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Adding Goals for Reuse Practice to Pro ject Plans
Margaret (Maggie) J. Davis
Boeing Defense & Space Group
P.O. Box 3999, MS 87-37
Seattle,WA 98124-2499
Tel: (206) 773-3313
Email: mjdavis@stars.boeing.com
Fax: (206) 773-4946
Abstract
This position reports on the Software Technology for Adaptable,Reliable Software (STARS)
Reuse Strategy Model (RSM), which is a planning aid for incorporating goals to foster reuse
practices into projects. The RSM assesses the extent of change to reuse-based development and
the extent of management and technological support for the change as well asidentifying goals
that further and improve the reuse practice and support. The RSM has seen trial application
by the STARS demonstration projects that confirmed its utility as a project planning aid.
Keywords: Strategic Planning, Domain-specific reuse, reuse processes
Workshop Goals: Networking with reuse community to discuss how to influence project
planning to better support reuse and to learn what metrics are being used on reuse-based
pro jects.
Working Groups: Reuse management, organization and economics; Usefuland collectible
metrics;
Davis_M- 1
1 Background
Ms. Margaret (Maggie) J. Davis is the technical lead for reuse on the Boeing STARS project, which
was sponsored in part by ARPA under USAF contract F19628-88-D-0028. Ms. Davis has served in
a lead capacity on the Boeing STARS project since its award in 1988. She provided management
direction for the Boeing STARS Repository during itsop eration in 1988-1990; designed and coded
a prototype Ada code review and understanding tool; developed an initial design for an asset
library mechanism (ROAMS) built as a tightly integrated application on a software engineering
environment integration framework; lead the design and implementation of a decision-based search
capability for ROAMS; had the primary resp onsibility for authoring the STARS Reuse Strategy
Model; and, has been deeply involved in the joint formulation and articulation of the STARS
Conceptual Framework for Reuse Pro cesses (CFRP) [1 ].
2 Position
In the course of planning the preparation phase of the ARPA Software Technology for Adaptable,
Reliable Systems (STARS) demonstrationsof megaprogramming, it became clear that the project
teams needed more than documentation describing processes supporting or describing what is
involved in domain-specific,reuse-based software development. In particular, they needed assistance
in identifying project goals and metrics that were specific to reuse. Thus,it was decided that STARS
efforts directed at contributing to evolution of acommunity-wide reuse maturity model would be
diverted to meeting these immediate needs of the STARS demonstration teams.
Since the overall goals for the STARS demonstrations include (1) showing how reuse can be prac-
ticed and (2) assisting the organizations involved in transitioning to domain-specific, reuse-based
software-intensive systems development, it was decided that the support from the reuse technol-
ogy area to the STARS demonstration teams would be in the form of a project planning aid that
supported assessment of current reuse practice, identification of goals for improving the current
practice, and identification of metrics to measure progress against selected goals. This project
planning aid is known as the STARS Reuse Strategy Model (RSM) [2 ] since it assists in the for-
mulation of the reuse strategy to be followed on apro ject.
Unlike usual project goals that measure success in terms of delivering artifacts that meet specific
standards of quality and functionality, goals identified by the RSM measure progress with respect
to the management and engineering processes used and the managerial andtechnological context
in which the project is carried out. Goals and metrics formulated relative to processes are similar
to measures of success often used by continuous quality improvement initiatives. Goals and metrics
formulated for the managerial and technological contexts of projects are similar to measurements
on the progress of technology transition or institutionalization. Since there are organizations im-
plementing continuous quality improvement within their business processes and introducing reuse
as a new technology at the same time, the RSMshould b eapplicable beyond the scope of STARS.
That is, the RSM can be used to assess and track the extent of technological change (what reuse
processes are practiced) and of supporting infrastructure for the new technology (context).
To add some simplifying structure to assessing reuse practice, the RSM identifies 32 individual
indicators organized into five groups or dimensions. Each dimension focuses on some separable
aspect or issue relative to reuse processes used and the context in which they are executed. Because
it was not always possible to formulateeach indicator to be completely independent of every other
Davis_M- 2
one, notes and heuristics for evaluating the interdependencies are provided.
The five dimensions used in the RSM are:
fflDomain Stability (5 indicators),
fflOrganization Readiness (9 indicators),
fflExperience with Domain-specific Knowledge (6 indicators),
fflUsage of Technology for Reuse Processes (8 indicators), and
fflBusiness Climate & Reuse Management (5 indicators).
