Shaochun Li

A Service-Based Framework for Mobile Social Messaging in PaaS Systems

With the rapid growth of cloud computing, developing business applications on Platform-as-a-Service (PaaS) systems is increasingly popular among industry companies. Various services are developed to support different business requirements on PaaS systems. However, to the best of our knowledge, currently there is no service that provides mobile social messaging services to enable users of their apps to share messages in their social networks (e.g., We Chat, Whats App, Kaka Talk). Lack of such mobile social messaging services prevents industry companies from succeeding in drastic market competitions (e.g., Capture high customer satisfactory). In this paper, we propose a service-based framework to enable the mobile social messaging in PaaS systems (e.g., IBM Blue mix). Using this framework, developers can focus on the service encapsulation of existing applications, and define their business process flows via the conversation management in our platform (no coding work is needed). As such, our framework can effectively reduce the development workload for mobile social messaging in PaaS systems.

Enabling customizable service-based procedural knowledge applications — An service-orientation for Dialog Manager

The Dialog Manager is a conversational web-based tool that helps organizations manage procedural knowledge. A dialog is a visual knowledge representation of certain procedural knowledge enriched with interactive guides. To empower the usage of dialog, we further provide a service-orientation for Dialog Manager, aiming to enable customized service-based knowledge applications. Such service-orientation will enable a user to select services to answer questions from dialog automatically during runtime. It will also enable the subject matter expert (SME) to specify the external services to make good use of user dialog data to facilitate ticket issuing and resolution. Through a case study, we will demonstrate the great business impact of our proposal.

Providing Mobile Dialog Services Using WeChat

WeChat-based services are becoming very popular among billions of users. It is now an important business strategy to provide services for users to access business systems via WeChat. However, to the best of our knowledge, currently there is no easy way to foster the development of mobile dialog services using WeChat. Lack of such mobile social messaging services prevents industry companies from succeeding in drastic market competitions (e.g., capture high customer satisfactory). In this paper, we propose a framework for providing mobile dialog services using WeChat. Using this framework, industry companies can easily provide their IT services using WeChat. There are two levels of dialog authoring: static dialogs that enable non-developers to define for offering guidance path with static texts, and dynamic dialogs that require developers to write codes to support dynamic guidance path and dynamic texts on different path nodes. This framework can serve as the bridge between users and various information and business functionalities. Finally, we also use a use case to demonstrate how this mobile dialog service can be used in supporting sports activities.

Self-adapting task allocation approach for software outsourcing services

Task allocation problem plays a key role in software outsourcing services. In this paper, a self-adapting task allocation approach is presented to provide optimal task assignment strategy in the project management of software outsourcing services. The approach is constituted by preparation, task allocation, evaluation, and evolution part. In the core part, task allocation, several mathematical models for different objectives are built to determine the optimal task allocation solutions, and heuristics are proposed to solve them. The proposed approach was proved by numerical examples to be efficient, practical and helpful for improving enterprise project management level and sources code quality.

Graph-based constraints analysis approach for project scoping

Project scoping is a changeable problem in project management. In this paper, a graph-based constraints analysis approach was proposed to solve the project scoping problem. It firstly build a directed graph based on the dependencies among the requirements, secondly update the connected graph based on user defined inclusive and exclusive constraints, thirdly find the connected sub-graph set, fourthly verify the constraints for sub-graph and determine all candidate sub-graph sets, and finally determine solution for the project scoping problem through solving a Knapsack problem. The proposed approach was illustrated through a simple example and validated by real cases. Through the experiments, the proposed approach is efficient and validate in practice.

Collaborative change impact analysis for enterprise application evolution

Change impact analysis is increasingly challenging for enterprise applications due to that applications in an enterprise portfolio usually heavily depend on each other and also grow rapidly in both of scale and complexity. Automatic impact analysis based on intra- and inter-application dependencies implies potential impact propagation directions. However, due to the variety and complexity of dependencies, determining real impacts is intelligence intensive and usually needs interventions of Subject Matter Experts (SMEs) on each involved application. In this paper, to enable a more agile enterprise application evolution, we propose and implement a collaborative change impact analysis approach which effectively coordinates involvements and incorporates insights of relevant SMEs. In the approach, we first construct an initial collaborative change impact analysis roadmap based on application dependencies. Then, we iteratively invite and coordinate relevant SMEs based on the roadmap, and then leverage their insights to dynamically refine the roadmap. The evaluations on real enterprise applications show the effectiveness of our proposed approach.

What Code Implements Such Service? A Behavior Model Based Feature Location Approach

Enterprises today are keen to unlock new business values of their legacy services towards new trends (e.g., cloud and mobile). To accelerate such process, automatic feature location techniques can enable developers to rapidly locate/understand implementations of certain services (e.g., services to expose, transform or improve). Existing feature location techniques [1-3, 5-10, 32] provide a good foundation but have several key limitations: limited leverage of description sources, less considerations of internal behaviors, and ineffectiveness for the identification of service-relevant code entries. To address these limitations, we propose a behavior model based feature location approach and implement a tool named BMLocator. In the offline phase, BMLocator applies Natural Language Processing (NLP) techniques and static code analysis to extract “behavior models” of code units via considering multiple information sources. While in the online phase, given a service description, BMLocator first extracts its behavior model and then recommends service-relevant code units/entries by matching its behavior model with code units under analysis. Through evaluations with public service requests of open-source projects (e.g., Tomcat and Hadoop), we show that the approach is more effective in recommending service-relevant code entries (e.g., most of entries are prioritized as the first ones) than existing techniques (i.e., TopicXP[37], CVSSearch[6]).

Exploiting Unique Characteristics of Mobile Backend Services to Recommend Right Ones

To accelerate the development of mobile apps, more and more third-party services that can be consumed as mobile backend services are available for the consumption of mobile developers. However, with the growth of mobile backend services, it turns to be a more and more challenging process for mobile developers to discover mobile backend services with high return-on-investment (ROI). Due to the unique characteristics of mobile backend services, directly applying existing Web service recommendation solutions for mobile backend services is ineffective. In this paper, we systematically studied and summarized four unique characteristics of mobile backend services. Based on these four unique characteristics, we proposed an extendable recommendation approach for mobile backend services to help mobile developers to efficiently identify what they really need. Through the empirical evaluations that we conducted on hundreds of open mobile backend services, we demonstrated the effectiveness and efficiency of the proposed approach.

Agent Based Decomposition for Service Change Request Analysis

Service requirement and change request analysis is critical important for the project, whose result directly affects the implementation planning. They are often raised from business perspective and need much more effort to drill down to IT system details from implementation perspective. Current practice is mainly depends on experts involvement, and has a very high entry barrier, which cause the analysis effort is labor intensive, costly, and error-prone. In order to facilitate the service change request analysis, a computer-aided approach is proposed in this paper. The approach leverages the understanding of the IT artifacts in the target system and the change requests details, and uses the applicable predefined decomposition agent to generate a plurality of sub-change requests with the correlation of IT artifacts. With this approach, change request decomposition may be performed automatically or semi-automatically. Thus, the efficiency of change request analysis may be improved.

Second Order-Based Real-Time Anomaly Detection for Application Maintenance Services

Application Maintenance Services (AMS) is essential for applications executed on servers to function properly. Its objective is to reduce the application incidents happened and quickly recover services from application failures/issues. The application incidents defined as events when there are some application failures/issues happened are major concerns of AMS, therefore we propose a second order-based anomaly detection method to describe and predict application incidents based on analysis of monitored server traffic metrics. The proposed method first detects anomalies for each metric, second builds the linkage between detected anomalies for all metrics of the server and application incidents, and then predicts potential application incidents. Through the experiments, we find that the presented method provides satisfactory results for identify application incident, which gives more than 90 percentage recall rate while about 65 percentage precision rate.