Software Quality Journal

Automated test data generation is a traditional technique for reducing the cost and time of software testing. Various metaheuristic techniques have been successfully applied for this task. In contrast to the typical metaheuristic algorithms applied for branch and path coverage, this study focused on low resource consumption and efficient information coverage for critical path coverage. First, we combined the characteristics of branch coverage and path coverage to determine a critical path based on quantified path scores. As a result, we constructed a fine-grained fitness function based on the uniform scale branch distance. Second, we proposed an adaptive particle swarm optimization (MCD-APSO) algorithm with multiple convergence directions to accelerate convergence and escape from local optima. The proposed MCD-APSO algorithm improved the global search ability by enriching the diversity of the particle swarm and enhancing the current evolutionary information use of the particles. Finally, to validate the performance of the MCD-APSO algorithm, we compared the proposed algorithm with six test-data generation algorithms on six normal-scale and six large-scale benchmark programs. The results showed that the MCD-APSO algorithm outperforms the benchmark programs regarding the mean number of iterations, total running time, and coverage failure probability.

This paper suggests that by operationalizing the concept of commitment in the shape of a model, a new insight is provided in improving software processes—a more human centered approach as opposed to various technical approaches available. In doing so the SPI managers/change agents are able to plan better the software process improvement initiative and benchmark successful projects (as well as failed ones). Results from five interviews with SPI professionals on the proposed Behavior-based Commitment Model are reported, together with early results from the empirical test in 14 software process improvement projects. Early results suggest that the behaviors introduced in the model are relevant in SPI initiatives, the use of model raises the awareness about the people issues in improving processes, and the model could be used aside with CMM, SPICE or other process improvement models.

Testing software that has a GUI is difficult. Manual testing is costly and error-prone, but recorded test cases frequently “break” due to changes in the GUI. Test cases intended to test business logic must therefore be converted to a less “brittle” form to lengthen their useful lifespan. In this paper, we describe BlackHorse, an approach to doing this that converts a recorded test case to Java code that bypasses the GUI. The approach was implemented within the testing environment of Research In Motion. We describe the design of the toolset and discuss lessons learned during the course of the project.

Strategic management is a key discipline that permits companies to achieve their competitive goals. An effective and explicit alignment and integration of business strategy with SPI initiatives based on measurement is essential to prevent loss of income, customers and competitiveness. By integrating SPI models and measurement techniques in the strategy management process, an organization’s investments will be better aligned with strategy, optimizing the benefits obtained as a result of an SPI program. In this paper, the authors propose BOQM (Balanced Objective-Quantifiers Methodology) that integrates properly strategic management, process improvement and quantitative measurement to manage the competitiveness of software engineering organizations. Finally, this paper presents and discusses the results from implementing BOQM in a software development organization.

Software failures in medical devices can lead to catastrophic situations. Therefore, it is crucial to handle software-related risks when developing medical devices, and there is a need for further analysis of how this type of risk management should be conducted. The objective of this paper is to collect and summarise experiences from conducting risk management with an organisation developing medical devices. Specific focus is put on the first steps of the risk management process, i.e. risk identification, risk analysis, and risk planning. The research is conducted as action research, with the aim of analysing and giving input to the organisation’s introduction of a software risk management process. First, the method was defined based on already available methods and then used. The defined method focuses on user risks, based on scenarios describing the expected use of the medical device in its target environment. During the use of the method, different stakeholders, including intended users, were involved. Results from the case study show that there are challenging problems in the risk management process with respect to definition of the system boundary and system context, the use of scenarios as input to the risk identification, estimation of detectability during risk analysis, and action proposals during risk planning. It can be concluded that the risk management method has potential to be used in the development organisation, although future research is needed with respect to, for example, context limitation and how to allow for flexible updates of the product.

In recent years, open-source software (OSS) has attracted increasing attention due to its easy accessibility via cloud repositories, voluntary community, no vendor lock-in, and low total cost of ownership. In turn, specifying and evaluating OSS quality has become a significant challenge for OSS adoption in organizations that are inclined to use them. Although many OSS quality models have been proposed in the literature, the dynamic and diverse nature of OSS has caused these models to be heterogeneous in terms of structure and content. This has adversely affected the standardization of evaluations and led to the evaluation results obtained from different OSS quality models for the same purpose being incomparable and sometimes unreliable. Therefore, in this study, a meta-model for OSS quality (OSS-QMM), which employs a unified structure from existing quality models and enables the derivation of homogeneous models, has been proposed. For this purpose, a systematic and laborious effort has been spent via a step-based meta-model creation process including review-and-revise iterations. In order to validate the OSS-QMM, case study and expert opinion methods have been applied to answer three research questions (RQs) targeted to investigate practical applicability, results comparability, and effectiveness of using the meta-model. Multiple and embedded case study designs have been employed for evaluating three real ERP systems, and 20 subject matter experts have been interviewed during the validation process. The results of multi-faceted empirical studies have indicated that the OSS-QMM has addressed solving problems in OSS quality evaluation and its adoption with high degrees of confidence.