Mutation of Directed Graphs -- Corresponding Regular Expressions and Complexity of Their Generation

Directed graphs (DG), interpreted as state transition diagrams, are traditionally used to represent finite-state automata (FSA). In the context of formal languages, both FSA and regular expressions (RE) are equivalent in that they accept and generate, respectively, type-3 (regular) languages. Based on our previous work, this paper analyzes effects of graph manipulations on corresponding RE. In this present, starting stage we assume that the DG under consideration contains no cycles. Graph manipulation is performed by deleting or inserting of nodes or arcs. Combined and/or multiple application of these basic operators enable a great variety of transformations of DG (and corresponding RE) that can be seen as mutants of the original DG (and corresponding RE). DG are popular for modeling complex systems; however they easily become intractable if the system under consideration is complex and/or large. In such situations, we propose to switch to corresponding RE in order to benefit from their compact format for modeling and algebraic operations for analysis. The results of the study are of great potential interest to mutation testing

Convocation of Thanks

The text of speeches delivered at the annual Convocation of Thanks ceremony, in remembrance of those who donated their bodies to the NYMC gross anatomy program

Assessing Resources Devoted to Electronic Reporting and Automation Among Central Cancer Registries Meeting National Program of Cancer Registries (NPCR) Quality Standards

The Centers for Disease Control and Prevention (CDC) has emphasized a need for data modernization initiatives (DMIs) to improve the quality and timeliness of cancer surveillance data. To guide such DMI efforts, we need data on the resources required to generate high-quality data. Twenty-one central cancer registries (CCRs) collected data from July 2020 to June 2021. We explored the potential relationship between resources for (1) electronic reporting and automation and (2) the quality of CCR data. We then compared activity-based costs of registries that always (n = 8), sometimes (n = 6), or seldom/never (n = 7) met data quality standards for completeness, timeliness, duplicate rate, and missing values. We found the registries that consistently met data quality standards used more resources on setting up processes to acquire data, training staff, and processing data. Compared to high-quality registries, registries that seldom/never met quality standards spent the most on case finding/data abstraction of non-hospital records. This study provides key findings for resource use, which can guide advancements when implementing electronic reporting and automation to improve CCR operations

A process for managing interaction between experimenters to get useful similar replications

Context: A replication is the repetition of an experiment. Several efforts have been made to adopt replication as a common practice in software engineering. There are different types of replications, depending on their purpose. Similar replications keep the experimental conditions as alike as possible to the original ones. External similar replications, where the replicating experimenters are not the same people as the original experimenters, have been a stumbling block. Several attempts at combining the results of replications have resulted in failure. Software engineering does not appear to be well suited to such replications, because it works with complex experimentally immature contexts. Software engineering settings have a large number of variables, and the role that many of them play is unknown. A successful (or useful) similar replication helps to better understand the phenomenon under study by verifying results and/or identifying contextual variables that could influence (or not) the results, through the combination of experimental results. Objective: To be able to get successful similar replications, there needs to be interaction between original and replicating experimenters. In this paper, we propose an interaction process for achieving successful similar replications. Method: This process consists of: an adaptation meeting, where experimenters tailor the experiment to the new setting; querying, to settle occasional inquiries while the experiment is being run; and a combination meeting, where experimenters meet to discuss the combination of replication outcomes with previous results. To check its effectiveness, the process has been tested on three different replications of the same experiment. Results: The proposed interaction process has helped to identify new contextual variables that could potentially influence (or not) the experimental results in the three replications run. Additionally, the interaction process has helped to uncover certain problems and deviations that occurred during some of the replications that we would have not been aware of otherwise. Conclusions: There are signs that suggest that it is possible to get successful similar replications in software engineering experimentation, when there is appropriate interaction among experimenters.This work has been performed under research Grant TIN2011-23216 of the Spanish Ministry of Science and Innovation.Juristo, N.; Vegas, S.; Solari, M.; Abrahao Gonzales, SM.; Ramos, I. (2013). A process for managing interaction between experimenters to get useful similar replications. Information and Software Technology. 55(2):215-225. https://doi.org/10.1016/j.infsof.2012.07.016S21522555