A Longitudinal Study of the Impact of Open Source Software Project Characteristics on Positive Outcomes

This article formulates and tests a set of hypotheses about the success of open source software projects with respect to market penetration and human resource attraction. The authors collected data from 1025 open source software projects in a longitudinal study. The cross-sectional results show that the extent of a project’s operating systems, the range of translated languages, programming languages, and project age positively impact OSS projects’ positive outcomes with respect to market penetration and human resource attraction.     

An investigation on the feasibility of cross-project defect prediction

Software defect prediction helps to optimize testing resources allocation by identifying defect-prone modules prior to testing. Most existing models build their prediction capability based on a set of historical data, presumably from the same or similar project settings as those under prediction. However, such historical data is not always available in practice. One potential way of predicting defects in projects without historical data is to learn predictors from data of other projects. This paper investigates defect predictions in the cross-project context focusing on the selection of training data. We conduct three large-scale experiments on 34 data sets obtained from 10 open source projects. Major conclusions from our experiments include: (1) in the best cases, training data from other projects can provide better prediction results than training data from the same project; (2) the prediction results obtained using training data from other projects meet our criteria for acceptance on the average level, defects in 18 out of 34 cases were predicted at a Recall greater than 70% and a Precision greater than 50%; (3) results of cross-project defect predictions are related with the distributional characteristics of data sets which are valuable for training data selection. We further propose an approach to automatically select suitable training data for projects without historical data. Prediction results provided by the training data selected by using our approach are comparable with those provided by training data from the same project.     

A second look at Faster,Better, Cheaper

“Faster, Better, Cheaper” (FBC) was a systems development methodology used by NASA in the 1990s. While usually a deprecated practice, we find that, with certain caveats, it is a viable approach. To determine this we utilized a stochastic AI tool to determine the behavior of FBC for several case studies. In these case studies we compare results of using FBC with that of other optimization policies. In our tests, FBC is as advantageous a policy to use with projects as other policies, while avoiding their apparent downfalls.     

Neuro-genetic prediction of software development effort

Prediction of resource requirements of a software project is crucial for the timely delivery of quality-assured software within a reasonable timeframe. Many conventional (model-based) and AI-oriented (model-free) resource estimators have been proposed in the recent past. This paper presents a novel genetically trained neural network (NN) predictor trained on historical data. We demonstrate substantial improvement in prediction accuracy by the neuro-genetic approach as compared to both a regression-tree-based conventional approach, as well as backpropagation-trained NN approach reported recently. The superiority of this new predictor is established using n-fold cross validation and Student's t-test on various partitions of merged Cocomo and Kemerer data sets incorporating data from 78 real-life software projects.     

一种支持多维资源描述的高效P2P路由算法

在分析现有P2P(peer to peer)路由算法的基础上,提出了一种基于二阶矩定位、支持多维资源数据描述的高效资源路由算法--FAN(flabellate addressable network)路由算法.FAN算法将节点映射到统一的多维笛卡尔空间,并以节点相对空间原点的二阶矩作为子空间管理和资源搜索的依据.FAN路由算法具有O(log(N/k))的高路由效率,在节点加入和退出FAN网络时,更新路由信息的代价为O(klog(N/k)).实验结果表明,FAN路由算法具有路由效率高、维护代价小的优点,是一种P2P环境中支持多维资源数据描述的高效结构化资源路由算法.而且,目前部分基于CAN(content-addressable network)网络的改进算法也可以在FAN网络中适用,并获得更好的路由效率和更低的维护代价.     

Risk-neutral evaluation of information security investment on data centers

Based on given data center network topology and risk-neutral management, this work proposes a simple but efficient probability-based model to calculate the probability of insecurity of each protected resource and the optimal investment on each security protection device when a data center is under security breach. We present two algorithms that calculate the probability of threat and the optimal investment for data center security respectively. Based on the insecurity flow model (Moskowitz and Kang 1997) of analyzing security violations, we first model data center topology using two basic components, namely resources and filters, where resources represent the protected resources and filters represent the security protection devices. Four basic patterns are then identified as the building blocks for the first algorithm, called Accumulative Probability of Insecurity, to calculate the accumulative probability of realized threat (insecurity) on each resource. To calculate the optimal security investment, a risk-neutral based algorithm, called Optimal Security Investment, which maximizes the total expected net benefit is then proposed. Numerical simulations show that the proposed approach coincides with Gordon’s (Gordon and Loeb, ACM Transactions on Information and Systems Security 5(4):438–457, 2002) single-system analytical model. In addition, numerical results on two common data center topologies are analyzed and compared to demonstrate the effectiveness of the proposed approach. The technique proposed here can be used to facilitate the analysis and design of more secured data centers.     

