especially for beginners. The overflow of information and the resulting need for many decisions is mentally tiring and can cause stress symptoms. There are several models in health care which are designed to fight stress. One of these is the salutogenesis model created by Aaron Antonovsky. In this paper, we will present an idea on how to transfer this model into a triage and recommendation model for static analysis tools and give an example of how this can be implemented in FindBugs, a static analysis tool for Java.
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