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Abstract - Personal Software Process with Automatic Requirements Traceability to Support Startups
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Abstract: This paperapplies Personal Software Process (PSP) for software development activities, and uses PSP scripts to follow the activities in software development. In particular, we have adapted a development script in order to enable automatic traceability. The script is the cyclical process that is designed for developing a large program in a sequence of small incremental steps. Moreover, we have extended an XTraQue tool to enable an automatic traceability during using PSP. This enables the completeness of traceability during using PSP. The Part-of-Speech (POS) embedded XML-based templates of software artefacts for PSP-based development, that is, functional requirements (FR), use case, and class diagram are defined. We perform an explanatory case study in order to evaluate the effectiveness between manual and automatic traceability during the personal software process (PSP). In particular, the causal links between software artefacts created during software development are so-called traceability relations. The result evaluation are concerned with precision and recall measures on the creation of traceability relations. Keywords: Personal Software Process, Software Improvement Process, Requirements Traceability, Incremental Development. |
Abstract - Comparing Statistical and Data Mining Techniques for Enrichment Ontology with Instances
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Abstract: Enriching instances into an ontology is an important task because the process extends knowledge in ontology to cover more extensively the domain of interest, so that greater benefits can be obtained. There are many techniques to classify instances of concepts with two popular techniques being the statistical and data mining methods. The paper compares the use of the two methods to classify instances to enrich ontology having greater domain knowledge, and selects a conditional random field for the statistical method and feature-weight k-nearest neighbor classification for the data mining method. The experiments are conducted on tourism ontology. The results show that conditional random fields methods provide greater precision and recall value than the other, specifically, F1-measure is 74.09% for conditional random fields and 60.04% for feature-weight k-nearest neighbor classification. Keywords: Ontology Enrichment, Statistical Technique, Classification, Conditional Random Fields (CRFs), Feature-weighted k-Nearest Neighbor. |
Abstract - EDITORIAL: Monetary Policy in a Post-Crisis World: Experiences and Practices
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Abstract - Predicting Fed Forecasts
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Abstract: Monetary policy decisions by the Fed's Federal Open Market Committee have attracted considerable attention in recent years, especially with quantitative easing through large-scale asset purchases, the introduction of forward guidance, and increases in the federal funds rate. The FOMC’s decisions are based in part on the Greenbook forecasts, which are economic forecasts produced by the Federal Reserve Board’s staff and which are presented to the FOMC prior to their policy meetings. Drawing on Stekler and Symington’s (2016) textual analysis of the minutes of the FOMC meetings, the current paper shows that those minutes provide a proximate mechanism for inferring the Fed staff's Greenbook forecasts of the U.S. real GDP growth rate, years before the Greenbook's public release. The FOMC minutes are thus highly informative about a key input to monetary policymaking. Keywords: Fed, financial crisis, FOMC, forecasts, GDP, Great Recession, Greenbook, impulse indicator saturation, projections, Tealbook, United States. |
