5 research outputs found
ELECTRONIC REQUIREMENTS NEGOTIATION β A LITERATURE SURVEY ON THE STATE-OF-THE-ART (23)
In the software development process, requirements negotiation is an essential part in which stakeholders jointly have to come to an agreement. Such a negotiation process is often conducted using information systems, which makes it an electronic requirements negotiation process. The aim of the current paper is to present the state-of-the-art in electronic requirements negotiations. We elicit the state-of-the-art by analysing relevant literature, extracting areas of current research, and describing the status quo of each area. The identified areas of research are foundations of electronic requirements negotiation, electronic requirements negotiation methodology, automation of electronic requirements negotiation, computer- mediated communication, and social communication
An Empirical Framework Design to Examine the Improvement in Software Requirements through Negotiation
Negotiation is one promising effort
during requirements elicitation process
to improve the quality of software
requirements. When negotiation is
claimed beneficial theoretically, it is
important that the deployment of
negotiation is examined and the
effectiveness of negotiation is evaluated
through empirical study. This paper aims
at providing an empirical framework
design to examine the improvement in
software requirements through
negotiation. Besides, it elaborates the
relevance of negotiation in requirements
elicitation process and its effectiveness.
An empirical study method is imposed to
design the framework. The design is
carefully established based the selection
of population and participants, the
experimental protocol, threats to validity
and justification of measures
Techno-economic analysis and decision making for PHEV benefits to society, consumers, policymakers and automakers
2012 Summer.Includes bibliographical references.Plug-in hybrid electric vehicles (PHEVs) are an emerging automotive technology that has the capability to reduce transportation environmental impacts, but at an increased production cost. PHEVs can draw and store energy from an electric grid and consequently show reductions in petroleum consumption, air emissions, ownership costs, and regulation compliance costs, and various other externalities. Decision makers in the policy, consumer, and industry spheres would like to understand the impact of HEV and PHEV technologies on the U.S. vehicle fleets, but to date, only the disciplinary characteristics of PHEVs been considered. The