A Proposal For An Intelligent Debugging Assistant

There are many ways to find bugs in programs. For example, observed input and output values can be compared to predicted values. An execution trace can be examined to locate errors in control flow. The utility of these and other strategies depends on the quality of the specifications available. The Debugging Assistant chooses the most appropriate debugging strategy based on the specification information available and the context of the bug. Particular attention has been given to applying techniques from the domain of hardware troubleshooting to the domain of software debugging. This has revealed two important differences between the two domains: (1) Unlike circuits, programs rarely come with complete specifications of their behavior, and (2) Unlike circuits, the cost of probing inputs and outputs of programs is low.MIT Artificial Intelligence Laborator

Standardised Outcomes in Nephrology-Polycystic Kidney Disease (SONG-PKD): study protocol for establishing a core outcome set in polycystic kidney disease

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is the most common potentially life threatening inherited kidney disease and is responsible for 5-10% of cases of end-stage kidney disease (ESKD). Cystic kidneys may enlarge up to 20 times the weight of a normal kidney due to the growth of renal cysts, and patients with ADPKD have an increased risk of morbidity, premature mortality, and other life-time complications including renal and hepatic cyst and urinary tract infection, intracranial aneurysm, diverticulosis, and kidney pain which impair quality of life. Despite some therapeutic advances and the growing number of clinical trials in ADPKD, the outcomes that are relevant to patients and clinicians, such as symptoms and quality of life, are infrequently and inconsistently reported. This potentially limits the contribution of trials to inform evidence-based decision-making. The Standardised Outcomes in Nephrology-Polycystic Kidney Disease (SONG-PKD) project aims to establish a consensus-based set of core outcomes for trials in PKD (with an initial focus on ADPKD but inclusive of all stages) that patients and health professionals identify as critically important. METHODS: The five phases of SONG-PKD are: a systematic review to identify outcomes that have been reported in existing PKD trials; focus groups with nominal group technique with patients and caregivers to identify, rank, and describe reasons for their choices; qualitative stakeholder interviews with health professionals to elicit individual values and perspectives on outcomes for trials involving patients with PKD; an international three-round Delphi survey with all stakeholder groups (including patients, caregivers, healthcare providers, policy makers, researchers, and industry) to gain consensus on critically important core outcome domains; and a consensus workshop to review and establish a set of core outcome domains and measures for trials in PKD. DISCUSSION: The SONG-PKD core outcome set is aimed at improving the consistency and completeness of outcome reporting across ADPKD trials, leading to improvements in the reliability and relevance of trial-based evidence to inform decisions about treatment and ultimately improve the care and outcomes for people with ADPKD

Dependency-Directed Localization of Software Bugs

Software bugs are violated specifications. Debugging is the process that culminates in repairing a program so that it satisfies its specification. An important part of debugging is localization, whereby the smallest region of the program that manifests the bug is found. The Debugging Assistant (DEBUSSI) localizes bugs by reasoning about logical dependencies. DEBUSSI manipulates the assumptions that underlie a bug manifestation, eventually localizing the bug to one particular assumption. At the same time, DEBUSSI acquires specification information, thereby extending its understanding of the buggy program. The techniques used for debugging fully implemented code are also appropriate for validating partial designs

Tobacco use and cancer causation: association by tumour type.

In the second part of our review we describe the association between tobacco use and risk of specific cancer types. There is evidence for an established association of tobacco use with cancer of the lung and larynx, head and neck, bladder, oesophagus, pancreas, stomach and kidney. In contrast, endometrial cancer is less common in women who smoke cigarettes. There are some data suggesting that tobacco use increases the risk for myeloid leukaemia, squamous cell sinonasal cancer, liver cancer, cervical cancer, colorectal cancer after an extended latency, childhood cancers and cancer of the gall bladder, adrenal gland and small intestine. Other forms of cancer, including breast, ovarian and prostate cancer, are unlikely to be linked to tobacco use