Cause Clue Clauses: Error Localization using Maximum Satisfiability

Much effort is spent everyday by programmers in trying to reduce long, failing execution traces to the cause of the error. We present a new algorithm for error cause localization based on a reduction to the maximal satisfiability problem (MAX-SAT), which asks what is the maximum number of clauses of a Boolean formula that can be simultaneously satisfied by an assignment. At an intuitive level, our algorithm takes as input a program and a failing test, and comprises the following three steps. First, using symbolic execution, we encode a trace of a program as a Boolean trace formula which is satisfiable iff the trace is feasible. Second, for a failing program execution (e.g., one that violates an assertion or a post-condition), we construct an unsatisfiable formula by taking the trace formula and additionally asserting that the input is the failing test and that the assertion condition does hold at the end. Third, using MAX-SAT, we find a maximal set of clauses in this formula that can be satisfied together, and output the complement set as a potential cause of the error. We have implemented our algorithm in a tool called bug-assist for C programs. We demonstrate the surprising effectiveness of the tool on a set of benchmark examples with injected faults, and show that in most cases, bug-assist can quickly and precisely isolate the exact few lines of code whose change eliminates the error. We also demonstrate how our algorithm can be modified to automatically suggest fixes for common classes of errors such as off-by-one.Comment: The pre-alpha version of the tool can be downloaded from http://bugassist.mpi-sws.or

Students' self-beliefs, attitudes and behaviours in school friendship and acquaintance groups

The broad aim of this research was to investigate group work in schools with friends and acquaintances. More specifically, the study sought to identify motivational factors that may underlie students' attitudes and behaviours when working in these contexts. Independent and interdependent self-construal, and self-efficacy for group work, were identified as variables that may be important for working in friendship and acquaintance groups. The participants were Year 10 and Year 11 students from secondary schools in the metropolitan area of Sydney, Australia. Data collection was carried out in three phases, the first two were survey-based, and the third was a mixed-methods study. In phase 1, participants (N = 188) attended two Independent schools. The main data analyses comprised exploratory factor analysis and multiple regression analysis. In phase 2, the participants (N = 583) attended nine randomly selected public schools. Data analysis was carried out using confirmatory factor analysis and structural equation modelling. In phase 3, participants (N = 38), attended two randomly selected public schools. In this phase, survey, observational and interview data were collected and analysed. The observational analysis centred on how students in friendship and acquaintance groups interacted whilst working on a group problem-solving activity. The interviews focused on students' experiences in the group problem-solving activity and their general perceptions, beliefs, and feelings about group work with friends and acquaintances. Group performance in the problem-solving activity was measured. Two results seemed particularly important. First, was the suggestion that self-efficacy for being receptive to the ideas of others and- self-efficacy for group facilitation in the friendship context may "flow-on" to corresponding self-efficacy beliefs in the acquaintance context. Second, interdependent and independent self, and self-efficacy for group work, were identified as important variables with regard to students' attitudes and behaviours in friendship and acquaintance groups. From a theoretical perspective the focus in this research on self-beliefs represents a relatively new way of studying group work with friends and acquaintances. From a practical perspective, the findings from the research should provide direction for teachers when they make decisions about how to organize students into groups for the purposes of learning

Environmental risk assessment of PPP application in European soils and potential ecosystem service losses considering impacts on non-target organisms

The use of Plant Protection Products (PPPs) is leading to high exposure scenarios with potential risk to soil organisms, including non-target species. Assessment of the effects of PPPs on non-target organisms is one of the most important components of environmental risk assessment (ERA) since they play crucial functions in ecosystems, being main driving forces in different soil processes. As part of the framework, EFSA is proposing the use of the ecosystem services approach for setting specific protection goals. In fact, the services provided by soil organisms can be impacted by the misuse of PPPs in agroecosystems. The aim of this work was to assess PPPs potential risk upon ecosystem services along European soils, considering impacts on earthworms and collembola. Four well-known (2 insecticides-esfenvalerate and cyclaniliprole- and 2 fungicides - picoxystrobin and fenamidone-) worst case application (highest recommended application) were studied; exploring approaches for linked observed effects with impacts on ecosystem services, accounting for their mode of action (MoA), predicted exposure, time-course effects in Eisenia fetida and Folsomia sp. and landscape variability. The selected fungicides exerted more effects than insecticides on E. fetida, whereas few effects were reported for both pesticides regarding Folsomia sp. The most impacted ecosystem services after PPP application to crops appeared to be habitat provision, soil formation and retention, nutrient cycling, biodiversity, erosion regulation, soil remediation/waste treatment and pest and disease regulation. The main factors to be taken into account for a correct PPP use management in crops are discussed.This work has been partially funded by European Food Safety Authority (EFSA) through the grant NP/EFSA/AFSCO/2016/03. The author Miguel J.G. Santos is employed with the EFSA in the PREV Unit. The author Jose V Tarazona was employed by EFSA until October 2022. The present article is published under the sole responsibility of the au thors and may not be considered as an EFSA scientific output. The po sitions and opinions presented in this article are those of the authors alone and do not represent the views of EFSA.S

