Selecting Software Test Data Using Data Flow Information
IEEE Transactions on Software Engineering
Functional program testing and analysis
Functional program testing and analysis
Information Processing Letters
A Statistical Theory of Digital Circuit Testability
IEEE Transactions on Computers
Partition Testing Does Not Inspire Confidence (Program Testing)
IEEE Transactions on Software Engineering
Analyzing Partition Testing Strategies
IEEE Transactions on Software Engineering
PIE: A Dynamic Failure-Based Technique
IEEE Transactions on Software Engineering
Orthogonal Defect Classification-A Concept for In-Process Measurements
IEEE Transactions on Software Engineering - Special issue on software measurement principles, techniques, and environments
Faults on its sleeve: amplifying software reliability testing
ISSTA '93 Proceedings of the 1993 ACM SIGSOFT international symposium on Software testing and analysis
A comparison of data flow path selection criteria
ICSE '85 Proceedings of the 8th international conference on Software engineering
Data Abstraction, Implementation, Specification, and Testing
ACM Transactions on Programming Languages and Systems (TOPLAS)
A Comparison of Some Structural Testing Strategies
IEEE Transactions on Software Engineering
A Formal Analysis of the Fault-Detecting Ability of Testing Methods
IEEE Transactions on Software Engineering
ICSE '81 Proceedings of the 5th international conference on Software engineering
A partition analysis method to increase program reliability
ICSE '81 Proceedings of the 5th international conference on Software engineering
Confidence-Based Reliability And Statistical Coverage Estimation
ISSRE '97 Proceedings of the Eighth International Symposium on Software Reliability Engineering
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A measure of software dependability called trustability is described. A program p has trustability T if we are at least T confident that p is free of faults. Trustability measurement depends on detectability. The detectability of a method is the probability that it will detect faults, when there are faults present. Detectability research can be used to characterize conditions under which one testing and analysis method is more effective than another. Several detectability results that were only previously described informally, and illustrated by example, are proved. Several new detectability results are also proved. The trustability model characterizes the kind of information that is needed to justify a given level of trustability. When the required information is available, the trustability approach can be used to determine strategies in which methods are combined for maximum effectiveness. It can be used to determine the minimum amount of resources needed to guarantee a required degree of trustability, and the maximum trustability that is achievable with a given amount of resources. Theorems proving several optimization results are given. Applications of the trustability model are discussed. Methods for the derivation of detectability factors, the relationship between trustability and operational reliability, and the relationship between the software development process and trustability are described.