A Model for Measuring Cognitive Complexity of Software

This paper proposes a model for calculating cognitive complexity of a code. This model considers all major factors responsible for (cognitive) complexity. The practical applicability of the measure is evaluated through experimentation, test cases and comparative study

A Complexity Measure Based on Cognitive Weights

Cognitive Informatics plays an important role in understanding the fundamental characteristics of software. This paper proposes a model of the fundamental characteristics of software, complexity in terms of cognitive weights of basic control structures. Cognitive weights are degree of difficulty or relative time and effort required for comprehending a given piece of software, which satisfy the definition of complexity. An attempt has also been made to prove the robustness of proposed complexity measure by comparing it with the other measures based on cognitive informatics

Microfluidic Device for Motility and Osmolality Analysis of Zebrafish Sperm

An increasing number of laboratories are evaluating sample quality via motility analysis by means of computer-assisted sperm analysis (CASA) after sperm activation by manual dilution and mixing. Even with the use of CASA, due to user variation, there is a lack of control over the activation process, resulting in inconsistent motility analysis. Low sample volume (~1-2µL), and a short motility duration (burst motility of less than 15s) add to the complexity of these difficulties. The objectives of this study were to develop a microfluidic device with the capabilities to (1) standardize the method of activation for zebrafish sperm so that all cells in a sample are subjected to the conditions needed to activate in a reproducible way, (2) reproducibly enable motility analysis of the activated sample within 5 s after activation without the interference of bulk fluid flow, and (3) facilitate the generation of activation curves by relating osmolality of the sample solution to percent motility at the time when motility analysis was performed. The device described here is a three-inlet microfluidic platform fabricated from polydimethylsiloxane (PDMS) bound to a glass substrate with a microfabricated gold floor electrode for osmolality detection. A passive micromixer is utilized to activate sperm samples, and a novel flow control system was designed to aid with the demands of sample analysis. The device demonstrated consistent zebrafish sperm activation and osmolality detection. The device was also able to consistently reach flow cessation in under 1s, allowing for rapid analysis of the sample. This device represents a pivotal step in streamlining methods for consistent, rapid assessment of sperm quality for zebrafish and other aquatic species. The capability to rapidly activate sperm and consistently measure motility with CASA using the microfluidic device described herein will help improve the reproducibility of studies on germplasm physiology

Analysis and evaluation of the entropy indices of a static network structure

Although degree distribution entropy (DDE), SD structure entropy (SDSE), Wu structure entropy (WSE) and FB structure entropy (FBSE) are four static network structure entropy indices widely used to quantify the heterogeneity of a complex network, previous studies have paid little attention to their differing abilities to describe network structure. We calculate these four structure entropies for four benchmark networks and compare the results by measuring the ability of each index to characterize network heterogeneity. We find that SDSE and FBSE more accurately characterize network heterogeneity than WSE and DDE. We also find that existing benchmark networks fail to distinguish SDSE and FBSE because they cannot discriminate local and global network heterogeneity. We solve this problem by proposing an evolving caveman network that reveals the differences between structure entropy indices by comparing the sensitivities during the network evolutionary process. Mathematical analysis and computational simulation both indicate that FBSE describes the global topology variation in the evolutionary process of a caveman network, and that the other three structure entropy indices reflect only local network heterogeneity. Our study offers an expansive view of the structural complexity of networks and expands our understanding of complex network behavior.The authors would like to thank the financial support of the National Natural Science Foundation of China (71501153), Natural Science Foundation of Shaanxi Province of China (2016JQ6072), and the Foundation of China Scholarship Council (201506965039, 201606965057). (71501153 - National Natural Science Foundation of China; 2016JQ6072 - Natural Science Foundation of Shaanxi Province of China; 201506965039 - Foundation of China Scholarship Council; 201606965057 - Foundation of China Scholarship Council)Published versio

Models and metrics for software management and engineering

This paper attempts to characterize and present a state of the art view of several quantitative models and metrics of the software life cycle. These models and metrics can be used to aid in managing and engineering software projects. They deal with various aspects of the software process and product, including resources allocation and estimation, changes and errors, size, complexity and reliability. Some indication is given of the extent to which the various models have been used and the success they have achieved

The Structured Process Modeling Theory (SPMT): a cognitive view on why and how modelers benefit from structuring the process of process modeling

After observing various inexperienced modelers constructing a business process model based on the same textual case description, it was noted that great differences existed in the quality of the produced models. The impression arose that certain quality issues originated from cognitive failures during the modeling process. Therefore, we developed an explanatory theory that describes the cognitive mechanisms that affect effectiveness and efficiency of process model construction: the Structured Process Modeling Theory (SPMT). This theory states that modeling accuracy and speed are higher when the modeler adopts an (i) individually fitting (ii) structured (iii) serialized process modeling approach. The SPMT is evaluated against six theory quality criteria