The Design, Usage, and Performance of GRUBER: A Grid Usage Service Level Agreement based BrokERing Infrastructure

We present GRUBER, a Grid Resource Usage service level agreement (uSLA) based BrokERing infrastructure, aimed at addressing the challenging issues that can arise within virtual organizations (VOs) that integrate participants and resources spanning multiple physical administrative domains. In such environments, participants delegate to one or more VOs the right to use certain resources subject to local policy and service level agreements; each VO then uses those resources subject to VO policy. GRUBER supports the explicit representation, enforcement, and management of service level agreements (SLAs) concerning resource usage (uSLAs) that can serve as an objective organizing principle for controlled resource sharing in distributed systems. uSLAs express how resources must be used over various time intervals and represent a novelty for the Grid domain. This paper provides a detailed overview of the GRUBER infrastructure, the evolution of its design to improve scalability, specifically the distribution of the resource brokering service, and the extended support for dynamic environments. We also present various results achieved over time that demonstrate both the utility and performance of GRUBER under various application workloads and scenarios. This work was carried out for CoreGrid IST project n°004265, funded by the European Commission.     

A multi-agent system for distributed multi-project scheduling: An auction-based negotiation approach

Simultaneously running multiple projects are quite common in industries. These projects require local (always available to the concerned project) and global (shared among the projects) resources that are available in limited quantity. The limited availability of the global resources coupled with compelling schedule requirements at different projects leads to resource conflicts among projects. Effectively resolving these resource conflicts is a challenging task for practicing managers. This paper proposes a novel distributed multi-agent system using auctions based negotiation (DMAS/ABN) approach for resolving the resource conflicts and allocating multiple different types of shared resources amongst multiple competing projects. The existing multi-agent system (MAS) using auction makes use of exact methods (e.g. dynamic programming relaxation) for solving winner determination problem to resolve resource conflicts and allocation of single unit of only one type of shared resource. Consequently these methods fail to converge for some multi-project instances and unsuitable for real life large problems. In this paper the multi-unit combinatorial auction is proposed and winner determination problem is solved by efficient new heuristic.The proposed approach can solve complex large-sized multi-project instances without any limiting assumptions regarding the number of activities, shared resources or the number of projects. Additionally our approach further allows to random project release-time of projects which arrives dynamically over the planning horizon. The DMAS/ABN is tested on standard set of 140 problem instances. The results obtained are benchmarked against the three state-of-the-art decentralized algorithms and two existing centralized methods. For 82 of 140 instances DMAS/ABN found new best solutions with respect to average project delay (APD) and produced schedules on an average 16.79% (with maximum 57.09%) lower APD than all the five methods for solving the same class of problems.     

Fair and efficient dynamic bandwidth allocation for multi-application networks

The large diversity of applications and requirements posed to current network environments make the resource allocation problem difficult to work out. This paper proposes a dynamic algorithm based on weighted fair queueing (WFQ) to promote fairness (in the Rawlsian sense) and efficiency (in the Paretian sense) in the allocation of bandwidth for multi-application networks. Utility functions are used to characterize application requirements and provide the informational basis from where the algorithm operates. Aggregation techniques are employed to ensure scalability in the network core. Simulation results confirm a significant improvement of our approach over traditional bandwidth allocation algorithms (maxmin and proportional fairness). The algorithm also provides low errors (below 10% when compared to the zero-delay centralized approach) whenever response time does not exceed 1000 times the timescale involving flow arrivals and departures.     

Multicriteria,multi-user scheduling in grids with advance reservation

In this paper, we propose a new method for multi-user, multicriteria job scheduling in Grid environments with QoS guarantees concerning time and cost. The main goal of our method is to find a fair schedule of jobs that were submitted by multiple users. To obtain a schedule which is satisfactory for each user we aim at finding a set of advance reservations (ARs) for multiple users at once. This goal is achieved by adequate use of the Ordered Weighted Averaging (OWA) operator and Multiobjective Evolutionary Algorithm (MOEA) with carefully designed problem representation and operators. We also propose a data structure and algorithm used to manage and search for resource availability time slots. Efficiency and usefulness of our approach was demonstrated by computational experiments conducted within a simulation environment.     

