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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 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]

When selecting the set of conditions to be tested in modular white-box testing of fundamental program functions, various kinds of criteria are available, including the branch coverage criterion and the all-uses criterion. But there has been very little research on the relationship of these criteria to the overlooking of program faults, and as a consequence many program faults have been discovered only in the later phases of development or at customer sites, where conditions not covered by the original testing occurred. In this paper, an attempt is made to identify the relationship between test conditions and program fault overlooks by expressing the data flows of the program as chains of define-use relationships between two variables. The approach is tested on commercial software products for the control of measuring equipment. The results are used to develop a method of choosing test paths so as to prevent the principal overlook types, and the detection ability and computational efficiency are compared with those of conventional selection criteria. The number of test required in the new method is comparable with that in the all-uses method, and it is capable of preventing almost all of the overlooks that arise from the method used for test path selection. [ABSTRACT FROM AUTHOR]

Mutation testing is a technique for testing software units that has great potential for improving the quality of testing, and thereby increasing the ability to assure the high reliability of critical software. It will be shown that recent advances in mutation research have brought a practical mutation testing system closer to reality. One recent advance is a partial solution to the problem of automatically detecting equivalent mutant programs. Equivalent mutants are currently detected by hand, which makes it very expensive and time-consuming. The problem of detecting equivalent mutants is a specific instance of a more general problem, commonly called the feasible path problem, which says that for certain structural testing criteria some of the test requirements are infeasible in the sense that the semantics of the program imply that no test case satisfies the test requirements. Equivalent mutants, unreachable statements in path testing techniques, and infeasible DU-pairs in data flow testing are all instances of the feasible path problem. This paper presents a technique that uses mathematical constraints, originally developed for test data generation, to detect some equivalent mutants and infeasible paths automatically. © 1997 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]