This paper presents an observational study that takes an initial step towards answering the question of how the selection of a programming paradigm affects the maintainability of a software system. Answers to this question are important because they can provide insight on how the maintainability characteristics of different programming paradigms could be leveraged to improve software-engineering education. The observational study compares developers' effectiveness and speed performing pre-determined maintenance tasks on two equivalent variations of a web-based application: one based on Procedural Programming and one based on Object-Oriented Programming. Presented within this paper are the study's design, metrics measuring maintenance effectiveness and speed, and a statistical analysis of the results, which provides evidence that the maintainability characteristics of the two paradigms are different within the context of this research. In addition, as an observational study, some of its important contributions are lessons learned about the experiment design process and ideas for new hypotheses. These are presented in preparation for a future, broader research, and larger-scale experiment. Finally, we discuss some forward-thinking ideas about how differences in the maintenance characteristics of programming paradigms may influence on software-engineering education.

Estimating the quality of Personal Identifiable Information (PII) creates a corresponding need to model and formalize PII for both the real-world and electronic data, in a way that supports rigorous reasoning relative to real-world constraints, rules from domain experts, and rules about expected data patterns. In this paper, we propose an extended first-order logic language (FOL), called PDFOL (Person Data First-order Logic), that can express these kinds of constraints and rules, as well as relevant person attributes and inter-person relations. We present the salient features of PDFOL, namely temporal predicated based on time intervals, aggregate functions, and tuple-set comparison operators. These features allow PDFOL to model person-centric databases, enabling formal and efficient reason about their quality. We show how PDFOL can express real-world constraints, expert opinions, and aggregate knowledge as closed PDFOL statements, which in turn can then be used to assess the quality of a database. We adapt and extend the traditional aggregate functions in three ways: a) allowing any arbitrary number free variables in function statement, b) adding groupings, and c) defining new aggregate function. We believe that this work will provide a foundation for future methods for reasoning about the quality of PII.

In an earlier study, we observed that students in a small graduate class who used Cloud Computing (CC) for their programming assignments improved their analysis-to-reuse (A2R) skills more than students who didn't use CC. That preliminary result motivated us to see if the use of CC in programming assignments would yield similar results for a broader range of classes and students. To this end, this paper reports on an observational study on the students of the Computer Science Department of Utah State University that spanned from August 2015 to December 2016 and included over 221 students, with data collected at three different times. An ANOVA statistical analysis of the study data revealed a significant difference in the perceptions about acquired A2R skills in favor of students that used CC.

Code offloading on mobile platforms has received much attention as a way of relieving heavy workload by utilizing power of the other devices or cloud servers. The offloading mechanisms rely on multiple platforms to be enabled on variety of mobile devices. To support platform heterogeneity, the execution code should be implemented in JavaScript and executed on the designate devices by correspondingly compatible JavaScript engine. In this paper, we present a novel distribution mechanism with a built-in JavaScript execution package, annotation processor and an engine to enable code offloading among the devices and servers in peer-to-peer (P2P) networks. This approach includes a set of constraints for code implementation so developers can easily integrate to their project. Our evaluation, based on a testbed with Android and Windows Phone devices, demonstrates the efficiency of offloading JavaScript-based packages on multiple devices, as well as compares the performance between JavaScript and native versions.

INTRODUCTION: Identity information is often used to link records within or among information systems in public health and clinical settings. The quality and stability of birth certificate identifiers impacts both the success of linkage efforts and the value of birth certificate registries for identity resolution. OBJECTIVE: Our objectives were to describe: (1) the frequency and cause of changes to birth certificate identifiers as children age, and (2) the frequency of events (ie, adoptions, paternities, amendments) that may trigger changes and their impact on names. METHODS: We obtained two de-identified datasets from the Utah birth certificate registry: (1) change history from 2000 to 2012, and (2) occurrences for adoptions, paternities, and amendments among births in 1987 and 2000. We conducted cohort analyses for births in 1987 and 2000, examining the number, reason, and extent of changes over time. We conducted cross-sectional analyses to assess the patterns of changes between 2000 and 2012. RESULTS: In a cohort of 48 350 individuals born in 2000 in Utah, 3164 (6.5%) experienced a change in identifiers prior to their 13th birthday, with most changes occurring before 2 years of age. Cross-sectional analysis showed that identifiers are stable for individuals over 5 years of age, but patterns of changes fluctuate considerably over time, potentially due to policy and social factors. CONCLUSIONS: Identities represented in birth certificates change over time. Specific events that cause changes to birth certificates also fluctuate over time. Understanding these changes can help in the development of automated strategies to improve identity resolution.

Rule-based deduplication utilizes expert domain knowledge to identify and remove duplicate data records. Achieving high accuracy in a rule-based system requires the creation of rules containing a good combination of discriminatory clues. Unfortunately, accurate rule-based deduplication often requires significant manual tuning of both the rules and the corresponding thresholds. This need for manual tuning reduces the efficacy of rule-based deduplication and its applicability to real-world data sets. No adequate solution exists for this problem. We propose a novel technique for rule-based deduplication. We apply individual deduplication rules, and combine the resultant match scores via learning-based information fusion. We show empirically that our fused deduplication technique achieves higher average accuracy than traditional rule-based deduplication. Further, our technique alleviates the need for manual tuning of the deduplication rules and corresponding thresholds.

article Free Access Share on Turnable formalism in object-oriented systems analysis: meeting the needs of both theoreticians and practitioners Authors: Stephen W. Clyde View Profile , David E. Embley View Profile , Scott N. Woodfield View Profile Authors Info & Claims ACM SIGPLAN NoticesVolume 27Issue 10Oct. 1992 pp 452–465https://doi.org/10.1145/141937.141972Published:31 October 1992Publication History 17citation355DownloadsMetricsTotal Citations17Total Downloads355Last 12 Months10Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF