A document-like software visualization method for effective cognition of c-based software systems

It is clear that maintenance is a crucial and very costly process in a software life cycle. Nowadays there are a lot of software systems particularly legacy systems that are always maintained from time to time as new requirements arise. One important source to understand a software system before it is being maintained is through the documentation, particularly system documentation. Unfortunately, not all software systems developed or maintained are accompanied with their reliable and updated documents. In this case, source codes will be the only reliable source for programmers. A number of studies have been carried out in order to assist cognition based on source codes. One way is through tool automation via reverse engineering technique in which source codes will be parsed and the information extracted will be visualized using certain visualization methods. Most software visualization methods use graph as the main element to represent extracted software artifacts. Nevertheless, current methods tend to produce more complicated graphs and do not grant an explicit, document-like re-documentation environment. Hence, this thesis proposes a document-like software visualization method called DocLike Modularized Graph (DMG). The method is realized in a prototype tool named DocLike Viewer that targets on C-based software systems. The main contribution of the DMG method is to provide an explicit structural re-document mechanism in the software visualization tool. Besides, the DMG method provides more level of information abstractions via less complex graph that include inter-module dependencies, inter-program dependencies, procedural abstraction and also parameter passing. The DMG method was empirically evaluated based on the Goal/Question/Metric (GQM) paradigm and the findings depict that the method can improve productivity and quality in the aspect of cognition or program comprehension. A usability study was also conducted and DocLike Viewer had the most positive responses from the software practitioners

Youthful Processing Speed in Older Adults: Genetic, Biological, and Behavioral Predictors of Cognitive Processing Speed Trajectories in Aging.

Objective: To examine the impact of genetic, inflammatory, cardiovascular, lifestyle, and neuroanatomical factors on cognitive processing speed (CPS) change over time in functionally intact older adults. Methods: This observational study conducted over two time points, included 120 community dwelling cognitively normal older adults between the ages of 60 and 80 from the University of California San Francisco Memory and Aging Center. Participants were followed with composite measures of CPS, calculated based on norms for 20-30 year-olds. Variables of interest were AD risk genes (APOE, CR1), markers of inflammation (interleukin 6) and cardiovascular health (BMI, LDL, HDL, mean arterial pressure, fasting insulin), self-reported physical activity, and corpus callosum (CC) volumes. The sample was divided into three groups: 17 "resilient-agers" with fast and stable processing speed; 56 "average-agers" with average and stable processing speed; and 47 "sub-agers" with average baseline speed who were slower at follow-up. Results: Resilient-agers had larger baseline CC volumes than sub-agers (p < 0.05). Resilient-agers displayed lower levels of interleukin-6 (IL-6) and insulin (ps < 0.05) than sub-agers, and reported more physical activity than both average- and sub-agers (ps < 0.01). In a multinomial logistic regression, physical activity and IL-6 predicted average- and sub-ager groups. Resilient-agers displayed a higher frequency of APOE e4 and CR1 AA/AG alleles. Conclusion: Robust and stable CPS is associated with larger baseline CC volumes, lower levels of inflammation and insulin, and greater self-reported physical activity. These findings highlight the relevance of neuroanatomical, biological, and lifestyle factors in the identification and prediction of heterogeneous cognitive aging change over time

A canonical theory of dynamic decision-making

Decision-making behavior is studied in many very different fields, from medicine and eco- nomics to psychology and neuroscience, with major contributions from mathematics and statistics, computer science, AI, and other technical disciplines. However the conceptual- ization of what decision-making is and methods for studying it vary greatly and this has resulted in fragmentation of the field. A theory that can accommodate various perspectives may facilitate interdisciplinary working. We present such a theory in which decision-making is articulated as a set of canonical functions that are sufficiently general to accommodate diverse viewpoints, yet sufficiently precise that they can be instantiated in different ways for specific theoretical or practical purposes. The canons cover the whole decision cycle, from the framing of a decision based on the goals, beliefs, and background knowledge of the decision-maker to the formulation of decision options, establishing preferences over them, and making commitments. Commitments can lead to the initiation of new decisions and any step in the cycle can incorporate reasoning about previous decisions and the rationales for them, and lead to revising or abandoning existing commitments. The theory situates decision-making with respect to other high-level cognitive capabilities like problem solving, planning, and collaborative decision-making. The canonical approach is assessed in three domains: cognitive and neuropsychology, artificial intelligence, and decision engineering

