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Dynamic software updating (DSU) systems patch programs on the fly without incurring downtime. To avoid failures due to the updating process itself, many DSU systems employ timing restrictions. However, timing restrictions are theoretically imperfect, and their practical effectiveness is an open question. This paper presents the first significant empirical evaluation of three popular timing restrictions: activeness safety (AS), which prevents updates to active functions, con-freeness safety (CFS), which only allows modifications to active functions when doing so is provably type-safe, and manual identification of the event-handling loops during which an update may occur. We evaluated these timing restrictions using a series of DSU patches to three programs: OpenSSH, vsftpd, and ngIRCd. We systematically applied updates at each distinct update point reached during execution of a suite of system tests for these programs to determine which updates pass and which fail. We found that all three timing restrictions prevented most failures, but only manual identification allowed none. Further, although CFS and AS allowed many more update points, manual identification still supported updates with minimal delay. Finally, we found that manual identification required the least developer effort. Overall, we conclude that manual identification is most effective. [ABSTRACT FROM AUTHOR]

This paper explores the testing complexity of several classes of programs, where the testing complexity is measured in terms of the number of test data required for demonstrating program correctness by testing. It is shown that even for very restrictive classes of programs, none of the commonly used test criteria, namely, having every statement, branch, and path executed at least once, is nearly sufficient to guarantee absence of errors. Based on the study of testing complexity, this paper proposes two new test criteria, one for testing a path and the other for testing a program. These new criteria suggest how to select test data to obtain confidence in program correctness beyond the requirement of having each statement, branch, or path tested at least once. [ABSTRACT FROM AUTHOR]

This paper presents a testing strategy designed to detect errors in the control flow of a computer program, and the conditions under which this strategy is reliable are given and characterized. The control flow statements in a computer program partition the input space into a set of mutually exclusive domains, each of which corresponds to a particular program path and consists of input data points which cause that path to be executed. The testing strategy generates test points to examine the boundaries of a domain to detect whether a domain error has occurred, as either one or more of these boundaries will have shifted or else the corresponding predicate relational operator has changed. If test points can be chosen within ∈ of each boundary, under the appropriate assumptions, the strategy is shown to be reliable in detecting domain errors of magnitude greater than ∈. Moreover, the number of test points required to test each domain grows only linearly with both the dimensionality of the input space and the number of predicates along the path being tested. [ABSTRACT FROM AUTHOR]

Two approaches to the study of program testing arc described. One approach is theoretical and the other empirical. In the theoretical approach situations are characterized in which it is possible to use testing to formally prove the correctness of programs or the correctness of properties of programs. In the empirical approach statistics are collected which record the frequency with which different testing strategies reveal the errors in a collection of programs. A summary of the results of two research projects which investigated these approaches are presented. The differences between the two approaches are discussed and their relative advantages and disadvantages are compared. [ABSTRACT FROM AUTHOR]