How the Sando Search Tool Recommends Queries

Developers spend a significant amount of time searching their local codebase. To help them search efficiently, researchers have proposed novel tools that apply state-of-the-art information retrieval algorithms to retrieve relevant code snippets from the local codebase. However, these tools still rely on the developer to craft an effective query, which requires that the developer is familiar with the terms contained in the related code snippets. Our empirical data from a state-of-the-art local code search tool, called Sando, suggests that developers are sometimes unacquainted with their local codebase. In order to bridge the gap between developers and their ever-increasing local codebase, in this paper we demonstrate the recommendation techniques integrated in Sando

Surveying Persons with Disabilities: A Source Guide (Version 1)

As a collaborator with the Cornell Rehabilitation Research and Training Center on Disability Demographics and Statistics, Mathematica Policy Research, Inc. has been working on a project that identifies the strengths and limitations in existing disability data collection in both content and data collection methodology. The intended outcomes of this project include expanding and synthesizing knowledge of best practices and the extent existing data use those practices, informing the development of data enhancement options, and contributing to a more informed use of existing data. In an effort to provide the public with an up-to-date and easily accessible source of research on the methodological issues associated with surveying persons with disabilities, MPR has prepared a Source Guide of material related to this topic. The Source Guide contains 150 abstracts, summaries, and references, followed by a Subject Index, which cross references the sources from the Reference List under various subjects. The Source Guide is viewed as a “living document,” and will be periodically updated

On the Generation, Structure, and Semantics of Grammar Patterns in Source Code Identifiers

Identifier names are the atoms of program comprehension. Weak identifier names decrease developer productivity and degrade the performance of automated approaches that leverage identifier names in source code analysis; threatening many of the advantages which stand to be gained from advances in artificial intelligence and machine learning. Therefore, it is vital to support developers in naming and renaming identifiers. In this paper, we extend our prior work, which studies the primary method through which names evolve: rename refactorings. In our prior work, we contextualize rename changes by examining commit messages and other refactorings. In this extension, we further consider data type changes which co-occur with these renames, with a goal of understanding how data type changes influence the structure and semantics of renames. In the long term, the outcomes of this study will be used to support research into: (1) recommending when a rename should be applied, (2) recommending how to rename an identifier, and (3) developing a model that describes how developers mentally synergize names using domain and project knowledge. We provide insights into how our data can support rename recommendation and analysis in the future, and reflect on the significant challenges, highlighted by our study, for future research in recommending renames

Transfer of learning from simulation to clinical practice in pre-registration healthcare student education.

