Aspect] is a simple and practical aspect-oriented extension to Java With just a few new constructs, AspectJ provides support for modular implementation of a range of crosscutting concerns. In AspectJ's dynamic join point model, join points are well-defined points in the execution of the program; pointcuts are collections of join points; advice are special method-like constructs that can be attached to pointcuts; and aspects are modular units of crosscutting implementation, comprising pointcuts, advice, and ordinary Java member declarations. AspectJ code is compiled into standard Java bytecode. Simple extensions to existing Java development environments make it possible to browse the crosscutting structure of aspects in the same kind of way as one browses the inheritance structure of classes. Several examples show that AspectJ is powerful, and that programs written using it are easy to understand.

An overview of AspectJ

我的台灣, 看見心靈的故鄉 =2009林磐聳藝術與設計展

[발표] 2015개정 실과 교육과정 ‘가정생활’ 영역 개발 방향

https://cronfa.swan.ac.uk/Record/cronfa38958/Download/0038958-06032018151557.pdf

Consumer adoption of mobile banking services: An empirical examination of factors according to adoption stages

Gamification in software engineering education: a systematic mapping

Credit risk is the risk of financial loss when a borrower fails to meet the financial commitment. While there are many factors that constitute credit risk, due diligence while giving loan (credit scoring), continuous monitoring of customer payments and other behaviour patterns could reduce the probability of accumulating non-performing assets (NPA) and frauds. In the past few years, the quantum of NPAs and frauds have gone up significantly, and therefore it has become imperative that banks and financial institutions use robust mechanisms to predict the performance of loans. The past two decades has seen an immense growth in the area of artificial intelligence, most notably machine learning (ML) with improved access to internet, data, and compute. Whilst there are credit rating agencies and credit scoring companies that provide their analysis of a customer to banks on a fee, the researchers continue to explore various ML techniques to improve the accuracy level of credit risk evaluation. In this survey paper, we performed a systematic literature review on existing research methods and ML techniques for credit risk evaluation. We reviewed a total of 136 papers on credit risk evaluation published between 1993 and March 2019. We studied the implications of hyper parameters on ML techniques being used to evaluate credit risk and, analyzed the limitations of the current studies and research trends. We observed that Ensemble and Hybrid models with neural networks and SVM are being more adopted for credit scoring, NPA prediction and fraud detection. We also realized that lack of comprehensive public datasets continue to be an area of concern for researchers.

Machine learning techniques for credit risk evaluation: a systematic literature review

Researchers have supported the idea of gamification to enhance students' interest in activities like code reviews, change management, knowledge management, issue tracking, etc. which might otherwise be repetitive and monotonous. We performed an experimental study consisting of nearly 180+ participants to measure the impact of gamification on code review process using 5 different code review tools, including one gamified code review instance from our extensible architectural framework. We assess the impact of gamification based on the code smells and bugs identified in a gamified and non-gamified environment as per code inspection report. Further, measurement and comparison of the quantity and usefulness of code review comments was done using machine learning techniques.

Impact of Gamification on Code review process: An Experimental Study

Peer code review and inspection is a quality improvementsoftware engineering activity consisting of systematicexamination of source code. While peer code review is commonlyused in industrial and open-source software projects, it is seldomtaught or practiced in undergraduate level Software Engineeringcourses. We conduct a study on the use of peer code reviewin a sophomore level introductory Software Engineering courseconsisting of more than 200 students and present our experiences,findings and challenges. We use Bitbucket's (a free code distributedversion control system hosting site for Git and Mercurial)in-built code-review system and web-based hosting service. Weextract the peer code review comments using Bitbucket API fordetecting coding standard or compliance violation and identificationof defects (number and type) by reviewers. We also conducta survey on the benefit of peer code review activity on peercohesion and communication. Our experiments and survey revealthat employing peer code review in an undergraduate class hasseveral learning benefits such as improvement in coding skills,program comprehension abilities, knowledge of coding standard,and compliance and peer communication

In Support of Peer Code Review and Inspection in an Undergraduate Software Engineering Course

Presence of information from multiple sources on the internet requires evaluating the credibility of the information, before its utilization. Researchers have suggested that internet users experience difficulty in accessing necessary information and do not pay enough attention to its credibility. We present here the design and implementation of an automated Web Credibility Assessment Support Tool (WebCAST) that considers multiple factors (type of website, popularity, sentiment, date of last update, reputation and review based on users' ratings reflecting personal experience) for assessing the credibility of information and returns a summary indication of the credibility of a website. We use Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA) method of Multi-Criteria Decision Analysis (MCDA) to give weights to the scale values on each factor, representing the relative importance of the attributes. An empirical evaluation of the tool was conducted by computing the correlation between the tool-generated credibility scores and that of human judges. The correlation was found to be 0.89, thus verifying the validity of the tool. In the future the proposed tool can be made useful to students in their learning process of credibility assessment.

Providing Web Credibility Assessment Support

Software engineering activities like code reviews, change management, knowledge management, issue tracking, etc. tend to be heavily process oriented. Gamification of such activities by composing the core activities with game design elements like badges and points can increase developers' interest in performing such activities. While there are various frameworks/applications that assist in gamification, extending the frameworks to add any/all desired game design elements has not been adequately addressed. In this paper, we propose an extensible architectural framework for gamification of software engineering activities where in the game design elements are modeled as services. We create an example instance of our framework by building a prototype for code review activity and note the challenges of designing such an extensible architectural framework. The example instance uses python's Flask micro framework and has five game design elements implemented as services, and exposed using restful APIs.

Y. Raghu Reddy

Papers

Machine learning techniques for credit risk evaluation: a systematic literature review

Impact of Gamification on Code review process: An Experimental Study

In Support of Peer Code Review and Inspection in an Undergraduate Software Engineering Course

Providing Web Credibility Assessment Support

Architecting an extensible framework for Gamifying Software Engineering concepts