Abstract-Architecture Compliance Checking (ACC) is useful to bridge the gap between architecture and implementation. ACC is an approach to verify conformance of implemented program code to high-level models of architectural design. Static ACC focuses on the modular software architecture and on the existence of rule violating dependencies between modules. Accurate tool support is essential for effective and efficient ACC. This paper presents a study on the accuracy of ACC tools regarding dependency analysis and violation reporting. Seven tools were tested and compared by means of a custom-made test application. In addition, the code of open source system Freemind was used to compare the tools on the number and precision of reported violation and dependency messages. On the average, 74 percent of 34 dependency types in our custom-made test software were reported, while 69 percent of 109 violating dependencies within a module of Freemind were reported. The test results show large differences between the tools, but all tools could improve the accuracy of the reported dependencies and violations.
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There remains some debate about whether beta power effects observed during sentence comprehension reflect ongoing syntactic unification operations (beta-syntax hypothesis), or instead reflect maintenance or updating of the sentence-level representation (beta-maintenance hypothesis). In this study, we used magnetoencephalography to investigate beta power neural dynamics while participants read relative clause sentences that were initially ambiguous between a subject- or an object-relative reading. An additional condition included a grammatical violation at the disambiguation point in the relative clause sentences. The beta-maintenance hypothesis predicts a decrease in beta power at the disambiguation point for unexpected (and less preferred) object-relative clause sentences and grammatical violations, as both signal a need to update the sentence-level representation. While the beta-syntax hypothesis also predicts a beta power decrease for grammatical violations due to a disruption of syntactic unification operations, it instead predicts an increase in beta power for the object-relative clause condition because syntactic unification at the point of disambiguation becomes more demanding. We observed decreased beta power for both the agreement violation and object-relative clause conditions in typical left hemisphere language regions, which provides compelling support for the beta-maintenance hypothesis. Mid-frontal theta power effects were also present for grammatical violations and object-relative clause sentences, suggesting that violations and unexpected sentence interpretations are registered as conflicts by the brain's domain-general error detection system.
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The task of risk assessment is a central feature of probation work and a core activity of probation officers. Risk assessment forms the basis for subsequent interventions and management of offenders so that the likelihood of reoffending is reduced. A primary difficulty for probation workers is the ability to predict the risk of probation violations which could facilitate prevention. The main objective of the present study was to investigate the value of the 61-item Dutch diagnostic and risk assessment tool Recidivism Assessment Scales (RISc) with respect to predicting probation supervision violations of male probationers (N = 14,363). Because all RISc assessments included in the study were completed before the start of the supervision period, they could not have been influenced by behavior of the offenders or other circumstances during this period. It was found that the predictive accuracy of the RISc, with regard to supervision violation, was supported. All RISc subscales and the total score significantly predicted probation supervision violation. The AUC demonstrating the strength of the relationship of the RISc total score (AUC = .70) is satisfactory. Logistic regression analyses resulted in a fitting model, demonstrating that a selection of only 17 items from the total of 61 RISc items was sufficient to predict probation violation while preserving predictive accuracy (AUC = .73). For one of the possible cut-off sum scores used to select groups at high risk for probation violation, it was shown that is possible to double the percentage of correctly identified future violators when compared to the base rate of probation violation.
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Semantic unification, the process by which small blocks of semantic information are combined into a coherent utterance, has been studied with various types of tasks. However, whether the brain activations reported in these studies are attributed to semantic unification per se or to other task-induced concomitant processes still remains unclear. The neural basis for semantic unification in sentence comprehension was examined using event-related potentials (ERP) and functional Magnetic Resonance Imaging (fMRI). The semantic unification load was manipulated by varying the goodness of fit between a critical word and its preceding context (in high cloze, low cloze and violation sentences). The sentences were presented in a serial visual presentation mode. The participants were asked to perform one of three tasks: semantic congruency judgment (SEM), silent reading for comprehension (READ), or font size judgment (FONT), in separate sessions. The ERP results showed a similar N400 amplitude modulation by the semantic unification load across all of the three tasks. The brain activations associated with the semantic unification load were found in the anterior left inferior frontal gyrus (aLIFG) in the FONT task and in a widespread set of regions in the other two tasks. These results suggest that the aLIFG activation reflects a semantic unification, which is different from other brain activations that may reflect task-specific strategic processing.
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SUMMARY Architecture compliance checking (ACC) is an approach to verify conformance of implemented program code to high-level models of architec tural design. Static ACC focuses on the modular software architecture and on the existence of rule violating dependencies between modules. Accurate tool support is essential for effective and efficient ACC. This paper presents a study on the accuracy of ACC tools regarding dependency analysis and violation reporting. Ten tools were tested and compare d by means of a custom-made benchmark. The Java code of the benchmark testware contains 34 different types of dependencies, which are based on an inventory of dependency types in object oriented program code. In a second test, the code of open source system FreeMind was used to compare the 10 tools on the number of reported rule violating dependencies and the exactness of the dependency and violation messages. On the average, 77% of the dependencies in our custom-made test software were reported, while 72% of the dependencies within a module of FreeMind were reported. The results show that all tools in the test could improve the accuracy of the reported dependencies and violations, though large differences between the 10 tools were observed. We have identified10 hard-to-detect types of dependencies and four challenges in dependency detection. The relevance of our findings is substantiated by means of a frequency analysis of the hard-to-detect types of dependencies in five open source systems. DOI: 10.1002/spe.2421
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Author supplied: "Abstract Software Architecture Compliance Checking (SACC) is an approach to verify conformance of implemented program code to high-level models of architectural design. Static SACC focuses on the modular software architecture and on the existence of rule violating dependencies between modules. Accurate tool support is essential for effective and efficient SACC. This document describes a test approach that may be used to determine how accurate a tested SACCT-tool is with respect to dependency analysis and violation reporting. This technical report is intended as a test manual and describes how a SACCT-tool can be tested. Two separate tests are described: the Benchmark test, and the FreeMind test."
