4910050
Empirical Study on Benchmarking Software Development Tasks
Benchmarking is one of the most important methods to learn the best practices for software process improvement. However, in current software process context, benchmarking is mainly for projects rather than software development tasks. Can we benchmark software development tasks? If so, how to? Moreover, benchmarking software development tasks has to deal with multivariate and variable return to scale (VRS). This paper reports practical experience of benchmarking software development tasks under multivariate and VRS constraints using Data Envelopment Analysis (DEA). The analysis of experience data in Institute of Software, Chinese Academy of Sciences (ISCAS) indicates that the ideas and techniques of benchmarking software projects can be deployed at the software development task level. Moreover, results also show that DEA VRS model allows the developers to gain new insight about how to identify the relatively efficient tasks as the task performance benchmark and how to establish different reference sets for each relatively inefficient task under multivariate and VRS constraints. We thus recommend DEA VRS model be used as the default technique for appropriately benchmarking software development tasks. Our results are beneficial to software process improvement. To the best of our knowledge, we believe that it is the first time to report such comprehensive and repeatable results of benchmarking software development tasks using DEA.
4924842
Assigning Local Fixed-time Constraints in Grid Workflow Systems
Many complex grid workflow processes often have only one global fixed-time constraint at the last activity. Since grid workflow execution normally lasts a long time, local control is very important to ensure the overall temporal correctness. With only one global fixed-time constraint, we cannot control grid workflow execution locally in terms of time. As a result, for any temporal violations, we must handle them globally with the consideration of all activities. This would impact the overall cost-effectiveness of grid workflow execution. Therefore, in this paper, we investigate how to assign local fixed-time constraints within the global one so that we can control grid workflow execution locally. Corresponding assigning and verification methods are developed. With local fixed-time constraints, we can achieve better cost-effectiveness
4928164
A service workflow management framework based on peer-to-peer and agent technologies
Service workflow management which consolidates multiple services to achieve business goals has become a critical issue in service-oriented computing. Due to the unique feature of service workflows such as full distribution and high dynamicity, the contemporary workflow technology has exhibited inefficiency, vulnerability, inflexibility and lack of adaptability. Based upon the authors' previous work on peer-to-peer based workflow management and seamless integration of agents and Web services, this paper innovatively presents SwinDeW-A which is a decentralised service workflow management framework based on peer-to-peer and agent technologies. Based on this framework, this paper also discusses how autonomous service level agreement negotiation, decentralised process enactment, and autonomous process adaptation can be achieved. The proposed approach takes advantages of the peer-to-peer computing technology and the agent technology to provide more efficient, reliable, flexible and adaptive service workflow management.
3428244
An Organisational Perspective on Collaborative Business Processes
Business collaboration is about coordinating the flow of information among organisations and linking their business processes. It brings great challenge to keep participating organisations as autonomous entities in integrating business processes of these organisations seamlessly. To address this issue, we develop a new perspective on business collaborations with a novel concept called relative workflow, which defines what a participating organisation can perceive in collaboration. By incorporating a visibility control mechanism, relative workflows allow each organisation to define its own collaboration structure and behaviours. In this paper, we present a formal definition of relative workflows and related algorithms for generating relative workflows, along with a discussion on how to perform tracking over relative workflows.