Figure 1 depicts each dimension and its indicators as a separate column. There is no significance
to the ordering of columns, nor the indicators within columns, nor is there any significance to the
ordering of indicators across rows. The indicators used resulted from analysis of previous work on
reuse maturity [3, 4 ], work in progress on reuse capability and adoption [5 ], and work in progress
on articulating the STARS vision of reuse [1 ].
The basic steps of the procedure for assessment and goal identification are to:
fflrate each indicator relative to a fixed, given scale;
ffluse the rating of each indicator as an index into a table of appropriate goals for improving
that rating;
ffluse the transition question to determine if there is effort already being applied towards those
goals;
ffluse the same table to identify measures of progress for each goal; and,
ffluse heuristics to check for consistency and to identify redundancy among the set of goals
identified.
It is assumed that once assessment and goal identification has been completed, the set of goals will
be evaluated relative to external constraints and transitions already in progress, will be arranged
from high to low priority, and a subset of the highest priority goals will actually levied against the
project. The assessment and goal formulation may be done by either a project management team
or by a management team providing coordinated reuse strategies for multiple projects.
The RSM document supports the assessment and goal identification process by supplying a uniform
set of tables that for each indicator provide:
fflan assessment question and partially ordered scale for answering the question;
ffla matrix of transition questions versus the scale values;
ffla matrix of goals and progress measures versus the scale values; and,
ffla set of notes or heuristics that help select the most appropriate answer to the assessment
question or evaluate goals.
Davis_M- 3
One of the indicator tables is shown in Figure 2. The assessment question is listed just above the
matrix. The scale of possible answers is shown on the left side of the matrix as a letter paired with
short descriptive text. Goals for improving the rating sit in the same row or in the rows below the
rating value. A transition questionthat determines if the effort is already underway for meeting
a particular goal lie in the same row as well as progress metrics appropriate to the specific goal.
Finally, heuristics on assessing the indicator or on evaluating the goals identified appear as a set of
notes below the matrix.
Since there is not a general consensus as to what reuse practices are consistently an improvement
over another, the assessment scales are ordered by degree of sophistication of the practice. And, the
reader is warned that greater sophistication is not necessarily b etterin the notes for each indicator
whose assessment scale is known to be partially ordered.
Each of the STARSdemonstration teams did a trial application of the RSM. The general conclusion
from the teams was that the RSM helped them identify management and infrastructure issues and
goals that they had not discovered in their top-down decomposition of strategic business objectives.
They believed that doing the RSMassessment was useful if it was used for nothing more than raising
issues that need to be addressed by reuse-based development pro jects. Further,at least two of the
projects intend to use the RSM to measure their state of reuse practice going into and at completion
of their demonstrations.
References
[1] R. S. S. Software Technology for Adaptable, "Stars conceptual framework for reuse pro-
cesses:definition," tech. rep., Advanced Research Projects Agency (ARPA), December 1992.
[2] R. S. S. Software Technology for Adaptable, "Stars reuse maturity model: Planning aid for
reuse-based pro jects," tech. rep., Advanced Research Projects Agency (ARPA), December 1992.
[3] S. P. Consortium, "Mount reuse." in reuse-related briefings, 1990.
[4] P. Koltun and A. Hudson, "A reuse maturity model," in Proceedings of the Fourth Annual
Workshop on Software Reuse, November 1991.
[5] T. D. etal., "Reuse adoption guidebook," tech. rep., Software Productivity Consortium (SPC),
Decemb er 1992.
3 Biography
Maggie Davis is Reuse Technology Area Lead for the Boeing STARS program, participating
in joint STARS activities and leading the Boeing-specific reuse technology development. Other
Boeing applied research projects Maggie has participated in include applying object-oriented and
knowledge-based techniques to the problem of system integration testing, using graphical user
interfaces to support timing and sizing analyses, and authoring a guidebook for the Air Force on
software specification techniques. Prior to her Boeing career, Maggie worked as ascientific and
systems programmer for a wholly-owned subsidiary of Shell Oil, Inc. that was developing thin-film,
photovoltaic energy devices and for the marketing division of E.I. Dupont, Fibers. Maggie holds a
M.S. in Computer Science from the University of Delaware.
Davis_M- 4
Figure 1: RSM Indicators by Dimension
Davis_M- 5
Figure 2: Example Indicator Table
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