MMRUC3: A recommendation approach of move method refactoring using coupling,cohesion, and contextual similarity to enhance software design

Placement of methods is one of the most important design activities for any object‐oriented application in terms of coupling and cohesion. Due to method misplacement, the application becomes tightly coupled and loosely cohesive, reflecting inefficient design. Therefore, a feature envy code smell emerges from the application, as many methods use more features of other classes than its current class. Hence, development and maintenance time, cost, and effort are increased. To refactor the code smell and enhance the design quality, move method refactoring plays a significant role through grouping similar behaviors of methods. This is because the manual refactoring process is infeasible due to the necessity of huge time and most of the existing techniques consider only coupling‐based and/or cohesion‐based information of nonstatic entities (methods and attributes) for the recommendation. However, this article proposes an approach that uses contextual information, based on information retrieval techniques, along with dependency (coupling and cohesion)‐based information of the application for the recommendation. In addition, the approach incorporates both static and nonstatic entities in the recommendation process. For validation, the approach is applied on seven well‐known open source projects. The results of the experimental evaluation indicate that the proposed approach provides better results with an average precision of 18.91%, a recall of 69.91%, and an F‐measure of 29.77% than the JDeodorant tool (a widely used eclipse plugin for refactorings). Moreover, this article establishes several relationships between the accuracy of the approach and project standards and sizes.     

Transactional Contention Management as a Non-Clairvoyant Scheduling Problem

The transactional approach to contention management guarantees consistency by making sure that whenever two transactions have a conflict on a resource, only one of them proceeds. A major challenge in implementing this approach lies in guaranteeing progress, since transactions are often restarted. Inspired by the paradigm of non-clairvoyant job scheduling, we analyze the performance of a contention manager by comparison with an optimal, clairvoyant contention manager that knows the list of resource accesses that will be performed by each transaction, as well as its release time and duration. The realistic, non-clairvoyant contention manager is evaluated by the competitive ratio between the last completion time (makespan) it provides and the makespan provided by an optimal contention manager.     

Strategic agents for multi-resource negotiation

In electronic commerce markets where selfish agents behave individually, agents often have to acquire multiple resources in order to accomplish a high level task with each resource acquisition requiring negotiations with multiple resource providers. Thus, it is crucial to efficiently coordinate these interrelated negotiations. This paper presents the design and implementation of agents that concurrently negotiate with other entities for acquiring multiple resources. Negotiation agents in this paper are designed to adjust (1) the number of tentative agreements for each resource and (2) the amount of concession they are willing to make in response to changing market conditions and negotiation situations. In our approach, agents utilize a time-dependent negotiation strategy in which the reserve price of each resource is dynamically determined by (1) the likelihood that negotiation will not be successfully completed (conflict probability), (2) the expected agreement price of the resource, and (3) the expected number of final agreements. The negotiation deadline of each resource is determined by its relative scarcity. Agents are permitted to decommit from agreements by paying a time-dependent penalty, and a buyer can make more than one tentative agreement for each resource. The maximum number of tentative agreements for each resource made by an agent is constrained by the market situation. Experimental results show that our negotiation strategy achieved significantly more utilities than simpler strategies.     

EFFICIENT ABSTRACTION SELECTION IN REINFORCEMENT LEARNING

This article addresses reinforcement learning problems based on factored Markov decision processes (MDPs) in which the agent must choose among a set of candidate abstractions, each build up from a different combination of state components. We present and evaluate a new approach that can perform effective abstraction selection that is more resource‐efficient and/or more general than existing approaches. The core of the approach is to make selection of an abstraction part of the learning agent's decision‐making process by augmenting the agent's action space with internal actions that select the abstraction it uses. We prove that under certain conditions this approach results in a derived MDP whose solution yields both the optimal abstraction for the original MDP and the optimal policy under that abstraction. We examine our approach in three domains of increasing complexity: contextual bandit problems, episodic MDPs, and general MDPs with context‐specific structure. © 2013 Wiley Periodicals, Inc.     

Teaching, Exploring, Learning—Developing Tutorials for In-Class Teaching and Self-Learning

This paper presents an experience report on a novel approach for a course on intermediate and advanced computer graphics topics. The approach uses Teachlet Tutorials, a combination of traditional seminar–type teaching with interactive exploration of the content by the audience, plus development of self-contained tutorials on the topic. In addition to a presentation, an interactive software tool is developed by the students to assist the audience in learning and exploring the topic's details. This process is guided through set tasks. The resulting course material is developed for two different contexts: (a) for classroom presentation and (b) as an interactive, self-contained, self-learning tutorial. The overall approach results in a more thorough understanding of the topic both for the student teachers as well as for the class participants. In addition to detailing the Teachlet Tutorial approach, this paper presents our experiences implementing the approach in our Advanced Computer Graphics course and presents the resultant projects. Most of the final Teachlet Tutorials were surprisingly good and we had excellent feedback from the students on the approach and course.     

