The program dependence graph and its use in optimization
ACM Transactions on Programming Languages and Systems (TOPLAS)
PLDI '90 Proceedings of the ACM SIGPLAN 1990 conference on Programming language design and implementation
IEEE Transactions on Software Engineering
Elements of information theory
Elements of information theory
Semantic metrics for software testability
Journal of Systems and Software - Special issue on the Oregon Metric Workshop
Forward computation of dynamic program slices
ISSTA '94 Proceedings of the 1994 ACM SIGSOFT international symposium on Software testing and analysis
jRapture: A Capture/Replay tool for observation-based testing
Proceedings of the 2000 ACM SIGSOFT international symposium on Software testing and analysis
Testability, fault size and the domain-to-range ratio: An eternal triangle
Proceedings of the 2000 ACM SIGSOFT international symposium on Software testing and analysis
Certification of programs for secure information flow
Communications of the ACM
A lattice model of secure information flow
Communications of the ACM
A note on the confinement problem
Communications of the ACM
Interprocedural control dependence
ACM Transactions on Software Engineering and Methodology (TOSEM)
Automated Software Engineering
Whole program Path-Based dynamic impact analysis
Proceedings of the 25th International Conference on Software Engineering
CSFW '02 Proceedings of the 15th IEEE workshop on Computer Security Foundations
The significance of program dependences for software testing, debugging, and maintenance
The significance of program dependences for software testing, debugging, and maintenance
Cost effective dynamic program slicing
Proceedings of the ACM SIGPLAN 2004 conference on Programming language design and implementation
Controlling the Complexity of Software Designs
Proceedings of the 26th International Conference on Software Engineering
Analysis and Visualization of Predicate Dependence on Formal Parameters and Global Variables
IEEE Transactions on Software Engineering
Detecting and Debugging Insecure Information Flows
ISSRE '04 Proceedings of the 15th International Symposium on Software Reliability Engineering
Dynamic information flow analysis, slicing and profiling
Dynamic information flow analysis, slicing and profiling
Efficient and precise dynamic impact analysis using execute-after sequences
Proceedings of the 27th international conference on Software engineering
Using dynamic information flow analysis to detect attacks against applications
SESS '05 Proceedings of the 2005 workshop on Software engineering for secure systems—building trustworthy applications
Experimental evaluation of using dynamic slices for fault location
Proceedings of the sixth international symposium on Automated analysis-driven debugging
Empirical Software Engineering
Pruning dynamic slices with confidence
Proceedings of the 2006 ACM SIGPLAN conference on Programming language design and implementation
Locating faults through automated predicate switching
Proceedings of the 28th international conference on Software engineering
Automatic extraction of abstract-object-state machines from unit-test executions
Proceedings of the 28th international conference on Software engineering
Mining object behavior with ADABU
Proceedings of the 2006 international workshop on Dynamic systems analysis
An empirical study of the strength of information flows in programs
Proceedings of the 2006 international workshop on Dynamic systems analysis
A simulation-based proof technique for dynamic information flow
Proceedings of the 2007 workshop on Programming languages and analysis for security
An Empirical Study of Test Case Filtering Techniques Based on Exercising Information Flows
IEEE Transactions on Software Engineering
Dytan: a generic dynamic taint analysis framework
Proceedings of the 2007 international symposium on Software testing and analysis
Language-based information-flow security
IEEE Journal on Selected Areas in Communications
An empirical study of the factors that reduce the effectiveness of coverage-based fault localization
Proceedings of the 2nd International Workshop on Defects in Large Software Systems: Held in conjunction with the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2009)
The potential of using dynamic information flow analysis in data value prediction
Proceedings of the 19th international conference on Parallel architectures and compilation techniques
An algorithm for capturing variables dependences in test suites
Journal of Systems and Software
Leveraging Strength-Based Dynamic Information Flow Analysis to Enhance Data Value Prediction
ACM Transactions on Architecture and Code Optimization (TACO)
Uncovering performance problems in Java applications with reference propagation profiling
Proceedings of the 34th International Conference on Software Engineering
Quantitative program slicing: separating statements by relevance
Proceedings of the 2013 International Conference on Software Engineering
Prevalence of coincidental correctness and mitigation of its impact on fault localization
ACM Transactions on Software Engineering and Methodology (TOSEM)
Generating profile-based signatures for online intrusion and failure detection
Information and Software Technology
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Dynamic information flow analysis (DIFA) was devised to enable the flow of information among variables in an executing program to be monitored and possibly regulated. It is related to techniques like dynamic slicing and dynamic impact analysis. To better understand the basis for DIFA, we conducted an empirical study in which we measured the strength of information flows identified by DIFA, using information theoretic and correlation-based methods. The results indicate that in most cases the occurrence of a chain of dynamic program dependences between two variables does not indicate a measurable information flow between them. We also explored the relationship between the strength of an information flow and the length of the corresponding dependence chain, and we obtained results indicating that no consistent relationship exists between the length of an information flow and its strength. Finally, we investigated whether data dependence and control dependence makes equal or unequal contributions to flow strength. The results indicate that flows due to data dependences alone are stronger, on average, than flows due to control dependences alone. We present the details of our study and consider the implications of the results for applications of DIFA and related techniques.