Context: Mutation testing has been mainly analyzed regarding traditional mutation operators involving structured programming constructs common in mainstream languages, but mutations at the class level have not been assessed to the same extent. This fact is noteworthy in the case of C + + , despite being one of the most relevant languages including object-oriented features. Objective: This paper provides a complete evaluation of class operators for the C + + programming language. MuCPP, a new system devoted to the application of mutation testing to this language, was developed to this end. This mutation system implements class mutation operators in a robust way, dealing with the inherent complexity of the language. Method:MuCPP generates the mutants by traversing the abstract syntax tree of each translation unit with the Clang API, and stores mutants as branches in the Git version control system. The tool is able to detect duplicate mutants, avoid system headers, and drive the compilation process. Then, MuCPP is used to conduct experiments with several open-source C + + programs. Results: The improvement rules listed in this paper to reduce unproductive class mutants have a significant impact in the computational cost of the technique. We also calculate the quantity and distribution of mutants generated with class operators, which generate far fewer mutants than their traditional counterparts. Conclusions: We show that the tests accompanying these programs cannot detect faults related to particular object-oriented features of C + + . In order to increase the mutation score, we create new test scenarios to kill the surviving class mutants for all the applications. The results confirm that, while traditional mutation operators are still needed, class operators can complement them and help testers further improve the test suite.

The nature of the requirements analysis problem, based as it is on uncertain and often inaccurate estimates of costs and effort, makes sensitivity analysis important. Sensitivity analysis allows the decision maker to identify those requirements and budgets that are particularly sensitive to misestimation. However, finding scalable sensitivity analysis techniques is not easy because the underlying optimization problem is NP-hard. This article introduces an approach to sensitivity analysis based on exact optimization. We implemented this approach as a tool, O ATSAC , which allowed us to experimentally evaluate the scalability and applicability of Requirements Sensitivity Analysis (RSA). Our results show that O ATSAC scales sufficiently well for practical applications in Requirements Sensitivity Analysis. We also show how the sensitivity analysis can yield insights into difficult and otherwise obscure interactions between budgets, requirements costs, and estimate inaccuracies using a real-world case study.

Wireless sensor network (WSN) applications are rapidly growing and are widely used in various disciplines. Deployment is one of the key issues to be solved in WSNs, since the sensor nodes’ positioning affects highly the system performance. An optimal WSN deployment should maximize the collection of the desired interest phenomena, guarantee the required coverage and connectivity, extend the network lifetime, and minimize the network cost in terms of energy consumption. Most of the research effort in this area aims to solve the deployment issue, without minimizing the network cost by reducing unnecessary working nodes in the network. In this paper, we propose a deployment approach based on the gradient method and the Simulated Annealing algorithm to solve the sensor deployment problem with the minimum number of sensor nodes. The proposed algorithm is able to heuristically optimize the number of sensors and their positions in order to achieve the desired application requirements.

This work presents a quantitative evaluation of the quality of a set of mutation operators for WS-BPEL 2.0 (Web Services Business Process Execution Language), an OASIS standardized language for the composition of Web Services. A series of experiments is conducted, aiming to determine how selective operators are for the qualification of test cases and, more generally, the quality of the operators themselves. This includes a formalization of mutation testing defining the key concepts and measures employed. Three different compositions are considered and special attention is paid to the properties that suitable test-suites should enjoy.

Summary: Mutation testing is a successful testing technique based on fault injection. However, it can be very costly, and several cost‐reduction techniques for reducing the number of mutants have been proposed in the literature. Cost reduction can be aided by an analysis of mutation operators, but this requires the definition of specialized metrics. Several metrics have been proposed before, although their effectiveness and relative merits are not easy to assess. A step ahead in the evaluation of mutation‐reduction techniques would be a better metric to determine objectively the quality of a set of mutants with respect to a given test suite. This work introduces such a metric, which is naturally extended to mutation operators and may be used to reduce the number of mutants, particularly of equivalent mutants. Finally, a firm mutation analysis tool for WS‐BPEL service compositions is presented, and experimental results obtained by comparing different metrics on several compositions are presented. Copyright © 2014 John Wiley & Sons, Ltd.