Topic
Manual testing
About: Manual testing is a research topic. Over the lifetime, 3158 publications have been published within this topic receiving 62107 citations.
Papers published on a yearly basis
1 / 2
Papers
19 Oct 2009
TL;DR: Direct automated random testing is described, an efficient approach which combines random and symbolic testing, and several heuristic search strategies are presented, including a novel strategy guided by the control flow graph of the program under test.
Abstract: Testing with manually generated test cases is the primary technique used in industry to improve reliability of software-in fact, such testing is reported to account for over half of the typical cost of software development I will describe directed automated random testing (also known as concolic testing), an efficient approach which combines random and symbolic testing Concolic testing enables automatic and systematic testing of programs, avoids redundant test cases and does not generate false warnings Experiments on real-world software show that concolic testing can be used to effectively catch generic errors such as assertion violations, memory leaks, uncaught exceptions, and segmentation faults From our initial experience with concolic testing we have learned that a primary challenge in scaling concolic testing to larger programs is the combinatorial explosion of the path space It is likely that sophisticated strategies for searching this path space are needed to generate inputs that effectively test large programs (by, eg, achieving significant branch coverage) I will present several such heuristic search strategies, including a novel strategy guided by the control flow graph of the program under test
1,912 citations
TL;DR: A relatwely large but easy-to-use collection of test functions and designed gmdelines for testing the reliability and robustness of unconstrained optimization software.
Abstract: Much of the testing of optimization software is inadequate because the number of test functmns is small or the starting points are close to the solution. In addition, there has been too much emphasm on measurmg the efficmncy of the software and not enough on testing reliability and robustness. To address this need, we have produced a relatwely large but easy-to-use collection of test functions and designed gmdelines for testing the reliability and robustness of unconstrained optimization software.
1,559 citations
TL;DR: In this paper, a method of testing the correctness of control structures that can be modeled by a finite-state machine is proposed, based on a result in automata theory and can be applied to software testing.
Abstract: We propose a method of testing the correctness of control structures that can be modeled by a finite-state machine. Test results derived from the design are evaluated against the specification. No "executable" prototype is required. The method is based on a result in automata theory and can be applied to software testing. Its error-detecting capability is compared with that of other approaches. Application experience is summarized.
1,431 citations
TL;DR: The notion of adequacy criteria is examined together with its role in software dynamic testing and the methods for comparison and assessment of criteria are reviewed.
Abstract: Objective measurement of test quality is one of the key issues in software testing. It has been a major research focus for the last two decades. Many test criteria have been proposed and studied for this purpose. Various kinds of rationales have been presented in support of one criterion or another. We survey the research work in this area. The notion of adequacy criteria is examined together with its role in software dynamic testing. A review of criteria classification is followed by a summary of the methods for comparison and assessment of criteria.
1,416 citations
TL;DR: Test case prioritization techniques schedule test cases for execution in an order that attempts to increase their effectiveness at meeting some performance goal as discussed by the authors, such as rate of fault detection, a measure of how quickly faults are detected within the testing process.
Abstract: Test case prioritization techniques schedule test cases for execution in an order that attempts to increase their effectiveness at meeting some performance goal. Various goals are possible; one involves rate of fault detection, a measure of how quickly faults are detected within the testing process. An improved rate of fault detection during testing can provide faster feedback on the system under test and let software engineers begin correcting faults earlier than might otherwise be possible. One application of prioritization techniques involves regression testing, the retesting of software following modifications; in this context, prioritization techniques can take advantage of information gathered about the previous execution of test cases to obtain test case orderings. We describe several techniques for using test execution information to prioritize test cases for regression testing, including: 1) techniques that order test cases based on their total coverage of code components; 2) techniques that order test cases based on their coverage of code components not previously covered; and 3) techniques that order test cases based on their estimated ability to reveal faults in the code components that they cover. We report the results of several experiments in which we applied these techniques to various test suites for various programs and measured the rates of fault detection achieved by the prioritized test suites, comparing those rates to the rates achieved by untreated, randomly ordered, and optimally ordered suites.
1,353 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2025 | 2 |
| 2024 | 8 |
| 2023 | 30 |
| 2022 | 60 |
| 2021 | 26 |
| 2020 | 47 |