Simulation has become an established pedagogy for teaching clinical skills to healthcare professionals and has been incorporated into pre-registration curricula internationally. Simulation can often be used to replace clinical practice hours and it is projected that the use of simulation will rise as placement opportunities decline. Simulation is also both resource and cost-intensive. Therefore, it becomes incumbent on educators to demonstrate the effectiveness of simulation. The broad purpose of this thesis is to extend the healthcare education knowledge base around the transfer of clinical skills to clinical practice after simulation. Three studies were undertaken, each with their own discrete aims. Firstly, an integrative literature review, to identify what evidence exists to support transfer of learning following simulation activities to clinical practice. Secondly, an explanatory sequential mixed-methods study, to ascertain and explore nurse academics’ views on current practice in Scottish higher education institutions (HEIs) in relation to the use of simulation best-practice statements and staff development. Thirdly, a convergent mixed-methods feasibility study exploring the parameters of evaluating the transfer of learning respiratory assessment skills from simulation to clinical practice for healthcare students. The paradigm underpinning this work is pragmatism using an iterative mixed-methods approach, which was applied in the following way: 1) an integrative review on transfer of learning; 2) an explanatory sequential mixed-methods study incorporated an e-Delphi study followed by telephone interviews that were thematically analysed using a qualitative descriptive approach; 3) a convergent mixed-methods study design was adopted for the feasibility study, so that quantitative data from questionnaires and qualitative data from interviews could be integrated. The integrative review found that there is limited published evidence on the effectiveness of simulation transferring to clinical practice in both health care education generally and pre-registration nurse education specifically. The current evidence-base could be improved by improving methodological rigor and being transparent around the intervention of simulation. The explanatory sequential mixed-methods study found that differences in simulation practices across Scottish HEIs were reported; however, participants unanimously agreed that they would welcome the use of simulation best practice statements in the future. They also identified a need for staff development and leadership in simulation. Whilst there are challenges involved in conducting studies evaluating transfer of learning to practice, such as the length of time required, the feasibility study demonstrated that a larger study would be worthwhile and so parameters of a future main study were explored. In conclusion, this thesis developed some key recommendations for both research and educational practice. Research into the effectiveness of simulation to transfer skills to clinical practice could be enhanced by greater collaboration between HEIs, which would enable larger samples to be reached across multiple research sites. Adopting a quasi-experimental research design might avoid methodological limitations of previous simulation evaluation studies. If institutions collaborated, then tools to evaluate the transfer of skills after simulation to clinical practice could be validated. The intervention of simulation could be strengthened using best-practice statements, which would standardise future multi-site research. Recommendations for educational practice in Scottish HEIs include the following: stronger leadership for simulation to drive and promote change; development in simulation pedagogy for healthcare educators; the use of simulation best-practice statements to provide a framework for simulation educators to standardise, evaluate and improve simulation activities; the introduction of simulation champions intra-institution to mentor, guide and support simulation educators (this could include sharing of simulation resources nationally); Scottish Schools of Nursing are currently not able to consider simulation as a significant replacement for clinical hours

Automated Software Transplantation

Automated program repair has excited researchers for more than a decade, yet it has yet to find full scale deployment in industry. We report our experience with SAPFIX: the first deployment of automated end-to-end fault fixing, from test case design through to deployed repairs in production code. We have used SAPFIX at Facebook to repair 6 production systems, each consisting of tens of millions of lines of code, and which are collectively used by hundreds of millions of people worldwide. In its first three months of operation, SAPFIX produced 55 repair candidates for 57 crashes reported to SAPFIX, of which 27 have been deem as correct by developers and 14 have been landed into production automatically by SAPFIX. SAPFIX has thus demonstrated the potential of the search-based repair research agenda by deploying, to hundreds of millions of users worldwide, software systems that have been automatically tested and repaired. Automated software transplantation (autotransplantation) is a form of automated software engineering, where we use search based software engineering to be able to automatically move a functionality of interest from a ‘donor‘ program that implements it into a ‘host‘ program that lacks it. Autotransplantation is a kind of automated program repair where we repair the ‘host‘ program by augmenting it with the missing functionality. Automated software transplantation would open many exciting avenues for software development: suppose we could autotransplant code from one system into another, entirely unrelated, system, potentially written in a different programming language. Being able to do so might greatly enhance the software engineering practice, while reducing the costs. Automated software transplantation manifests in two different flavors: monolingual, when the languages of the host and donor programs is the same, or multilingual when the languages differ. This thesis introduces a theory of automated software transplantation, and two algorithms implemented in two tools that achieve this: µSCALPEL for monolingual software transplantation and τSCALPEL for multilingual software transplantation. Leveraging lightweight annotation, program analysis identifies an organ (interesting behavior to transplant); testing validates that the organ exhibits the desired behavior during its extraction and after its implantation into a host. We report encouraging results: in 14 of 17 monolingual transplantation experiments involving 6 donors and 4 hosts, popular real-world systems, we successfully autotransplanted 6 new functionalities; and in 10 out of 10 multlingual transplantation experiments involving 10 donors and 10 hosts, popular real-world systems written in 4 different programming languages, we successfully autotransplanted 10 new functionalities. That is, we have passed all the test suites that validates the new functionalities behaviour and the fact that the initial program behaviour is preserved. Additionally, we have manually checked the behaviour exercised by the organ. Autotransplantation is also very useful: in just 26 hours computation time we successfully autotransplanted the H.264 video encoding functionality from the x264 system to the VLC media player, a task that is currently done manually by the developers of VLC, since 12 years ago. We autotransplanted call graph generation and indentation for C programs into Kate, (a popular KDE based test editor used as an IDE by a lot of C developers) two features currently missing from Kate, but requested by the users of Kate. Autotransplantation is also efficient: the total runtime across 15 monolingual transplants is 5 hours and a half; the total runtime across 10 multilingual transplants is 33 hours

