A Methodology for Engineering Collaborative and ad-hoc Mobile Applications using SyD Middleware

Today’s web applications are more collaborative and utilize standard and ubiquitous Internet protocols. We have earlier developed System on Mobile Devices (SyD) middleware to rapidly develop and deploy collaborative applications over heterogeneous and possibly mobile devices hosting web objects. In this paper, we present the software engineering methodology for developing SyD-enabled web applications and illustrate it through a case study on two representative applications: (i) a calendar of meeting application, which is a collaborative application and (ii) a travel application which is an ad-hoc collaborative application. SyD-enabled web objects allow us to create a collaborative application rapidly with limited coding effort. In this case study, the modular software architecture allowed us to hide the inherent heterogeneity among devices, data stores, and networks by presenting a uniform and persistent object view of mobile objects interacting through XML/SOAP requests and responses. The performance results we obtained show that the application scales well as we increase the group size and adapts well within the constraints of mobile devices

International conference on software engineering and knowledge engineering: Session chair

The Thirtieth International Conference on Software Engineering and Knowledge Engineering (SEKE 2018) will be held at the Hotel Pullman, San Francisco Bay, USA, from July 1 to July 3, 2018. SEKE2018 will also be dedicated in memory of Professor Lofti Zadeh, a great scholar, pioneer and leader in fuzzy sets theory and soft computing. The conference aims at bringing together experts in software engineering and knowledge engineering to discuss on relevant results in either software engineering or knowledge engineering or both. Special emphasis will be put on the transference of methods between both domains. The theme this year is soft computing in software engineering & knowledge engineering. Submission of papers and demos are both welcome

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

Improving Software Performance in the Compute Unified Device Architecture

This paper analyzes several aspects regarding the improvement of software performance for applications written in the Compute Unified Device Architecture CUDA). We address an issue of great importance when programming a CUDA application: the Graphics Processing Unit’s (GPU’s) memory management through ranspose ernels. We also benchmark and evaluate the performance for progressively optimizing a transposing matrix application in CUDA. One particular interest was to research how well the optimization techniques, applied to software application written in CUDA, scale to the latest generation of general-purpose graphic processors units (GPGPU), like the Fermi architecture implemented in the GTX480 and the previous architecture implemented in GTX280. Lately, there has been a lot of interest in the literature for this type of optimization analysis, but none of the works so far (to our best knowledge) tried to validate if the optimizations can apply to a GPU from the latest Fermi architecture and how well does the Fermi architecture scale to these software performance improving techniques.Compute Unified Device Architecture, Fermi Architecture, Naive Transpose, Coalesced Transpose, Shared Memory Copy, Loop in Kernel, Loop over Kernel

Algon: a framework for supporting comparison of distributed algorithm performance

Programmers often need to use distributed algorithms to add non-functional behaviour such as mutual exclusion, deadlock detection and termination, to a distributed application. They find the selection and implementation of these algorithms daunting. Consequently, they have no idea which algorithm will be best for their particular application. To address this difficulty the Algon framework provides a set of pre-coded distributed algorithms for programmers to choose from, and provides a special performance display tool to support choice between algorithms. The performance tool is discussed. The developer of a distributed application will be able to observe the performance of each of the available algorithms according to a set of of widely accepted and easily-understandable performance metrics and compare and contrast the behaviour of the algorithms to support an informed choice. The strength of the Algon framework is that it does not require a working knowledge of algorithmic theory or functionality in order for the developer to use the algorithms