Disrupted Peyer’s Patch Microanatomy in COVID-19 Including Germinal Centre Atrophy Independent of Local Virus

Confirmed SARS-coronavirus-2 infection with gastrointestinal symptoms and changes in microbiota associated with coronavirus disease 2019 (COVID-19) severity have been previously reported, but the disease impact on the architecture and cellularity of ileal Peyer’s patches (PP) remains unknown. Here we analysed post-mortem tissues from throughout the gastrointestinal (GI) tract of patients who died with COVID-19. When virus was detected by PCR in the GI tract, immunohistochemistry identified virus in epithelium and lamina propria macrophages, but not in lymphoid tissues. Immunohistochemistry and imaging mass cytometry (IMC) analysis of ileal PP revealed depletion of germinal centres (GC), disruption of B cell/T cell zonation and decreased potential B and T cell interaction and lower nuclear density in COVID-19 patients. This occurred independent of the local viral levels. The changes in PP demonstrate that the ability to mount an intestinal immune response is compromised in severe COVID-19, which could contribute to observed dysbiosis

LNCS

Static program analyzers are increasingly effective in checking correctness properties of programs and reporting any errors found, often in the form of error traces. However, developers still spend a significant amount of time on debugging. This involves processing long error traces in an effort to localize a bug to a relatively small part of the program and to identify its cause. In this paper, we present a technique for automated fault localization that, given a program and an error trace, efficiently narrows down the cause of the error to a few statements. These statements are then ranked in terms of their suspiciousness. Our technique relies only on the semantics of the given program and does not require any test cases or user guidance. In experiments on a set of C benchmarks, we show that our technique is effective in quickly isolating the cause of error while out-performing other state-of-the-art fault-localization techniques

Responsibility Analysis by Abstract Interpretation

Given a behavior of interest in the program, statically determining the corresponding responsible entity is a task of critical importance, especially in program security. Classical static analysis techniques (e.g. dependency analysis, taint analysis, slicing, etc.) assist programmers in narrowing down the scope of responsibility, but none of them can explicitly identify the responsible entity. Meanwhile, the causality analysis is generally not pertinent for analyzing programs, and the structural equations model (SEM) of actual causality misses some information inherent in programs, making its analysis on programs imprecise. In this paper, a novel definition of responsibility based on the abstraction of event trace semantics is proposed, which can be applied in program security and other scientific fields. Briefly speaking, an entity ER is responsible for behavior B, if and only if ER is free to choose its input value, and such a choice is the first one that ensures the occurrence of B in the forthcoming execution. Compared to current analysis methods, the responsibility analysis is more precise. In addition, our definition of responsibility takes into account the cognizance of the observer, which, to the best of our knowledge, is a new innovative idea in program analysis.Comment: This is the extended version (33 pages) of a paper to be appeared in the Static Analysis Symposium (SAS) 201

Neutralization potency of monoclonal antibodies recognizing dominant and subdominant epitopes on SARS-CoV-2 Spike is impacted by the B.1.1.7 variant

Interaction of the SARS-CoV-2 Spike receptor binding domain (RBD) with the receptor ACE2 on host cells is essential for viral entry. RBD is the dominant target for neutralizing antibodies, and several neutralizing epitopes on RBD have been molecularly characterized. Analysis of circulating SARS-CoV-2 variants has revealed mutations arising in the RBD, N-terminal domain (NTD) and S2 subunits of Spike. To understand how these mutations affect Spike antigenicity, we isolated and characterized >100 monoclonal antibodies targeting epitopes on RBD, NTD, and S2 from SARS-CoV-2-infected individuals. Approximately 45% showed neutralizing activity, of which ∼20% were NTD specific. NTD-specific antibodies formed two distinct groups: the first was highly potent against infectious virus, whereas the second was less potent and displayed glycan-dependant neutralization activity. Mutations present in B.1.1.7 Spike frequently conferred neutralization resistance to NTD-specific antibodies. This work demonstrates that neutralizing antibodies targeting subdominant epitopes should be considered when investigating antigenic drift in emerging variants