Estimating, planning and managing Agile Web development projects under a value-based perspective

Context: The processes of estimating, planning and managing are crucial for software development projects, since the results must be related to several business strategies. The broad expansion of the Internet and the global and interconnected economy make Web development projects be often characterized by expressions like delivering as soon as possible, reducing time to market and adapting to undefined requirements. In this kind of environment, traditional methodologies based on predictive techniques sometimes do not offer very satisfactory results. The rise of Agile methodologies and practices has provided some useful tools that, combined with Web Engineering techniques, can help to establish a framework to estimate, manage and plan Web development projects. Objective: This paper presents a proposal for estimating, planning and managing Web projects, by combining some existing Agile techniques with Web Engineering principles, presenting them as an unified framework which uses the business value to guide the delivery of features. Method: The proposal is analyzed by means of a case study, including a real-life project, in order to obtain relevant conclusions. Results: The results achieved after using the framework in a development project are presented, including interesting results on project planning and estimation, as well as on team productivity throughout the project. Conclusion: It is concluded that the framework can be useful in order to better manage Web-based projects, through a continuous value-based estimation and management process.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-

Requirements Prioritisation and Retrospective Analysis for Release Planning Process Improvement

The quality of a product can be defined by its ability to satisfy the needs and expectations of its customers. Achieving quality is especially difficult in market-driven situations since the product is released on an open market with numerous potential customers and users with various wishes. The quality of the software product is to a large extent determined by the quality of the requirements engineering (RE) and release planning decisions regarding which requirements that are selected for a product. The goal of this thesis is to enhance software product quality and increase the competitive edge of software organisations by improving release planning decision-making. The thesis is based on empirical research, including both qualitative and quantitative research approaches. The research contains a qualitative survey of RE challenges in market-driven organisations based on interviews with practitioners. The survey provided increased understanding of RE challenges in the software industry and gave input to the continued research. Among the challenging issues, one was selected for further investigation due to its high relevance to the practitioners: requirements prioritisation and release planning decision-making. Requirements prioritisation techniques were evaluated through experiments, suggesting that ordinal scale techniques based on grouping and ranking may be valuable to practitioners. Finally, a retrospective method called PARSEQ (Post-release Analysis of Requirements SElection Quality) is introduced and tested in three case studies. The method aims at evaluating prior releases and finding improvement proposals for release planning decision-making in future release projects. The method was found valuable by all participants and relevant improvement proposals were discovered in all cases

National Environmental Policy During the Clinton Years

We review major developments in national environmental policy during the Clinton Administration, defining environmental policy to include not only the statutes, regulations, and policies associated with reducing pollution, but also major issues of public lands management and species preservation. We adopt economic criteria for policy assessment and highlight a set of five themes that emerge in the economics of national environmental policy over the past decade. First, over the course of the decade, national environmental targets were made more stringent, and environmental quality improved. Most important among the new targets were the National Ambient Air Quality Standards (NAAQS) for ambient ozone and particulate matter, issued by EPA in July 1997, which could turn out to be one of the Clinton Administration's most enduring environmental legacies. Also, natural resource policy during the Clinton years was heavily weighted toward environmental protection. Environmental quality improved overall during the decade, continuing a trend that began in the 1970s, although improvements were much less than during the previous two decades. Second, the use of benefit-cost analysis for assessing environmental regulation was controversial in the Clinton Administration, while economic efficiency emerged as a central goal of the regulatory reform movement in the Congress during the 1990s. When attention was given to increased efficiency, the locus of that attention during the Clinton years was the Congress in the case of environmental policies and the Administration in the case of natural resource policies. Ironically, the increased attention given to benefit-cost analysis may not have had a marked effect on the economic efficiency of environmental regulations. Third, cost-effectiveness achieved a much more prominent position in public discourse regarding environmental policy during the 1990s. From the Bush Administration through the Clinton Administration, interest and activity regarding market-based instruments for environmental protection, particularly tradeable permit systems, continued to increase. Fourth, the Clinton Administration put much greater emphasis than previous administrations on expanding the role of environmental information disclosure and voluntary programs. While such programs can provide cost-effective ways of reaching environmental policy goals, little is known about their actual costs or effectiveness. Fifth and finally, the Environmental Protection Agency placed much less emphasis on economic analysis during the 1990s. EPA leadership was more hostile to economic analysis than it had been under the prior Bush Administration, and it made organizational changes to reflect this change in priorities.

Final Report from the Models for Change Evaluation

Note: This evaluation is accompanied by an evaluation of the National Campaign for this initiative as well as introduction to the evaluation effort by MacArthur's President, Julia Stasch, and a response to the evaluation from the program team. Access these related materials here (https://www.macfound.org/press/grantee-publications/evaluation-models-change-initiative).Models for Change is an initiative of The John D. and Catherine T. MacArthur Foundationto accelerate juvenile justice reforms and promote fairer, more effective, and more developmentally appropriate juvenile justice systems throughout the United States. Between 2004 and 2014, the Foundation invested more than $121 million in the initiative, intending to create sustainable and replicable models of systems reform.In June 2013, the Foundation partnered with Mathematica Policy Research and the University of Maryland to design and conduct a retrospective evaluation of Models for Change. The evaluation focused on the core state strategy, the action network strategy, and the national context in which Models for Change played out. This report is a digest and synthesis of several technical reports prepared as part of the evaluation

A critical analysis of the retrospective introduction of tax legislation.

Masters Degree. University of KwaZulu-Natal, Durban.No abstract available

Multiobjective strategies for New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline. Formally, the NPD problem can be stated as follows: select a set of R&D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGAII type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. This work is illustrated with a study case involving nine interdependent new product candidates targeting three diseases. An analysis is performed for this test bench on the different pairs of criteria both for the bi- and tricriteria optimization: large portfolios cause resource queues and delays time to launch and are eliminated by the bi- and tricriteria optimization strategy. The optimization strategy is thus interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

Multiobjective strategies for New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline. Formally, the NPD problem can be stated as follows: select a set of R&D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGAII type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. This work is illustrated with a study case involving nine interdependent new product candidates targeting three diseases. An analysis is performed for this test bench on the different pairs of criteria both for the bi- and tricriteria optimization: large portfolios cause resource queues and delays time to launch and are eliminated by the bi- and tricriteria optimization strategy. The optimization strategy is thus interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

A Handbook of Data Collection Tools: Companion to "A Guide to Measuring Advocacy and Policy"

This handbook of data collection tools is intended to serve as a companion to A Guide to Measuring Advocacy and Policy. Organizational Research Services (ORS) developed this guide on behalf of the Annie E. Casey Foundation to support efforts to develop and implement an evaluation of advocacy and policy work. The companion handbook is dedicated to providing examples of practical tools and processes for collecting useful information from policy and advocacy efforts. Included within this handbook are a legislative process tracking log, a meeting observation checklist, a policy brief stakeholder survey, a policy tracking analysis tool, and a policy tracking form.This best practice provides an approach to measure advocacy and policy change efforts, starting with a theory of change, identifying outcome categories, and selecting practical approaches to measurement