14447070
Achieving convergence, causality preservation, and intention preservation in real-time cooperative editing systems
Real-time cooperative editing systems allow multiple users to view and edit the same text/graphic/image/multimedia document at the same time for multiple sites connected by communication networks. Consistency maintenance is one of the most significant challenges in designing and implementing real-time cooperative editing systems. In this article, a consistency model, with properties of convergence, causality preservation, and intention preservation, is proposed as a framework for consistency maintenance in real-time cooperative editing systems. Moreover, an integrated set of schemes and algorithms, which support the proposed consistency model, are devised and discussed in detail. In particular, we have contributed (1) a novel generic operation transformation control algorithm for achieving intention preservation in combination with schemes for achieving convergence and causality preservation and (2) a pair of reversible inclusion and exclusion transformation algorithms for stringwise operations for text editing. An Internet-based prototype system has been built to test the feasibility of the proposed schemes and algorithms
1701823
Dynamic checking of temporal constraints for concurrent workflows
At present, workflow management systems have not sufficiently dealt with the issues of time, involving time modelling at build-time and time management at run-time. They are lack of the ability to support the checking of temporal constraints at run-time. Although some approaches have been devised to tackle this problem, they are limited to a single workflow and use only static techniques to verify temporal constraints. In reality, there are multiple workflows executing concurrently in a workflow management system. There may well exist resource constraints between these concurrent workflows, which affect significantly the verification of temporal constraints at run-time. This paper proposes a novel approach for dynamic verification of temporal constraints for concurrent workflows. We first investigate resource constraints in workflow management systems, and then define concurrent workflow executions. Based on these definitions, we propose a verification method by analysing the temporal relationship and resource constraints between activities among concurrent workflows.
1856845
Typing evolving ambients
This paper presents a type system that deals with the type evolution problem of the ambient calculus. It breaks the law that the open capability must introduce to the opening process the exact type information of the opened ambient. It can also serve as a general type architecture supporting type evolution. A typical usage of the type system is illustrated in the immobile server example.
2952964
Non-Disjoint Discretization for Naive-Bayes Classifiers
Previous discretization techniques have discretized numeric attributes into disjoint intervals. We argue that this is neither necessary nor appropriate for naive-Bayes classifiers. The analysis leads to a new discretization method, Non-Disjoint Discretization (NDD). NDD forms overlapping intervals for a numeric attribute, always locating a value toward the middle of an interval to obtain more reliable probability estimation. It also adjusts the number and size of discretized intervals to the number of training instances, seeking an appropriate trade-off between bias and variance of probability estimation. We justify NDD in theory and test it on a wide cross-section of datasets. Our experimental results suggest that for naiveBayes classifiers, NDD works better than alternative discretization approaches.
7098682
High-performing feature selection for text classification
This paper reports a controlled study on a large number of filter feature selection methods for text classification. Over 100 variants of five major feature selection criteria were examined using four well-known classification algorithms: a Naive Bayesian (NB) approach, a Rocchio-style classifier, a k-nearest neighbor (kNN) method and a Support Vector Machine (SVM) system. Two benchmark collections were chosen as the testbeds: Reuters-21578 and small portion of Reuters Corpus Version 1 (RCV1), making the new results comparable to published results. We found that feature selection methods based on chi2 statistics consistently outperformed those based on other criteria (including information gain) for all four classifiers and both data collections, and that a further increase in performance was obtained by combining uncorrelated and high-performing feature selection methods.The results we obtained using only 3% of the available features are among the best reported, including results obtained with the full feature set.
156436
Learning Multiple Related Tasks using Latent Independent Component Analysis
We propose a probabilistic model based on Independent Component Analysis for learning multiple related tasks. In our model the task parameters are assumed to be generated from independent sources which account for the relatedness of the tasks. We use Laplace distributions to model hidden sources which makes it possible to identify the hidden, independent components instead of just modeling correlations. Furthermore, our model enjoys a sparsity property which makes it both parsimonious and robust. We also propose efficient algorithms for both empirical Bayes method and point estimation. Our experimental results on two multi-label text classification data sets show that the proposed approach is promising.
6730244
Nemos: a framework for axiomatic and executable specifications of memory consistency models
Summary form only given. Conforming to the underlying memory consistency rules is a fundamental requirement for implementing shared memory systems and developing multiprocessor programs. In order to promote understanding and enable automated verification, it is highly desirable that a memory model specification be both declarative and executable. We present a specification framework called Nemos (Nonoperational yet Executable Memory Ordering Specifications), which supports precise specification and automatic execution in the same framework. We employ a uniform notation based on predicate logic to define shared memory semantics in an axiomatic as well as compositional style. We also apply constraint logic programming and SAT solving to make the axiomatic specifications executable for memory model analysis. To illustrate our approach, we formalize a collection of classical memory models, including sequential consistency, coherence, PRAM, causal consistency, and processor consistency.