Off-Label and Unlicensed Medicines' Related Problems in Paediatric In-Patients

Background: Current legislations such as paediatric investigation plan (PIP) require pharmaceutical companies seeking marketing authorisation for a new medicine to provide evidence of studies in paediatrics to justify the use of such medicine in this population. In spite of these legislations, there are still challenges with conduct of clinical trials in paediatrics; thus, there is lack of commercially available dosage forms appropriate for use in this population. Consequently, a good proportion of medicines used in treating paediatric patients are used in the unlicensed (UL) or off-label (OL) manner. Use of UL or OL medicines has been associated with higher safety incidents such as, adverse drug reactions (ADRs) than licensed medicines. ADRs are only a subset of medicine related problems (MRPs) associated with the use of medicines. Currently, no studies have explored all aspects of problems associated with the use of OL and UL medicines in paediatrics. Aim: To investigate the prevalence of the use of OL and UL medicines and problems associated with their use in paediatrics patients admitted to intensive care units of a Children’s Hospital. Method: A systematic literature review was carried out to identify problems that are associated with the use of OL and UL medicines. A retrospective review of case notes (n=194) of patients who were admitted to Paediatric Intensive Care Unit (PICU) was carried out at medical records units of the hospital. This was followed by a prospective review of case notes (n=147) of patients admitted to PICU. The last study involved a prospective review of case notes (n=87) admitted to Neonatal Intensive Care Unit (NICU); NICU had migrated to electronic prescribing at the time the study was carried out. Licensing status of medicines was determined using Summary of Product Characteristics of medicines. Definition and categories of MRPs were based on the Pharmaceutical Care Network Europe classification system version 6.2. Naranjo causality scale was used to identify the medicines that was associated with MRPs. Severity and preventability of identified MRPs were assessed using the National Patient Safety Agency categorisation for level of harm and Schumock and Thornton scale respectively. Data was analysed using computer programmes including Excel, Statistical Package for the Social Sciences and STATA. Results: In the retrospective study, 53% of the total number of patients developed at least one MRP and 8% (n=165/2000) of the total number of medicines were associated with MRPs. From the total number of MRPs, 43% were associated with licensed medicines, while 57% were associated with OL and/or UL medicines. Identified MRPs were mostly ADRs and treatment effectiveness problems (84% vs.16%). In the prospective PICU study, 66% of the total number of patients developed at least one MRP and 11% (n=178/1578) of prescribed medicines were associated with MRPs. From the total number of MRPs, 40.4% were associated with licensed medicines, while 59.6% were associated with OL and/or UL medicines. Among the identified MRPs, 83% were ADRs and 17% were treatment effectiveness problems. In the NICU study, 90% of the patients developed MRPs and 9% (n= 186/1978) of the total number of medicines were associated with MRPs. From the total number of MRPs, 55% were associated with licensed medicines, while 45% were associated with OL and/or UL medicines. All the identified MRPs were ADRs. Conclusion: This research is the first to investigate MRPs associated with the use of OL and UL medicines in paediatric in-patients. MRPs associated with the use of OL and UL medicines were higher than with the use of licensed medicines. Inclusion of paediatrics in clinical trials of new medicines is fundamental to reducing the use of OL and UL medicines and the problems associated with their use

