A theory of diagnosis from first principles
Artificial Intelligence
Artificial Intelligence
PELAS-Program Error-Locating Assistant System
IEEE Transactions on Software Engineering
Aspect: detecting bugs with abstract dependences
ACM Transactions on Software Engineering and Methodology (TOSEM)
Model-based diagnosis of hardware designs
Artificial Intelligence
New directions in debugging hardware designs
IEA/AIE '99 Proceedings of the 12th international conference on Industrial and engineering applications of artificial intelligence and expert systems: multiple approaches to intelligent systems
Automatic Program DeBugging for Intelligent Tutoring Systems
Automatic Program DeBugging for Intelligent Tutoring Systems
Algorithmic Program DeBugging
Dependency-Directed Localization of Software Bugs
Dependency-Directed Localization of Software Bugs
Logic programs for consistency-based diagnosis
Logic programs for consistency-based diagnosis
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
DiKe - A Model-Based Diagnosis Kernel and Its Application
KI '01 Proceedings of the Joint German/Austrian Conference on AI: Advances in Artificial Intelligence
| Hi-index | 0.00 |
This paper describes the use of model-based reasoning for locating bugs in Java programs. Model-based diagnosis is a technology that uses a declarative, generic description of the behavior of the components occurring in a domain to construct a model of the overall system which can then be used at the desired level of abstraction to predict a system's behavior and derive assumptions about which parts of the system are incorrect. This approach is particularly enticing when applied to software since the model can be constructed from the program automatically. However, the actual choice of models poses interesting challenges. We show a simple model based on dependencies that can be used to diagnose very large programs, and walk through an example debugging session.