Collaborative design : managing task interdependencies and multiple perspectives

This paper focuses on two characteristics of collaborative design with respect to cooperative work: the importance of work interdependencies linked to the nature of design problems; and the fundamental function of design cooperative work arrangement which is the confrontation and combination of perspectives. These two intrinsic characteristics of the design work stress specific cooperative processes: coordination processes in order to manage task interdependencies, establishment of common ground and negotiation mechanisms in order to manage the integration of multiple perspectives in design

Maintaining binding in working memory: Comparing the effects of intentional goals and incidental affordances

Much research on memory for binding depends on incidental measures. However, if encoding associations benefits from conscious attention, then incidental measures of binding memory might not yield a sufficient understanding of how binding is accomplished. Memory for letters and spatial locations was compared in three within-participants tasks, one in which binding was not afforded by stimulus presentation, one in which incidental binding was possible, and one in which binding was explicitly to be remembered. Some evidence for incidental binding was observed, but unique benefits of explicit binding instructions included preserved discrimination as set size increased and drastic reduction in false alarms to lures that included a new spatial location and an old letter. This suggests that substantial cognitive benefits, including enhanced memory for features themselves, might occur through intentional binding, and that incidental measures of binding might not reflect these advantages. (C) 2011 Elsevier Inc. All rights reserved

Evaluating the Impact of Critical Factors in Agile Continuous Delivery Process: A System Dynamics Approach

Continuous Delivery is aimed at the frequent delivery of good quality software in a speedy, reliable and efficient fashion – with strong emphasis on automation and team collaboration. However, even with this new paradigm, repeatability of project outcome is still not guaranteed: project performance varies due to the various interacting and inter-related factors in the Continuous Delivery 'system'. This paper presents results from the investigation of various factors, in particular agile practices, on the quality of the developed software in the Continuous Delivery process. Results show that customer involvement and the cognitive ability of the QA have the most significant individual effects on the quality of software in continuous delivery

Evaluation of Cognitive Architectures for Cyber-Physical Production Systems

Cyber-physical production systems (CPPS) integrate physical and computational resources due to increasingly available sensors and processing power. This enables the usage of data, to create additional benefit, such as condition monitoring or optimization. These capabilities can lead to cognition, such that the system is able to adapt independently to changing circumstances by learning from additional sensors information. Developing a reference architecture for the design of CPPS and standardization of machines and software interfaces is crucial to enable compatibility of data usage between different machine models and vendors. This paper analysis existing reference architecture regarding their cognitive abilities, based on requirements that are derived from three different use cases. The results from the evaluation of the reference architectures, which include two instances that stem from the field of cognitive science, reveal a gap in the applicability of the architectures regarding the generalizability and the level of abstraction. While reference architectures from the field of automation are suitable to address use case specific requirements, and do not address the general requirements, especially w.r.t. adaptability, the examples from the field of cognitive science are well usable to reach a high level of adaption and cognition. It is desirable to merge advantages of both classes of architectures to address challenges in the field of CPPS in Industrie 4.0

Functional network changes and cognitive control in schizophrenia

Cognitive control is a cognitive and neural mechanism that contributes to managing the complex demands of day-to-day life. Studies have suggested that functional impairments in cognitive control associated brain circuitry contribute to a broad range of higher cognitive deficits in schizophrenia. To examine this issue, we assessed functional connectivity networks in healthy adults and individuals with schizophrenia performing tasks from two distinct cognitive domains that varied in demands for cognitive control, the RiSE episodic memory task and DPX goal maintenance task. We characterized general and cognitive control-specific effects of schizophrenia on functional connectivity within an expanded frontal parietal network (FPN) and quantified network topology properties using graph analysis. Using the network based statistic (NBS), we observed greater network functional connectivity in cognitive control demanding conditions during both tasks in both groups in the FPN, and demonstrated cognitive control FPN specificity against a task independent auditory network. NBS analyses also revealed widespread connectivity deficits in schizophrenia patients across all tasks. Furthermore, quantitative changes in network topology associated with diagnostic status and task demand were observed. The present findings, in an analysis that was limited to correct trials only, ensuring that subjects are on task, provide critical insights into network connections crucial for cognitive control and the manner in which brain networks reorganize to support such control. Impairments in this mechanism are present in schizophrenia and these results highlight how cognitive control deficits contribute to the pathophysiology of this illness