Measuring and evaluating IS expectations and benefit success from B2B electronic trading: a new survey approach

This article demonstrates a survey approach for measuring and evaluating IS benefit success from business-to-business (B2B) electronic trading. This article is of significance in demonstrating practical benefit success mechanisms for evaluating complex IS projects. A new survey approach is used to help evaluate the IS benefit success for each participating organisation. Disconfirmation theory and the expectations paradigm are used to justify the overall approach taken. A central tenet of the overall evaluation approach has been the need for a combined evaluation of benefit success based on interpreting or diagnosing two outcomes: (a) the ‘realised benefit outcome’ (RBO), or the actual number of realised strategic and operational benefits a company has achieved, regardless of initial expectations, as well as (b) the ‘benefit state outcome’ (BSO), or the extent of benefit planning gap (BPG) experienced within each company relative to their original expectations. This article demonstrates in detail how to measure benefit success from survey data using a perceptual self-assessed rating instrument. The approach will be useful for other academics and practitioners in the development of usable IS benefits evaluation mechanisms.     

基于图嵌入的软件项目源代码检索方法

源代码检索是软件工程领域的一项重要研究问题,其主要任务是检索和复用软件项目API（application program interface,应用程序接口）.随着软件项目的规模越来越大、越来越复杂,当前,源代码检索一方面需要提高基于自然语言API查询的准确性,另一方面需要定位和展示目标API及其相关代码之间的关联,以更好地辅助用户理解API的实现逻辑和使用场景.为此,提出一种基于图嵌入的软件项目源代码检索方法.该方法能够基于软件项目源代码自动构建其代码结构图,并通过图嵌入对源代码进行信息表示.在此基础上,用户可以输入自然语言问题、检索并返回相关的API及其关联信息构成的连通代码子图,从而提高API检索和复用的效率.在以开源项目Apache Lucene和POI为例的检索实验中,该方法检索结果的F1值比现有基于最短路径的方法提高了10%,同时显著缩短了平均响应时间.     

Adaptability mechanisms for autonomic system implementation with AAOP

This paper presents a new approach to implementing an adaptability loop in Autonomic Computing (AC) systems, which is based on adaptable aspects. The approach utilizes the concept of adaptable aspect‐oriented programming (AAOP) in which a set of AOP aspects is used to run an application in the manner specified by its adaptability strategy. We present a model execution environment based on this concept, enabling the execution of applications with applied adaptability strategies. In the AAOP‐based AC system, the application is instrumented with aspects selected by the system from a set of all available aspects (sensors, effectors, and goal aspects) in such a way that the system can monitor and manage the application. This model can be used to implement systems that are able to monitor an application and its execution environment, and perform actions such as changing the current set of non‐functional constraints in response to changes in the application or its environment. The model can be used for various types of non‐functional goals, in various programming languages, both in centralized and distributed environments. This paper describes its Java‐based implementation and non‐functional goals referring to resource management. As a consequence, the application uses resources in a way specified in its adaptability strategy. Resource consumption management logic is transparent for the application, meaning that no modifications in the application source code are needed. Copyright © 2010 John Wiley & Sons, Ltd.     

Cy-Clone: An approach to the engineering of resource adequate cyclic real-time systems

The cyclic paradigm is used quite widely in real-time system applications, and is the most predominant approach taken for hard real-time systems. At the same time, there has been an absence of research and development related to solving existing problems as well as in finding new avenues for generalizing the applicability of the cyclic paradigm. For example, there has been very little research and development aimed at exploiting the cyclic paradigm in parallel processing environments. In this paper, we consider Cy-Clone (a Clone of the Cyclic paradigm) which provides a holistic approach to developing deterministic real-time systems according to a variant of the cyclic paradigm for both single processor and multiprocessor environments. The approach is especially applicable in time and safety critical systems.The problem-oriented philosophy upon which Cy-Clone rests is based upon the notions of resource adequacy, that is, the provision of sufficient hardware resources, and direct mapping, that is, the direct transformation of the real-time application processes to programmed processes which are statically scheduled and allocated in a cyclic manner. Thus, complications of dynamic scheduling and administrating limited shared resources are removed. This simplification leads to significant advantages in terms of predictability, performance, reliability, testability, extendability, verifiability, security, fault tolerance and most importantly understandability.This work has been supported by (FMV), the Swedish Defense Materiel Administration. An early version of the work was also supported by Tour and Andersson Industri Automation AB (Malmö).