The impact of computerised physician order entry with integrated clinical decision support on pharmacist-physician communication in the hospital setting

An analysis of over 34,000 free-text messages assigned by pharmacists to prescription orders over a 12-month period showed a sub-optimal exchange of information with the physician. Focus groups and observational research were conducted to provide a more in-depth understanding of the factors involved. The use of CPOE did not reduce opportunities for personal interaction. The capability to communicate electronically facilitated a non-interruptive workflow, beneficial for staff time and for limiting distractions. It also improved clinical documentation, which helped coordinate care of patients between members of the pharmacy team. However, the research identified several barriers to the effectiveness of communication via the CPOE system, including: the increased frequency of messages sent; poor display characteristics of the message; poor access to information to inform decision-making; one-way communication; and no assigned responsibility to respond. These factors need to be considered in the design of systems and supported by interprofessional training to optimise communication between the professionals

Experience matters: women's experience of care during facility-based childbirth. A mixed-methods study on postpartum outcomes

Background: The poor treatment women are receiving during facility-based childbirth is an escalating global issue with potentially adverse postnatal consequences. My thesis aims to enhance understanding of these consequences, with a focus on postnatal care-seeking behaviour, maternal mental health and breastfeeding patterns in Tucumán, Argentina. / Objective: I sought to investigate the impact of mistreatment during childbirth (MDC) on postnatal outcomes and explore the influence of individual, interpersonal and societal factors on this relationship. / Methods: Employing a pragmatic epistemological framework, I adopted a mixed-methods approach. First, a systematic review of existing literature on mistreatment and its postnatal effects provided a comprehensive foundation for my research. Subsequently, I conducted semi-structured interviews and focus group discussions with women from an underserved community in Tucumán to gain qualitative insights. To complement this, I carried out a prospective cohort study with women who delivered in a public maternity hospital. Data analysis involved using the capability, opportunity, motivation, and behaviour (COM-B) model, directed acyclic graphs, and factor analysis to examine behavioural impacts, association pathways, and operationalisation of MDC. Multivariable models were applied to measure the association between MDC and postnatal outcomes. / Results: The study revealed that MDC should not be operationalised as a single construct, as women perceive breaches of quality of care differently from direct physical or verbal abuse. Health literacy, social support and self-esteem were identified as psychosocial confounders in the relationship between mistreatment and postnatal outcomes. Only 26% of women in the cohort study in Tucumán accessed postnatal care, with incidences of postpartum depression and anxiety of 67% and 21%, respectively. No statistically significant association was found between MDC and care seeking behaviour, although a possible trend emerged suggesting the women experiencing physical or verbal MDC could be more likely to seek care than those who were not mistreated. / Conclusion: Several exploratory hypotheses are presented to explain the trend suggesting that women who are verbally or physically mistreated are more prone to seek care after birth. Additionally, three concrete contributions emerged from this work: 1) the need to differentiate the conceptualisation of MDC from its operationalisation when assessing postnatal effects; 2) the importance of integrating psychosocial factors into the theory of change when designing effective interventions, and 3) the urgency of enhancing postnatal care access to improve maternal and newborn health outcomes, regardless of women’s childbirth experiences

Surveying Persons with Disabilities: A Source Guide

In 2003, The National Institute on Disability and Rehabilitation Research (NIDRR) funded a Rehabilitation Research and Training Center on Disability Demographics and Statistics (StatsRRTC) at Cornell University‘s Employment and Disability Institute (EDI). The goal of the Center is to ―explore the reliability of existing data sources and collection methods and evaluate ways to improve and expand current data collection efforts‖ (EDI 2008). As a collaborator with the StatsRRTC, Mathematica Policy Research, Inc. (MPR), has been working on a project that identifies the strengths and limitations in existing disability data collection in both content and data collection methodology. The intended outcomes of this project include expanding and synthesizing knowledge of best practices and the extent to which existing data use those practices, informing the development of data enhancement options, and contributing to a more informed use of existing data