Khaled El Emam

Testing the theory of relative defect proneness for closed-source software

Recent studies on open-source software (OSS) products report that smaller modules are proportionally more defect prone compared to larger ones. This phenomenon, referred to as the Theory of Relative Defect Proneness (RDP), challenges the traditional QA approaches that give a higher priority to larger modules, and it attracts growing interest from closed-source software (CSS) practitioners. In this paper, we report the findings of a study where we tested the theory of RDP using ten CSS products. The results clearly confirm the theory of RDP. We also demonstrate the useful practical implications of this theory in terms of defect-detection effectiveness. Therefore, this study does not only make research contributions by rigorously testing a scientific theory for a different category of software products, but also provides useful insights and evidence to practitioners for revising their existing QA practices.

A Review of Evidence on Consent Bias in Research

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Evaluation of rare event detection

This study analyzes evaluation measures for rare event detection We introduce a procedure which is built upon the characteristics of rare events We propose properties for evaluation measures which assess the measure applicability to classification of rare events Prevention of leaks of personal health information supports the empirical evidence.

Privacy and Anonymity Challenges When Collecting Data for Public Health Purposes

Two contemporary problems face public health professionals in collecting data from health care providers: the de-identification of geospatial information in a manner that still allows meaningful analysis, and ensuring that provider performance data (e.g., infection or screening rates) is complete and accurate. In this paper, we discuss new methods for de-identifying geographic information that will allow useful de-identified data to be disclosed to public health. In addition, we propose privacy preserving mechanisms that will likely encourage providers to disclose complete and accurate data. However, this must be accompanied by steps to grow trust between the providers and public health.

Efficient Privacy-Preserving Identity Scheme for Electronic Validation of Phase 1 Clinical Trials

New drug studies are essential to advance the pharmaceutical industry’s ability to fight diseases. These studies are typically performed in four phases. We are interested in “phase 1” clinical trials where the goal is to evaluate the safety of a new drug. Contract research organizations recruit participants for their studies and need to verify electronically certain criteria without revealing the identity of these participants to other organizations. We outline some potential attacks against current identity representation schemes. Afterwards, we present privacy-preserving techniques to represent the identity of a participant in a scheme where operations can be performed efficiently and accurately. Our methods and scheme can also be applied to other domains to preserve an individual’s privacy.

The Ethical Merits of Nudges in the Clinical Setting

Nudging, or choice architecture, has become a more prominent concept in medicine. Some regard simple framing techniques or reminders as beneficial to patients, improving overall health; others rega...

A privacy preserving protocol for tracking participants in phase I clinical trials

OBJECTIVEnSome phase 1 clinical trials offer strong financial incentives for healthy individuals to participate in their studies. There is evidence that some individuals enroll in multiple trials concurrently. This creates safety risks and introduces data quality problems into the trials. Our objective was to construct a privacy preserving protocol to track phase 1 participants to detect concurrent enrollment.nnnDESIGNnA protocol using secure probabilistic querying against a database of trial participants that allows for screening during telephone interviews and on-site enrollment was developed. The match variables consisted of demographic information.nnnMEASUREMENTnThe accuracy (sensitivity, precision, and negative predictive value) of the matching and its computational performance in seconds were measured under simulated environments. Accuracy was also compared to non-secure matching methods.nnnRESULTSnThe protocol performance scales linearly with the database size. At the largest database size of 20,000 participants, a query takes under 20s on a 64 cores machine. Sensitivity, precision, and negative predictive value of the queries were consistently at or above 0.9, and were very similar to non-secure versions of the protocol.nnnCONCLUSIONnThe protocol provides a reasonable solution to the concurrent enrollment problems in phase 1 clinical trials, and is able to ensure that personal information about participants is kept secure.