multidisciplinary tradeoffs between vehicle energy sources, policy requirements, market conditions, consumer preferences and technology improvements are not well understood. For example, the results of recent studies have posited the importance of PHEVs to the future US vehicle fleet. No studies have considered the value of PHEVs to automakers and policy makers as a tool for achieving US corporate average fuel economy (CAFE) standards which are planned to double by 2030. Previous studies have demonstrated the cost and benefit of PHEVs but there is no study that comprehensively accounts for the cost and benefits of PHEV to consumers. The diffusion rate of hybrid electric vehicle (HEV) and PHEV technology into the marketplace has been estimated by existing studies using various tools and scenarios, but results show wide variations between studies. There is no comprehensive modeling study that combines policy, consumers, society and automakers in the U.S. new vehicle sales cost and benefits analysis. The aim of this research is to build a potential framework that can simulate and optimize the benefits of PHEVs for a multiplicity of stakeholders. This dissertation describes the results of modeling that integrates the effects of PHEV market penetration on policy, consumer and economic spheres. A model of fleet fuel economy and CAFE compliance for a large US automaker will be developed. A comprehensive total cost of ownership model will be constructed to calculate and compare the cost and benefits of PHEVs, conventional vehicles (CVs) and HEVs. Then a comprehensive literature review of PHEVs penetration rate studies will be developed to review and analyze the primary purposes, methods, and results of studies of PHEV market penetration. Finally a multi-criteria modeling system will incorporate results of the support model results. In this project, the models, analysis and results will provide a broader understanding of the benefits and costs of PHEV technology and the parties to whom those benefits accrue. The findings will provide important information for consumers, automakers and policy makers to understand and define HEVs and PHEVs costs, benefits, expected penetration rate and the preferred vehicle design and technology scenario to meet the requirements of policy, society, industry and consumers
Configuration of service oriented architectures with semantic technologies based on non-functional requirements
ΠΠ²Π° Π΄ΠΈΡΠ΅ΡΡΠ°ΡΠΈΡΠ° ΡΠ΅ ΡΠΎΠΊΡΡΠΈΡΠ°Π½Π° Π½Π° ΠΏΡΠΈΠΌΠ΅Π½Ρ ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠΊΠΈΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ° Π·Π°
