Requirements Prioritization Based on Benefit and Cost Prediction: An Agenda for Future Research

In early phases of the software cycle, requirements prioritization necessarily relies on the specified requirements and on predictions of benefit and cost of individual requirements. This paper presents results of a systematic review of literature, which investigates how existing methods approach the problem of requirements prioritization based on benefit and cost. From this review, it derives a set of under-researched issues which warrant future efforts and sketches an agenda for future research in this area

Requirements Prioritization Based on Benefit and Cost Prediction: A Method Classification Framework

In early phases of the software development process, requirements prioritization necessarily relies on the specified requirements and on predictions of benefit and cost of individual requirements. This paper induces a conceptual model of requirements prioritization based on benefit and cost. For this purpose, it uses Grounded Theory. We provide a detailed account of the procedures and rationale of (i) how we obtained our results and (ii) how we used them to form the basis for a framework for classifying requirements prioritization methods

The Failed Promise of User Fees: Empirical Evidence from the United States Patent and Trademark Office

In an attempt to shed light on the impact of user-fee financing structures on the behavior of administrative agencies, we explore the relationship between the funding structure of the Patent and Trademark Office (PTO) and its examination practices. We suggest that the PTO’s reliance on prior grantees to subsidize current applicants exposes the Agency to a risk that its obligatory costs will surpass incoming fee collections. When such risks materialize, we hypothesize, and thereafter document, that the PTO will restore financial balance by extending preferential examination treatment—i.e., higher granting propensities and/or shorter wait times—to some technologies over others

The Failed Promise of User Fees: Empirical Evidence from the United States Patent and Trademark Office

In an attempt to shed light on the impact of user-fee financing structures on the behavior of administrative agencies, we explore the relationship between the funding structure of the Patent and Trademark Office (PTO) and its examination practices. We suggest that the PTO’s reliance on prior grantees to subsidize current applicants exposes the Agency to a risk that its obligatory costs will surpass incoming fee collections. When such risks materialize, we hypothesize, and thereafter document, that the PTO will restore financial balance by extending preferential examination treatment—i.e., higher granting propensities and/or shorter wait times—to some technologies over others

How Do Real Options Concepts Fit in Agile Requirements Engineering?

Agile requirements engineering is driven by creating business value for the client and heavily involves the client in decision-making under uncertainty. Real option thinking seems to be suitable in supporting the client’s decision making process at inter-iteration time. This paper investigates the fit between real option thinking and agile requirements engineering. We first look into previously published experiences in the agile software engineering literature to identify (i) ‘experience clusters’ suggesting the ways in which real option concepts fit into the agile requirements process and (ii) ‘experience gaps’ and under-researched agile requirements decision-making topics which require further empirical studies. Furthermore, we conducted a cross-case study in eight agile development organizations and interviewed 11 practitioners about their decision-making process. The results suggest that options are almost always identified, reasoned about and acted upon. They are not expressed in quantitative terms, however, they are instead explicitly or implicitly taken\ud into account during the decision-making process at interiteration time

Complementing Measurements and Real Options Concepts to Support Inter-iteration Decision-Making in Agile Projects

Agile software projects are characterized by iterative and incremental development, accommodation of changes and active customer participation. The process is driven by creating business value for the client, assuming that the client (i) is aware of it, and (ii) is capable to estimate the business value, associated with the separate features of the system to be implemented. This paper is focused on the complementary use of measurement techniques and concepts of real-option-analysis to assist clients in assessing and comparing alternative sets of requirements. Our overall objective is to provide systematic support to clients for the decision-making process on what to implement in each iteration. The design of our approach is justified by using empirical data, published earlier by other authors

FQPA IMPLEMENTATION TO REDUCE PESTICIDE RESIDUE RISKS: PART II: IMPLEMENTATION ALTERNATIVES AND STRATEGIES

Implementation of the Food Quality Protection Act (FQPA) is fraught with difficulty due to the divergent perspectives and demands of stakeholders in the process. In "Part I: Agricultural Producer Concerns," the authors reviewed the concerns of food producers about potential FQPA threats to farm profitability, international competitiveness, consumer perceptions, and the development of pest resistance to remaining pesticides. Fortunately, lessons from past environmental policy and economic theory offer useful principles for how to implement the FQPA. This paper, "Part II: Implementation Alternatives and Strategies" addresses ways to accommodate producer concerns while meeting the policy mandate of reducing risk from pesticide exposure, especially for infants and children. In so doing, the authors are neither advocating nor criticizing this FQPA policy mandate; rather, they are providing policy analysis of alternative implementation strategies.Crop Production/Industries, Food Consumption/Nutrition/Food Safety,

Scalable Robust Kidney Exchange

In barter exchanges, participants directly trade their endowed goods in a constrained economic setting without money. Transactions in barter exchanges are often facilitated via a central clearinghouse that must match participants even in the face of uncertainty---over participants, existence and quality of potential trades, and so on. Leveraging robust combinatorial optimization techniques, we address uncertainty in kidney exchange, a real-world barter market where patients swap (in)compatible paired donors. We provide two scalable robust methods to handle two distinct types of uncertainty in kidney exchange---over the quality and the existence of a potential match. The latter case directly addresses a weakness in all stochastic-optimization-based methods to the kidney exchange clearing problem, which all necessarily require explicit estimates of the probability of a transaction existing---a still-unsolved problem in this nascent market. We also propose a novel, scalable kidney exchange formulation that eliminates the need for an exponential-time constraint generation process in competing formulations, maintains provable optimality, and serves as a subsolver for our robust approach. For each type of uncertainty we demonstrate the benefits of robustness on real data from a large, fielded kidney exchange in the United States. We conclude by drawing parallels between robustness and notions of fairness in the kidney exchange setting.Comment: Presented at AAAI1