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Table 2: Overview of current goal-oriented research in RE
"... In PAGE 6: ...ynamic aspects of goal driven approaches, i.e., the proposed way-of-working and the tool support provided for enacting this way-of-working. Using the framework of usage, subject, representation and development dimensions, it is possible to evaluate each approach against a set of criteria as shown on Table2 . The results indicate how each approach fits the framework and provide a comprehensive overview of current threads in goal-oriented research.... In PAGE 6: ... This interpretation is plausible since requirements by their very nature represent a target to be reached, a wish to be fulfilled, a vision to be materialised. Nevertheless, Table2 also indicates that research in the area is fragmented. Coverage of the area tends to focus each time on specific RE issues, whilst no research has so far taken place in order to define the overall role that goals could play in RE.... ..."
Table 2. Mapping of the goal-oriented proactive part of B-Tropos in SCIFF.
"... In PAGE 10: ...o check if the actual behavior is conformant w.r.t. a given SCIFF specification. 5 Mapping B-Tropos concepts to the SCIFF framework In this section we present the mapping of B-Tropos concepts into SCIFF speci- fications, briefly describing how the obtained formalization is used to implement the skeleton of logic-based agents. Table2 summarizes the formalization of the goal-oriented part of B-Tropos in SCIFF. Tasks and goals refer to a whatsoever actor X.... ..."
Table 2. Mapping of the goal-oriented proactive part of B-Tropos in SCIFF.
"... In PAGE 10: ...hecking if the actual behavior is conformant w.r.t. a given SCIFF specification. 5 Mapping B-Tropos concepts to the SCIFF framework In this section we present the mapping of B-Tropos concepts into SCIFF speci- fications, briefly describing how the obtained formalization is used to implement the skeleton of logic-based agents. Table2 summarizes the formalization of the goal-oriented part of B-Tropos in SCIFF. This part represents the static knowledge of the application domain, so it is modeled inside the SCIFF knowledge base.... ..."
Table 1. Algorithmic vs. Goal-Oriented Approaches to Planning Approach Advantages Disadvantages
in IMP = Impactor Spacecraft ITS = Impactor Targeting Sensor MMPAT = Multi-Mission Power Analysis Tool
"... In PAGE 3: ... Another approach to planning, favored by the research community, is to focus on the purpose or goal of each activity in the plan, and to let a computer program (the apos;planner apos;) develop an algorithm, or plan, that will satisfy the high-level goal. Each approach has its advantages and disadvantages ( Table1 ). There has also been a hybrid planner, designed and used by the MER mission, merging the capability of APGEN with those of an AI-based application (Europa).... ..."
Table 1 - Goal-based templates for goal-oriented hypotheses Item Guidelines
"... In PAGE 5: ... This link is clearly show in Figure 1 by a bold arrow. Table1 synthesises some examples of goal-based templates that should be developed to support the goal-oriented SHs formulation. In particular, it suggests some guidelines useful for establishing the items of interest of such SHs by taking into consideration the various goal-facets.... ..."
Table 1: A `score-card apos; on the advantages and disadvantages of signature-driven searches for SUSY versus model-driven.
"... In PAGE 6: ... The strategy is to pick channels of broad interest and low standard- model rate, make a priori predictions of the Standard Model rates and distributions, both from physics processes and detector e ects, and then make the measurement. The advantages and disadvantages, for there are both, are listed in Table1 . Both methods are useful, and the advent of Run II means that we need to prepare the signature-driven analyses now.... In PAGE 36: ...062 0.039 Table1 0: The number of events with N or more jets. The 95% con dence level limits on BR A in pb for events with N or more jets.... In PAGE 36: ... After searching the parameter space for regions where the search would be sensitive (large branching ratios, cross sections, and acceptance), parameters were selected as enumerated in Table 11. M1 = M2 N2 = ~ , N2 ! N1 dominates tan = 1:2 N1 = ~ hb, N2 ! N1 dominates M2 = 0:89 j j + 39 GeV N2 ! N1 dominates good acceptance for the ~ t = N1 + 5 GeV good acceptance for the b M ~ Q = 200 GeV large cross section M~ g = 210 GeV ~ g ! q ~ Q competes with ~ g ! t~ t M~ ` =500 GeV prevent C ! `~ ` MA =500 GeV H0; H ; A heavy Table1 1: The underlying assumptions and the reasons for them in the baseline model for ~ 0 2 ! ~ 0 1. The rst limit on this model considers only ~ 2 ~ 0 2 production, where the branching ratios are 100% and kinematics of the events are relatively simple.... ..."
Table 2. Core practices of agile development, and their compatibility with a model-driven software development approach (http://www.agilemodeling.com)
TABLE 6. A `score-card apos; on the advantages and disadvantages of signature-driven searches for SUSY versus model-driven.
Table 1 describes a three-level maturity model using a model-driven software factory approach, from Repeatable to Managed to Optimized developments.
"... In PAGE 2: ... Optimized A continuous feedback contributes to improve the software production and the ROI (return on investment) of the software development. Table1 . A three-level maturity model with a model-driven software factory approach Software production improvement requires strategic decisions consistent with a software factory approach.... ..."
(Table 2). Table 1. Core principles (excerpt) of agile development, and their compatibility with a model-driven software development approach (http://www.agilemodeling.com)
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