Uncovering Dependence Clusters and Linchpin Functions

Dependence clusters are (maximal) collections of mutually dependent source code entities according to some dependence relation. Their presence in software complicates many maintenance activities including testing, refactoring, and feature extraction. Despite several studies finding them common in production code, their formation, identification, and overall structure are not well understood, partly because of challenges in approximating true dependences between program entities. Previous research has considered two approximate dependence relations: a fine-grained statement-level relation using control and data dependences from a program’s System Dependence Graph and a coarser relation based on function-level controlflow reachability. In principal, the first is more expensive and more precise than the second. Using a collection of twenty programs, we present an empirical investigation of the clusters identified by these two approaches. In support of the analysis, we consider hybrid cluster types that works at the coarser function-level but is based on the higher-precision statement-level dependences. The three types of clusters are compared based on their slice sets using two clustering metrics. We also perform extensive analysis of the programs to identify linchpin functions – functions primarily responsible for holding a cluster together. Results include evidence that the less expensive, coarser approaches can often be used as e�ective proxies for the more expensive, finer-grained approaches. Finally, the linchpin analysis shows that linchpin functions can be e�ectively and automatically identified.

Substance use and misuse in burn patients: testing the classical hypotheses of the interaction between posttraumatic symptomatology and substance use

Background: We aimed to test whether the three classical hypotheses of the interaction between posttraumatic symptomatology and substance use (high risk of trauma exposure, susceptibility for posttraumatic symptomatology, and self-medication of symptoms), may be useful in the understanding of substance use among burn patients. Methods: We analysed substance use data (nicotine, alcohol, cannabis, amphetamines, cocaine, opiates, and tranquilizers) and psychopathology measures among burn patients admitted to a Burns Unit and enrolled in a longitudinal observational study. Lifetime substance use information (n = 246) was incorporated to analyses aiming to test the high risk hypothesis. Only patients assessed for psychopathology in a six months follow-up (n = 183) were included in prospective analyses testing the susceptibility and self-medication hypotheses. Results: Regarding the high risk hypothesis, results show a higher proportion of heroin and tranquilizer users compared to the general population. Furthermore, in line with the susceptibility hypothesis, higher levels of symptomatology were found in lifetime alcohol, tobacco and drug users during recovery. The self-medication hypothesis could be tested partially due to the hospital stay “cleaning” effect, but severity of symptoms was linked to caffeine, nicotine, alcohol and cannabis use after discharge. Conclusions: We found that the three classical hypotheses could be used to understand the link between traumatic experiences and substance use explaining different patterns of burn patient’s risk for trauma exposure and emergence of symptomatology.