ΡΠ΅ΡΠ°Π²Π°ΡΠ΅ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ° ΠΎΠΏΡΠΈΠΌΠ°Π»Π½Π΅ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠ°ΡΠΈΡΠ΅ ΡΠ΅ΡΠ²ΠΈΡΠ½ΠΎ-ΠΎΡΠΈΡΠ΅Π½ΡΠΈΡΠ°Π½ΠΈΡ
Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΠ° (Π΅Π½Π³Π». Service Oriented Architecture β SOA) Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ
Π½Π΅ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½ΠΈΡ
Π·Π°Ρ
ΡΠ΅Π²Π° ΠΊΠΎΡΠΈΡΠ½ΠΈΠΊΠ°. Π Π΅ΡΠ΅ΡΠ΅ ΡΠ΅ Π±Π°Π·ΠΈΡΠ°Π½ΠΎ Π½Π° ΠΏΡΠΎΡΠΈΡΠ΅ΡΡ ΠHP
Π°Π»Π³ΠΎΡΠΈΡΠΌΠ° Π·Π° ΡΠ°Π΄ ΡΠ° ΡΠ°Π·Π»ΠΈΡΠΈΡΠΈΠΌ Π²ΡΡΡΠ°ΠΌΠ° Π·Π°Ρ
ΡΠ΅Π²Π° ΠΈ ΡΠ°Π·Π²ΠΎΡΡ Ρ
Π΅ΡΡΠΈΡΡΠΈΡΠΊΠΎΠ³ ΠΏΡΠΈΡΡΡΠΏΠ°
Π·Π°ΡΠ½ΠΎΠ²Π°Π½ΠΎΠ³ Π½Π° Π³Π΅Π½Π΅ΡΠΈΡΠΊΠΈΠΌ Π°Π»Π³ΠΎΡΠΈΡΠΌΠΈΠΌΠ° Π·Π° ΡΠ΅ΡΠ°Π²Π°ΡΠ΅ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠ° ΠΎΠΏΡΠΈΠΌΠ°Π»Π½Π΅
ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠ°ΡΠΈΡΠ΅. ΠΠΎΡΡΠΎΡΠ΅ΡΠ° ΡΠ΅ΡΠ΅ΡΠ° Ρ ΠΎΠ²ΠΎΡ ΠΎΠ±Π»Π°ΡΡΠΈ ΡΡ ΠΏΠΎΠΊΠ°Π·Π°Π»Π° ΠΈΠ·ΡΠ·Π΅ΡΠ½ΠΎ ΠΌΠ°Π»ΠΈ Π½ΠΈΠ²ΠΎ
ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΠΈΠ·Π°ΡΠΈΡΠ΅, ΡΡ ΠΊΠΎΡΠΈΡΠ½ΠΈΡΠΈΠΌΠ° Π½ΠΈΡΠ΅ Π΄ΠΎΠ·Π²ΠΎΡΠ΅Π½ΠΎ Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°ΡΠ΅ ΡΠ°Π·Π½ΠΈΡ
ΡΠΎΡΠΈΡΡΠΈΡΠΈΡΠ°Π½ΠΈΡΠΈΡ
Π²ΡΡΡΠ° Π·Π°Ρ
ΡΠ΅Π²Π° ΠΊΠΎΡΠΈ ΠΎΡΠ»ΠΈΠΊΠ°Π²Π°ΡΡ ΡΠΈΡ
ΠΎΠ²Π΅ ΠΆΠ΅ΡΠ΅, ΠΎΡΠ΅ΠΊΠΈΠ²Π°ΡΠ° ΠΈ
ΡΡΡΠΎΠ³Π΅ Π·Π°Ρ
ΡΠ΅Π²Π΅ Π·Π° ΠΊΠΎΡΠ΅ Π·Π°Ρ
ΡΠ΅Π²Π°ΡΡ ΠΏΠΎΡΠΏΡΠ½ΠΎ ΠΈΡΠΏΡΡΠ΅ΡΠ΅. Π’Π°ΠΊΠΎΡΠ΅, ΠΏΠΎΡΡΠΎΡΠ΅ΡΠ° ΡΠ΅ΡΠ΅ΡΠ° ΡΡ
Π±ΠΈΠ»Π° ΠΏΠ΅ΡΠΌΠ°Π½Π΅Π½ΡΠ½ΠΎ ΡΠΎΠΊΡΡΠΈΡΠ°Π½Π° Π½Π° ΠΈΡΠΏΡΡΠ΅ΡΠ΅ Π·Π°Ρ
ΡΠ΅Π²Π° ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½ΠΎΡΡΠΈ, Π½Π°ΠΊΠΎΠ½ ΡΠ΅Π³Π°
ΡΠ΅ Π²ΡΡΠΈ ΠΎΠ΄Π°Π±ΠΈΡ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠ°ΡΠΈΡΠ΅ ΡΡ
ΠΎΠ΄Π½ΠΎ Π·Π°Ρ
ΡΠ΅Π²ΠΈΠΌΠ° ΠΎ ΡΠΌΠ°ΡΠ΅ΡΡ Π²ΡΠ΅Π΄Π½ΠΎΡΡΠΈ
ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° ΠΊΠΎΡΠ΅ ΠΈΠΌΠ°ΡΡ ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΡΡ ΡΠ°ΡΡΠ° (Π½ΠΏΡ., ΡΠ΅Π½Π° ΠΈ Π²ΡΠ΅ΠΌΠ΅ ΠΈΠ·Π²ΡΡΠ°Π²Π°ΡΠ°),
ΠΎΠ΄Π½ΠΎΡΠ½ΠΎ ΠΏΠΎΠ²Π΅ΡΠ°ΡΡ Π²ΡΠ΅Π΄Π½ΠΎΡΡΠΈ ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ° ΠΊΠΎΡΠ΅ ΠΈΠΌΠ°ΡΡ ΡΠ΅Π½Π΄Π΅Π½ΡΠΈΡΡ ΠΎΠΏΠ°Π΄Π°ΡΠ°
(Π½ΠΏΡ., ΠΏΠΎΡΠ·Π΄Π°Π½ΠΎΡΡ ΠΈ Π΄ΠΎΡΡΡΠΏΠ½ΠΎΡΡ). ΠΠ΅ΡΡΡΠΈΠΌ, ΠΊΠ°Π΄Π° ΡΠ΅ ΠΏΠΎΡΠΌΠ°ΡΡΠ°ΡΡ ΡΠ΅Π»Π΅ ΡΠ°ΠΌΠΈΠ»ΠΈΡΠ΅
SOA, ΠΎΠ΄ ΠΏΠΎΡΠ΅Π±Π½ΠΎΠ³ Π·Π½Π°ΡΠ°ΡΠ° ΠΏΠΎΡΡΠ°ΡΠ΅ ΠΏΡΠΎΠ±Π»Π΅ΠΌ ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΡΠ΅ ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠ°ΡΠΈΡΠ΅ ΠΏΡΠΈ
ΠΈΡΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½ΠΎΠΌ Π·Π°Π΄ΠΎΠ²ΠΎΡΠ΅ΡΡ ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½ΠΈΡ
ΠΈ Π½Π΅ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½ΠΈΡ
Π·Π°Ρ
ΡΠ΅Π²Π°.
ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎ ΠΈΠ½ΡΠ΅Π³ΡΠ°Π»Π½ΠΎ ΡΠ΅ΡΠ΅ΡΠ΅ ΠΏΠΎΠ΄ Π½Π°Π·ΠΈΠ²ΠΎΠΌ OptConfSOAFΠΎΠ±Π΅Π·Π±Π΅ΡΡΡΠ΅
ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ°ΡΠ΅ ΡΠ°Π·Π»ΠΈΡΠΈΡΠΈΡ
Π²ΡΡΡΠ° Π·Π°Ρ
ΡΠ΅Π²Π° (Π±Π΅Π·ΡΡΠ»ΠΎΠ²Π½ΠΈ, ΡΡΠ»ΠΎΠ²Π½ΠΈ, Π·Π°Ρ
ΡΠ΅Π²ΠΈ ΠΎ
Π»Π΅ΠΊΡΠΈΠΊΠΎΠ³ΡΠ°ΡΡΠΊΠΎΠΌ ΠΏΠΎΡΠ΅ΡΠΊΡ) ΠΎ Π½Π΅ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½ΠΈΠΌ ΠΊΠ°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊΠ°ΠΌΠ° ΠΈ ΠΎΠΏΡΠΈΠΌΠ°Π»Π½Ρ
ΠΊΠΎΠ½ΡΠΈΠ³ΡΡΠ°ΡΠΈΡΡ ΡΠ°ΠΌΠΈΠ»ΠΈΡΠ° SOA Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°Π½ΠΈΡ
Π·Π°Ρ
ΡΠ΅Π²Π°. ΠΡΠΈΡΡΡΠΏ ΠΊΠΎΡΠΈ ΡΠ΅
ΠΏΡΠ΅Π΄Π»Π°ΠΆΠ΅ ΠΎΠ±Π΅Π·Π±Π΅ΡΡΡΠ΅ ΠΈΡΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½ΠΎ Π·Π°Π΄ΠΎΠ²ΠΎΡΠ΅ΡΠ΅ Π·Π°Ρ
ΡΠ΅Π²Π° ΠΊΠΎΡΠΈ ΡΠ΅ ΡΠΈΡΡ
ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½ΠΎΡΡΠΈ ΡΠΈΡΡΠ΅ΠΌΠ° ΠΊΠ°ΠΎ ΠΈ Π½Π΅ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½ΠΈΡ
Π·Π°Ρ
ΡΠ΅Π²Π° ΠΊΠΎΡΠΈ ΠΌΠΎΠ³Ρ Π±ΠΈΡΠΈ
ΡΠ°Π·Π»ΠΈΡΠΈΡΠΎΠ³ Π½ΠΈΠ²ΠΎΠ° ΠΏΡΠΈΠΎΡΠΈΡΠ΅ΡΠ°, ΠΎΠ΄Π½ΠΎΡΠΈΡΠΈ ΡΠ΅ Π½Π° ΠΏΠΎΡΠ΅Π΄ΠΈΠ½Π΅ Π΄Π΅Π»ΠΎΠ²Π΅ ΠΈΠ»ΠΈ ΡΠ΅ΡΠ²ΠΈΡΠ½ΠΎ-
ΠΎΡΠΈΡΠ΅Π½ΡΠΈΡΠ°Π½Ρ Π°ΡΡ
ΠΈΡΠ΅ΠΊΡΡΡΡ Ρ ΡΠ΅Π»ΠΎΡΡΠΈ.
ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎ ΡΠ΅ΡΠ΅ΡΠ΅ ΡΠ΅ ΠΎΠΏΡΡΠ΅ ΠΈ Π½ΠΈΡΠ΅ ΠΎΠ³ΡΠ°Π½ΠΈΡΠ΅Π½ΠΎ ΡΠ°ΠΌΠΎ Π½Π° Π²Π΅Π± ΡΠ΅ΡΠ²ΠΈΡΠ΅, ΠΈΠ°ΠΊΠΎ
ΡΠ΅ ΠΏΠΎΡΠ°ΠΌ ΡΠ΅ΠΌΠ°Π½ΡΠΈΡΠΊΠΈΡ
ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡΠ° ΠΎΠ±ΠΈΡΠ½ΠΎ Π²Π΅Π·ΡΡΠ΅ Π·Π° Π΄Π°ΡΠΈ Π΄ΠΎΠΌΠ΅Π½ ΠΏΡΠΈΠΌΠ΅Π½Π΅. Π Π΅ΡΠ΅ΡΠ΅
ΡΠ΅ ΠΌΠΎΠΆΠ΅ ΠΏΡΠΈΠΌΠ΅Π½ΠΈΡΠΈ Ρ Π±ΠΈΠ»ΠΎ ΠΊΠΎΠΌ Π΄ΠΎΠΌΠ΅Π½Ρ Ρ ΠΊΠΎΡΠ΅ΠΌ ΡΠ΅ SOA ΠΏΠ°ΡΠ°Π΄ΠΈΠ³ΠΌΠ° ΠΌΠΎΠΆΠ΅
ΠΏΡΠΈΠΌΠ΅Π½ΠΈΡΠΈ ΠΏΠΎΡΠΌΠ°ΡΡΠ°ΡΠ΅ΠΌ ΡΠ΅ΡΠ²ΠΈΡΠ° ΠΊΠ°ΠΎ Π±ΠΈΠ»ΠΎ ΠΊΠΎΡΠ΅ ΠΊΠΎΠΌΠΏΠΎΠ½Π΅Π½ΡΠ΅ (Π½Π΅ΠΎΠ±Π°Π²Π΅Π·Π½ΠΎ
ΡΠΎΡΡΠ²Π΅ΡΡΠΊΠ΅) Π΄Π°ΡΠ΅ ΡΡΠ½ΠΊΡΠΈΠΎΠ½Π°Π»Π½ΠΎΡΡΠΈ...This dissertation is focused on the application of semantic technologies for solving the
problem of optimal configuration of service-oriented architectures (SOA) based on
stakeholdersβ non-functional requirements. The proposed solution is developed as an
extension of the AHP algorithm to allow for processing of different kinds of
requirements. To address the problem of optimal configuration of SOA, a heuristic
approach based on genetic algorithms has also been proposed and validated.
Existing approaches in this field have shown low level of personalization, i.e.
stakeholders are neither enabled to define sophisticated requirements that reflect their
own expectations and attitudes, nor they are able to indicate hard requirements that have
to be fully satisfied. Furthermore, existing approaches were primarily addressing the
problem of fulfilling functional requirements, while the selection of an appropriate
configuration is driven by the goal of decreasing the values of monotonically decreasing
features (e.g., price and execution time) and simultaneous increasing the values of
monotonically increasing features (e.g., availability and reliability). By considering the
whole SOA families, the problem of configuration based on both functional and nonfunctional
requirements gets special importance for research and further applications.
The proposed solution, titled OptConfSOAF provides a framework for
specification and processing of different kinds of requirements (unconditional,
conditional, and requirements about lexicographical order) over non-functional features,
and further optimal configuration of SOA families. The proposed approach provides
simultaneous fulfillment of functional requirements (i.e., requirements related to the
systemβs functionalities) and non-functional requirements, where the latter could be
defined with different level of importance, for specific parts of a SOA-based system or
the system in its entirety.
The proposed solution is general and is not bound to web services, even though
semantic technologies are often associated with that domain. Since the solution
considers a service as a component (no mandatory to be software component) with the
specified functionality, it is applicable and easily adaptable to any specific application
domain where SOA paradigm may be applied..
Requirements Negotiation Using Multi-Criteria Preference Analysis
Many software projects have failed because their requirements were poorly negotiated among stakeholders. Reaching agreements of negotiated requirements among stakeholders who have different concerns, responsibilities, and priorities is quite challenging. Formal (fully-automated) approaches of requirements negotiation require significant efforts of knowledge representation and validation, whereas informal (manual) approaches do not provide systematic methods of requirements negotiation. This paper proposes a novel light-weighted, yet systematic requirements negotiation model, called "Multi-Criteria Preference Analysis Requirements Negotiation (MPARN) " to guide stakeholders to evaluate, negotiate, and agree upon alternatives among stakeholders using multi-criteria preference analysis theory. This eight-step MPARN model was applied to requirements gathered for an industrial-academic repository system. The result showed that the MPARN model assisted stakeholders to have unbiased aspects within a requirements negotiation in a light-weighted way and increase stakeholders β levels of cooperation and trust by measuring each stakeholderβs preference and value function explicitly through a step-by-step process