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Software Engineering, IEEE Transactions on

Issue 6 • Date June 2007

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Displaying Results 1 - 8 of 8
  • [Front cover]

    Page(s): c1
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    Freely Available from IEEE
  • [Inside front cover]

    Page(s): c2
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    Freely Available from IEEE
  • Adaptive Service Composition in Flexible Processes

    Page(s): 369 - 384
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3278 KB) |  | HTML iconHTML  

    In advanced service oriented systems, complex applications, described as abstract business processes, can be executed by invoking a number of available Web services. End users can specify different preferences and constraints and service selection can be performed dynamically identifying the best set of services available at runtime. In this paper, we introduce a new modeling approach to the Web service selection problem that is particularly effective for large processes and when QoS constraints are severe. In the model, the Web service selection problem is formalized as a mixed integer linear programming problem, loops peeling is adopted in the optimization, and constraints posed by stateful Web services are considered. Moreover, negotiation techniques are exploited to identify a feasible solution of the problem, if one does not exist. Experimental results compare our method with other solutions proposed in the literature and demonstrate the effectiveness of our approach toward the identification of an optimal solution to the QoS constrained Web service selection problem View full abstract»

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  • Integrating Software Models and Platform Models for Performance Analysis

    Page(s): 385 - 401
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    System performance is a key factor to take into account throughout the software life cycle of modern computer systems, mostly due to their typical characteristics such as distributed deployment, code mobility, and platform heterogeneity. An open challenge in this direction is to integrate the performance validation as a transparent and efficient activity in the system development process. Several methodologies have been proposed to automate the transformation of software/hardware models into performance models. In this paper, we do not take a transformational approach; rather, we present a framework to integrate a software model with a platform model in order to build a performance model. Performance indices are obtained from simulation of the resulting performance model. Our framework provides a library of predefined resource models, model annotation and integration procedures, and simulation support that makes the performance analysis a much easier activity. We present the results obtained from two different industrial case studies that show the maturity and the stability of our approach View full abstract»

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  • Empirical Validation of Three Software Metrics Suites to Predict Fault-Proneness of Object-Oriented Classes Developed Using Highly Iterative or Agile Software Development Processes

    Page(s): 402 - 419
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (10999 KB) |  | HTML iconHTML  

    Empirical validation of software metrics suites to predict fault proneness in object-oriented (OO) components is essential to ensure their practical use in industrial settings. In this paper, we empirically validate three OO metrics suites for their ability to predict software quality in terms of fault-proneness: the Chidamber and Kemerer (CK) metrics, Abreu's Metrics for Object-Oriented Design (MOOD), and Bansiya and Davis' Quality Metrics for Object-Oriented Design (QMOOD). Some CK class metrics have previously been shown to be good predictors of initial OO software quality. However, the other two suites have not been heavily validated except by their original proposers. Here, we explore the ability of these three metrics suites to predict fault-prone classes using defect data for six versions of Rhino, an open-source implementation of JavaScript written in Java. We conclude that the CK and QMOOD suites contain similar components and produce statistical models that are effective in detecting error-prone classes. We also conclude that the class components in the MOOD metrics suite are not good class fault-proneness predictors. Analyzing multivariate binary logistic regression models across six Rhino versions indicates these models may be useful in assessing quality in OO classes produced using modern highly iterative or agile software development processes. View full abstract»

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  • Feature Location Using Probabilistic Ranking of Methods Based on Execution Scenarios and Information Retrieval

    Page(s): 420 - 432
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2453 KB) |  | HTML iconHTML  

    This paper recasts the problem of feature location in source code as a decision-making problem in the presence of uncertainty. The solution to the problem is formulated as a combination of the opinions of different experts. The experts in this work are two existing techniques for feature location: a scenario-based probabilistic ranking of events and an information-retrieval-based technique that uses latent semantic indexing. The combination of these two experts is empirically evaluated through several case studies, which use the source code of the Mozilla Web browser and the Eclipse integrated development environment. The results show that the combination of experts significantly improves the effectiveness of feature location as compared to each of the experts used independently View full abstract»

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  • TSE Information for authors

    Page(s): c3
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  • [Back cover]

    Page(s): c4
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Aims & Scope

The IEEE Transactions on Software Engineering is interested in well-defined theoretical results and empirical studies that have potential impact on the construction, analysis, or management of software. The scope of this Transactions ranges from the mechanisms through the development of principles to the application of those principles to specific environments. Specific topic areas include: a) development and maintenance methods and models, e.g., techniques and principles for the specification, design, and implementation of software systems, including notations and process models; b) assessment methods, e.g., software tests and validation, reliability models, test and diagnosis procedures, software redundancy and design for error control, and the measurements and evaluation of various aspects of the process and product; c) software project management, e.g., productivity factors, cost models, schedule and organizational issues, standards; d) tools and environments, e.g., specific tools, integrated tool environments including the associated architectures, databases, and parallel and distributed processing issues; e) system issues, e.g., hardware-software trade-off; and f) state-of-the-art surveys that provide a synthesis and comprehensive review of the historical development of one particular area of interest.

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Meet Our Editors

Editor-in-Chief
Matthew B. Dwyer
Dept. Computer Science and Engineering
256 Avery Hall
University of Nebraska-Lincoln
Lincoln, NE 68588-0115 USA
tseeicdwyer@computer.org