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Gamma-band neuronal synchronization during sentence-level language comprehension has previously been linked with semantic unification. Here, we attempt to further narrow down the functional significance of gamma during language comprehension, by distinguishing between two aspects of semantic unification: successful integration of word meaning into the sentence context, and prediction of upcoming words. We computed eventrelated potentials (ERPs) and frequency band-specific electroencephalographic (EEG) power changes while participants read sentences that contained a critical word (CW) that was (1) both semantically congruent and predictable (high cloze, HC), (2) semantically congruent but unpredictable (low cloze, LC), or (3) semantically incongruent (and therefore also unpredictable; semantic violation, SV). The ERP analysis showed the expected parametric N400 modulation (HC < LC < SV). The time-frequency analysis showed qualitatively different results. In the gamma-frequency range, we observed a power increase in response to the CW in the HC condition, but not in the LC and the SV conditions. Additionally, in the theta frequency range we observed a power increase in the SV condition only. Our data provide evidence that gamma power increases are related to the predictability of an upcoming word based on the preceding sentence context, rather than to the integration of the incoming word's semantics into the preceding context. Further, our theta band data are compatible with the notion that theta band synchronization in sentence comprehension might be related to the detection of an error in the language input.
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There is growing evidence suggesting that synchronization changes in the oscillatory neuronal dynamics in the EEG or MEG reflect the transient coupling and uncoupling of functional networks related to different aspects of language comprehension. In this work, we examine how sentence-level syntactic unification operations are reflected in the oscillatory dynamics of the MEG. Participants read sentences that were either correct, contained a word category violation, or were constituted of random word sequences devoid of syntactic structure. A time-frequency analysis of MEG power changes revealed three types of effects. The first type of effect was related to the detection of a (word category) violation in a syntactically structured sentence, and was found in the alpha and gamma frequency bands. A second type of effect was maximally sensitive to the syntactic manipulations: A linear increase in beta power across the sentence was present for correct sentences, was disrupted upon the occurrence of a word category violation, and was absent in syntactically unstructured random word sequences. We therefore relate this effect to syntactic unification operations. Thirdly, we observed a linear increase in theta power across the sentence for all syntactically structured sentences. The effects are tentatively related to the building of a working memory trace of the linguistic input. In conclusion, the data seem to suggest that syntactic unification is reflected by neuronal synchronization in the lower-beta frequency band.
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Walter, A. S. and D. P. Redlawsk (2021). The Effects of Politician 's Moral Violation on Voters ' Moral Emotions, Political Behavior, https://doi.org/10.1007/s11109-021-09749-z Existing empirical research on voters’ responses to individual politicians’ moral transgressions pays limited attention to moral emotions, although moral emotions are an integral part of voters’ moral judgment. This study looks at U.S. voters’ discrete moral emotional responses to politician’s moral violations and examines how these discrete moral emotional responses are dependent on voters’ own moral principles and the extent to which they identify with a political party. We report on a 5 × 3 between-subjects experiment where 2026 U.S. respondents reacted to politicians’ violations of one of five moral foundations defined by Moral Foundations Theory. We randomly vary which moral foundation is violated and the partisanship of the politician. While voters’ own moral principles somewhat condition moral emotional responses, we find that voters’ moral emotional responses mostly depend on partisan identification. When voters share party identity with a politician committing a moral violation, they respond with less anger, contempt, disgust and shame than when they do not share party identity. The effect is greater among strong partisans. However, we find limited evidence that specific moral emotions are activated by violations of particular moral foundations, thereby challenging Moral Foundations Theory. https://doi.org/10.1007/s11109-021-09749-z
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Author supplied: "Abstract—Software architecture compliance checking (SACC) is an approach to monitor the consistency between the intended and the implemented architecture. In case of static SACC, the focus is mainly on the detection of dependencies that violate architectural relation rules. Interpretation of reported violations may be cumbersome, since the violations need to be connected to architectural resolutions and targeted qualities such as maintainability and portability. This paper describes an SACC case study which shows that inclusion of different types of rules in the SACC process enhances reasoning on architecture violations, especially if a rule type is related to specific architectural pattern. The SACC is performed with HUSACCT, an SACC-tool that provides rich sets of module and rule types in support of patterns such as layers, facade, and gateway. The case system is a governmental system developed in C#, which follows the .NET common application architecture. Even though the system appeared to be well-structured, the SACC revealed that 10 of the 17 architectural rules were violated."
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