896 resultados para software management


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When project managers determine schedules for resource-constrained projects, they commonly use commercial project management software packages. Which resource-allocation methods are implemented in these packages is proprietary information. The resource-allocation problem is in general computationally difficult to solve to optimality. Hence, the question arises if and how various project management software packages differ in quality with respect to their resource-allocation capabilities. None of the few existing papers on this subject uses a sizeable data set and recent versions of common software packages. We experimentally analyze the resource-allocation capabilities of Acos Plus.1, AdeptTracker Professional, CS Project Professional, Microsoft Office Project 2007, Primavera P6, Sciforma PS8, and Turbo Project Professional. Our analysis is based on 1560 instances of the precedence- and resource-constrained project scheduling problem RCPSP. The experiment shows that using the resource-allocation feature of these packages may lead to a project duration increase of almost 115% above the best known feasible schedule. The increase gets larger with increasing resource scarcity and with increasing number of activities. We investigate the impact of different complexity scenarios and priority rules on the project duration obtained by the software packages. We provide a decision table to support managers in selecting a software package and a priority rule.

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We present results of a benchmark test evaluating the resource allocation capabilities of the project management software packages Acos Plus.1 8.2, CA SuperProject 5.0a, CS Project Professional 3.0, MS Project 2000, and Scitor Project Scheduler 8.0.1. The tests are based on 1560 instances of precedence– and resource–constrained project scheduling problems. For different complexity scenarios, we analyze the deviation of the makespan obtained by the software packages from the best feasible makespan known. Among the tested software packages, Acos Plus.1 and Project Scheduler show the best resource allocation performance. Moreover, our numerical analysis reveals a considerable performance gap between the implemented methods and state–of–the–art project scheduling algorithms, especially for large–sized problems. Thus, there is still a significant potential for improving solutions to resource allocation problems in practice.

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Various software packages for project management include a procedure for resource-constrained scheduling. In several packages, the user can influence this procedure by selecting a priority rule. However, the resource-allocation methods that are implemented in the procedures are proprietary information; therefore, the question of how the priority-rule selection impacts the performance of the procedures arises. We experimentally evaluate the resource-allocation methods of eight recent software packages using the 600 instances of the PSPLIB J120 test set. The results of our analysis indicate that applying the default rule tends to outperform a randomly selected rule, whereas applying two randomly selected rules tends to outperform the default rule. Applying a small set of more than two rules further improves the project durations considerably. However, a large number of rules must be applied to obtain the best possible project durations.

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Quality data are not only relevant for successful Data Warehousing or Business Intelligence applications; they are also a precondition for efficient and effective use of Enterprise Resource Planning (ERP) systems. ERP professionals in all kinds of businesses are concerned with data quality issues, as a survey, conducted by the Institute of Information Systems at the University of Bern, has shown. This paper demonstrates, by using results of this survey, why data quality problems in modern ERP systems can occur and suggests how ERP researchers and practitioners can handle issues around the quality of data in an ERP software Environment.

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Software Configuration Management (SCM) techniques have been considered the entry point to rigorous software engineering, where multiple organizations cooperate in a decentralized mode to save resources, ensure the quality of the diversity of software products, and manage corporate information to get a better return of investment. The incessant trend of Global Software Development (GSD) and the complexity of implementing a correct SCM solution grow not only because of the changing circumstances, but also because of the interactions and the forces related to GSD activities. This paper addresses the role SCM plays in the development of commercial products and systems, and introduces a SCM reference model to describe the relationships between the different technical, organizational, and product concerns any software development company should support in the global market.

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The acquisition of the information system technologies using the services of an external supplier could be the the best options to reduce the implementation and maintenance cost of software solutions, and allows a company to improve the efficient use of its resources. The focus of this paper is to outline a methodology structure for the software acquisition management. The methodology proposed in this paper is the result of the study and the convergence of the weakness and strengths of some models (CMMI, SA-CMM, ISO/IEC TR 15504, COBIT, and ITIL) that include the software acquisition process.

