Mining Fix Patterns for FindBugs Violations

In this paper, we first collect and track a large number of fixed and unfixed violations across revisions of software. The empirical analyses reveal that there are discrepancies in the distributions of violations that are detected and those that are fixed, in terms of occurrences, spread and categories, which can provide insights into prioritizing violations. To automatically identify patterns in violations and their fixes, we propose an approach that utilizes convolutional neural networks to learn features and clustering to regroup similar instances. We then evaluate the usefulness of the identified fix patterns by applying them to unfixed violations. The results show that developers will accept and merge a majority (69/116) of fixes generated from the inferred fix patterns. It is also noteworthy that the yielded patterns are applicable to four real bugs in the Defects4J major benchmark for software testing and automated repair.Comment: Accepted for IEEE Transactions on Software Engineerin

Anti-depressants and Suicide

Does drug treatment for depression with selective serotonin reuptake inhibitors (SSRIs) increase or decrease the risk of completed suicide? The question is important in part because of recent government warnings that question the safety of SSRIs, one of the most widely prescribed medications in the world. While there are plausible clinical and behavioral arguments that SSRIs could have either positive or negative effects on suicide, randomized clinical trials have not been very informative because of small samples and other problems. In this paper we use data from 26 countries for up to 25 years to estimate the effect of SSRI sales on suicide mortality using just the variation in SSRI sales that can be explained by cross-country variation in the growth of drug sales more generally. We find that an increase in SSRI sales of 1 pill per capita (about a 12 percent increase over 2000 sales levels) is associated with a decline in suicide mortality of around 5 percent. These estimates imply a cost per statistical life far below most other government interventions to improve health outcomes.

Ethical guidelines for nudging in information security & privacy

There has recently been an upsurge of interest in the deployment of behavioural economics techniques in the information security and privacy domain. In this paper, we consider first the nature of one particular intervention, the nudge, and the way it exercises its influence. We contemplate the ethical ramifications of nudging, in its broadest sense, deriving general principles for ethical nudging from the literature. We extrapolate these principles to the deployment of nudging in information security and privacy. We explain how researchers can use these guidelines to ensure that they satisfy the ethical requirements during nudge trials in information security and privacy. Our guidelines also provide guidance to ethics review boards that are required to evaluate nudge-related research

Role of information, cost-sharing, and payment reforms in health care markets

This dissertation analyzes the role of information, cost-sharing, and payment reforms in health care markets. The first chapter analyzes the impact on total medical costs of using a risk-adjusted comprehensive payment model, to support a patient-centered medical home. We compare insurance claims data on treatment and control practices from a network health plan in upstate New York. Practices in the treatment group embraced a risk-based comprehensive payment model, receiving risk-adjusted base payments and bonuses, compared with fee-for-service in the control group. We estimate the treatment effect using difference-in-differences and use propensity weights to address differences in exogenous variability between control and treatment patients. Our estimation results suggest that risk-based comprehensive payment model has notably dampened spending growth for the practices in the treatment group. Chapter two presents empirical evidence on the impact of patient reviews on consumers' physician choices. Our study extracted data from ZocDoc.com--a unique website that integrates patient reviews, and appointment scheduling for physicians on one platform. Our results suggest that patient reviews are becoming an important source of reputation for physicians. Because ZocDoc displays each physician's rounded average rating to patients, we can use regression discontinuity to identify the causal impact of patient ratings on patient demand. Indeed, we find that half a star improvement in ratings, on a scale of 1 to 5 stars, leads to a 10% increase in the likelihood, at the mean, that a doctor will fill an appointment. The third chapter examines the joint effect of FDA's drug risk communication and consumer cost-sharing on the consumption of prescription drugs. Given different levels of cost sharing, one should expect the consumer response to any negative information regarding a particular drug to be slower at lower levels of cost-sharing. However, as a competing hypothesis one can also expect that the response to a severe drug risk communication to be swift and not responsive to cost sharing. Using MarketScan's database of privately insured individuals in the United, I find that higher cost sharing indeed has a significant impact of how patients respond to drug risk communication, I find that higher cost sharing combined with drug risk communication reduces the compliance rate

A participatory qualitative analysis of barriers of public transport by persons with disabilities from seven European cities

Although there is literature published by a considerable number of scientific publications regarding disability and transport, the affected persons are only very rarely involved in the research. The paper presents the results of two qualitative studies conducted jointly with persons with different forms of disabilities: i) a social media content analysis and ii) peer-to-peer interviews with persons with disabilities (N = 49). The studies aimed to identify barriers that persons with access needs face during their trips with public transport. In line with a participatory approach, persons with disabilities from seven European cities were involved in conducting the research allowing for new interpretations of transport equity issues. Qualitative content analysis of both studies revealed barriers clustered into eight categories: regulations, public awareness and assistance, information provision and communication, infrastructure, vehicles, general service quality, stops and stations and emotional barriers. The two studies highlight important factors that influence disabled users’ experiences of public transport. Upon reflection, the paper derives research hypotheses and demonstrates the value of involving people with disabilities in the analysis of disability research to derive in-depth insights about equity in transport.Peer Reviewe

Police Misconduct:Mapping its location, seriousness and theoretical underpinning

Police misconduct and the location of street crimes and deviance have received much research attention. The location of police misconduct, by contrast, has not. Taking the case of Ireland, where policing underwent significant reform in 2007, police oversight data are mapped to determine the location and nature of complaints and any clustering of police misconduct, particularly in areas of greatest deprivation usually associated with people coming into most frequent contact with police. The implications of the findings for police, police oversight, and existing theories by which geography of deviance is framed are discussed

Automotive Collision Warning System Retrofit

In the early 2000s, few automakers began implementing forward collision warning systems in their cars. As technology advanced this system became available on more and more luxury cars. In recent years, this technology has spread to more affordable vehicles driven every day. However, as this technology has only recently advanced to less expensive, more economical cars, older vehicles of the same model may not have this advanced and important safety feature. This project investigates and creates a preliminary design for an affordable, easy-to-install, forward collision warning system that can be retrofitted to vehicles without the system currently installed. Using a density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm, an extended Kalman filter, and a time-to-collision algorithm, a forward collision warning system was developed and simulated using the Insurance Institute of Highway Safety (IIHS) test scenarios. Software testing and implementation was done in MATLAB and has provided a foundation for future hardware implementation using Texas Instruments mmWave automotive radar (AWR1843BOOST)