IET Software最新文献

As more and more software teams use online issue tracking systems to collaborate on software projects, the accurate assignment of new issues to the most suitable contributors may have significant impact on the success of the project. As a result, several research efforts have been directed towards automating this process to save considerable time and effort. However, most approaches focus mainly on software bugs and employ models that do not sufficiently take into account the semantics and the non-textual metadata of issues and/or produce models that may require manual tuning. A methodology that extracts both textual and non-textual features from different types of issues is designed, providing a Jira dataset that involves not only bugs but also new features, issues related to documentation, patches, etc. Moreover, the semantics of issue text are effectively captured by employing a topic modelling technique that is optimised using the assignment result. Finally, this methodology aggregates probabilities from a set of individual models to provide the final assignment. Upon evaluating this approach in an automated issue assignment setting using a dataset of Jira issues, the authors conclude that it can be effective for automated issue assignment.

In the context of requirements specification in Global Software Development, aspects such as differences in culture, language and schedule affect software development teams; however, we do not know the effect of these issues. Compare the native language requirements with the foreign language requirements concerning external quality. We conducted a controlled experiment of one-factor two treatments within-subjects with 17 experimental subjects. Wilcoxon test indicates that there is evidence to reject the null hypothesis (p-value = 0.008); there is a statistically significant difference. The external quality value obtained with native language requirements is superior to the external quality produced with the foreign language. The effect size equals an absolute value of 0.45, which corresponds to a medium effect. The language used in the requirements specification influences the external quality; using the native language in the requirements specification significantly increases the external quality. The result obtained in this research should be considered to evaluate the roles and English language skills of GSD team members and their effect on external software quality. We also suggest considering the English language skills of the experimental subjects in the experimental laboratories since language could influence the results of the experiments.

Software faults are costly to find and remove from programs. It is better to avoid inserting the faults in the first place. The authors identify requirements-related faults that can arise during the transformation of formal specifications into programs, analyse each to discover its causes, and propose corresponding fault prevention methods. The approach works by analysing a specification, decomposing it into specification fragments with different levels like components, determining the correct implementation order among the components, and enabling automated code generation for the components and other low-level specification fragments. The approach seeks to reduce the faults in programs significantly by guiding programmers to work effectively and productively. The authors evaluate the approach's performance experimentally and compare it to the performance of a fault-prevention method with industry applications.

As agile software development and extreme programing have become increasingly popular, continuous integration (CI) has become a widely used collaborative work method. However, it is common to make changes frequently to a project during CI. If existing testing methods are applied to CI directly, it will be difficult to make testing resources focus on changes generated by CI, which results in insufficient testing for changes. To solve this problem, we propose a fuzz testing method for CI. First, differential analysis is performed to determine the change points generated during CI, change points are added to the taint source set, and static analysis is conducted to calculate the distances between each basic block and the taint sources. Then, the project under test is instrumented according to the distances. During fuzz testing, testing resources are allocated based on seed coverage to test the change points effectively. Using the proposed methods, we implement CIDFuzz as a prototype tool, and experiments are conducted on four open-source projects that use CI. Experimental results show that, compared with AFL and AFLGo, CIDFuzz can reduce the time costs of covering change points up to 39.59% and 41.64%, respectively. Also, CIDFuzz can reduce the time costs of reproducing vulnerabilities up to 34.78% and 25.55%.