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This research is concerned with the experimental software engineering area, specifically experiment replication. Replication has traditionally been viewed as a complex task in software engineering. This is possibly due to the present immaturity of the experimental paradigm applied to software development. Researchers usually use replication packages to replicate an experiment. However, replication packages are not the solution to all the information management problems that crop up when successive replications of an experiment accumulate. This research borrows ideas from the software configuration management and software product line paradigms to support the replication process. We believe that configuration management can help to manage and administer information from one replication to another: hypotheses, designs, data analysis, etc. The software product line paradigm can help to organize and manage any changes introduced into the experiment by each replication. We expect the union of the two paradigms in replication to improve the planning, design and execution of further replications and their alignment with existing replications. Additionally, this research work will contribute a web support environment for archiving information related to different experiment replications. Additionally, it will provide flexible enough information management support for running replications with different numbers and types of changes. Finally, it will afford massive storage of data from different replications. Experimenters working collaboratively on the same experiment must all have access to the different experiments.

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There is no empirical evidence whatsoever to support most of the beliefs on which software construction is based. We do not yet know the adequacy, limits, qualities, costs and risks of the technologies used to develop software. Experimentation helps to check and convert beliefs and opinions into facts. This research is concerned with the replication area. Replication is a key component for gathering empirical evidence on software development that can be used in industry to build better software more efficiently. Replication has not been an easy thing to do in software engineering (SE) because the experimental paradigm applied to software development is still immature. Nowadays, a replication is executed mostly using a traditional replication package. But traditional replication packages do not appear, for some reason, to have been as effective as expected for transferring information among researchers in SE experimentation. The trouble spot appears to be the replication setup, caused by version management problems with materials, instruments, documents, etc. This has proved to be an obstacle to obtaining enough details about the experiment to be able to reproduce it as exactly as possible. We address the problem of information exchange among experimenters by developing a schema to characterize replications. We will adapt configuration management and product line ideas to support the experimentation process. This will enable researchers to make systematic decisions based on explicit knowledge rather than assumptions about replications. This research will output a replication support web environment. This environment will not only archive but also manage experimental materials flexibly enough to allow both similar and differentiated replications with massive experimental data storage. The platform should be accessible to several research groups working together on the same families of experiments.

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The aim of the paper is to discuss the use of knowledge models to formulate general applications. First, the paper presents the recent evolution of the software field where increasing attention is paid to conceptual modeling. Then, the current state of knowledge modeling techniques is described where increased reliability is available through the modern knowledge acquisition techniques and supporting tools. The KSM (Knowledge Structure Manager) tool is described next. First, the concept of knowledge area is introduced as a building block where methods to perform a collection of tasks are included together with the bodies of knowledge providing the basic methods to perform the basic tasks. Then, the CONCEL language to define vocabularies of domains and the LINK language for methods formulation are introduced. Finally, the object oriented implementation of a knowledge area is described and a general methodology for application design and maintenance supported by KSM is proposed. To illustrate the concepts and methods, an example of system for intelligent traffic management in a road network is described. This example is followed by a proposal of generalization for reuse of the resulting architecture. Finally, some concluding comments are proposed about the feasibility of using the knowledge modeling tools and methods for general application design.

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In the last decades, software systems have become an intrinsic element in our daily lives. Software exists in our computers, in our cars, and even in our refrigerators. Today’s world has become heavily dependent on software and yet, we still struggle to deliver quality software products, on-time and within budget. When searching for the causes of such alarming scenario, we find concurrent voices pointing to the role of the project manager. But what is project management and what makes it so challenging? Part of the answer to this question requires a deeper analysis of why software project managers have been largely ineffective. Answering this question might assist current and future software project managers in avoiding, or at least effectively mitigating, problematic scenarios that, if unresolved, will eventually lead to additional failures. This is where anti-patterns come into play and where they can be a useful tool in identifying and addressing software project management failure. Unfortunately, anti-patterns are still a fairly recent concept, and thus, available information is still scarce and loosely organized. This thesis will attempt to help remedy this scenario. The objective of this work is to help organize existing, documented software project management anti-patterns by answering our two research questions: · What are the different anti-patterns in software project management? · How can these anti-patterns be categorized?