A Model for Software Contexts
Diana Kirk and Stephen G. MacDonell
SERL, School of Computing & Mathematical Sciences, Auckland University of Technology,
Private Bag 92006, Auckland 1142, New Zealand
Keywords:
Software Practices, Software Organisations, Research Model.
Abstract:
It is widely acknowledged by researchers and practitioners that software development methodologies are gen-
erally adapted to suit specific project contexts. Research into practices-as-implemented has been fragmented
and has tended to focus either on the strength of adherence to a specific methodology or on how the efficacy
of specific practices is affected by contextual factors. We submit the need for a more holistic, integrated
approach to investigating context-related best practice. We propose a six-dimensional model of the problem-
space, with dimensions organisational drivers (why), space and time (where), culture (who), product life-cycle
stage (when), product constraints (what) and engagement constraints (how). We test our model by using it to
describe and explain a reported implementation study. Our contributions are a novel approach to understanding
situated software practices and a preliminary model for software contexts.
1 INTRODUCTION
For many years, the established wisdom relating to
software development projects was that a specific
methodology must be selected and, once selected,
must be adhered to without alteration. This viewpoint
was based on the notion that “development models
are best regarded as a coherent set of practices, some
of which are required to balance the performance
trade-offs arising from the use (or absence) of others”
(Cusumano et al., 2003). As time has passed, it has
become clear that this ideal has seldom been reached
in practice (Avison and Pries-Heje, 2008; Bajec et al.,
2007; Hansson et al., 2009; MacCormack et al., 2012;
Petersen and Wohlin, 2009; de Azevedo Santos et al.,
2011; Turner et al., 2010). Research indicates that,
rather than adopt and adhere to a specific methodol-
ogy, many organisations adapt practices from several
approaches, often at the level of the individual project.
As an example, as agile approaches have become
more established, deficiencies have been exposed,
leading to either contextualisation (Hoda et al., 2010)
or to amalgamation with other paradigms, for exam-
ple, the ‘lean paradigm (Wang et al., 2012). Mac-
Cormack el al. suggest that firms must deploy dif-
ferent business processes according to business con-
text and that applying a uniform ‘best practice’ ap-
proach results in missed opportunities (MacCormack
et al., 2012). The emergence of global software de-
velopment has raised a number of issues representa-
tive of this paradigm and researchers suggest current
practices must be extended or modified (Richardson
et al., 2012; ul Haq et al., 2011). The software-as-
a-service paradigm has raised new possibilities for
evaluation of user behaviour and new kinds of ap-
proach are required as current methodologies do not
satisfy the need for these new opportunities (Stucken-
berg and Heinzl, 2010). The traditional viewpoint has
thus been superseded by one of acceptance that tai-
loring according to project-specific contexts is both
necessary and unavoidable.
The idea that practice and context are inherently
intertwined has precedence in other areas of research.
Studies in organisational and management sciences
have applied theories of technology appropriation and
task-technology fit to understand the adaptation of
technologies by individuals and groups (Fidock and
Carroll, 2006; Fuller and Dennis, 2009). ‘Practices
theory’ is based on the viewpoint that practice and
knowledge are inseparable and that “it does not make
sense to talk about either knowledge or practice with-
out the other” (Orlikowski, 2002).
An acceptance of the mutual dependence of prac-
tice and context leads us to understand that we must
change the way we think about software process.
We have, from the beginning, been presented with
many different development models and methodolo-
gies, each pre-architected with a specific environment
and/or set of objectives in mind (Avison and Pries-
Heje, 2008). Assumptions are often implicit and so
197
Kirk D. and G. MacDonell S..
A Model for Software Contexts.
DOI: 10.5220/0004456801970204
In Proceedings of the 8th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE-2013), pages 197-204
ISBN: 978-989-8565-62-4
Copyright
c
2013 SCITEPRESS (Science and Technology Publications, Lda.)
unavailable for serious reflection. This approach of
proposing generic process ‘solutions’ can no longer
be justified. In addition, the intertwining of practice
and context means that context alters as a result of
practice, and so our viewing of ‘context’ as some-
thing fixed is also no longer helpful. An inexperi-
enced developer who participates in a series of formal
design reviews is changed by the experience. Rather
than continuing to propose and justify sets of defined
practices within fixed contexts, we must follow other
disciplines and turn our focus towards understanding
more deeply the relationships between practice and
context. Many researchers have sought such under-
standing, mainly by examining practice efficacy in a
specific situation. For a comprehensive overview of
this research, see (McLeod and MacDonell, 2011).
We suggest that such investigations, although in-
teresting, have limited utility because of the large
number of possible contextual factors. Without a the-
oretical model of the problem space, our investiga-
tions must necessarily remain fragmented. In this
paper, we address this gap by first abstracting the
problem space and then aiming to understand the
relationships between practices and our abstraction.
Our model is based on observations made by Or-
likowski during a study of distributed development
(Orlikowski, 2002) (see section 2). We propose a six-
dimensional model, with dimensions organisational
drivers (why), space and time (where), culture (who),
product life-cycle stage (when), product constraints
(what) and engagement constraints(how). We test our
model by analysing a reported study into the causes of
overscoping in a large organisation, and explore pos-
sible explanations for findings.
The contributions of this paper are a novel ap-
proach to understanding situated software practices
and an abstraction of the software problem space
based on work in other disciplines. In section 2, we
overview studies aimed at problem space abstraction.
In section 3, we present our proposed model. In sec-
tion 4 we apply it to understand an implementation
study from the literature and in section 5 we discuss
findings. In section 6, we summarise the paper and
discuss limitations and future work.
2 ABSTRACTING THE PROBLEM
SPACE
In this section, we overview research aimed at cate-
gorising the problem space along various dimensions.
Avison and Pries-Heje aimed to support selec-
tion of a suitable methodology that is project-specific
(Avison and Pries-Heje, 2008). For a given project,
the authors plotted position along each of eight di-
mensions on a radar graph and inferred an appropriate
methodology from the shape of the plotted graph.
While we support the intent to understanding
project-space in this way, we see two limitations in
the work. First, the abstracted categories are based
on inputs from a single organisation and so are in-
evitably scoped to the operating space for the organ-
isation. This means that, although key ideas such as
distance, quality, and culture are included, some im-
portant contexts are missing. One example is the need
to consider the business goals of the organsation when
selecting practices (Wang et al., 2012). Lepmets et
al. suggest that processes “are part of a larger or-
ganizational system and therefore cannot be tinkered
with in isolation” (Lepmets et al., 2012). A second
limitation is that the abstraction is based at the level
of the project. In the realm of software development
this has implications of spanning requirements deter-
mination through to product delivery and we suggest
that this scope is not sufficiently broad. For exam-
ple, the most important practices recommended for
new product developmentare at ‘the leading edge’ i.e.
involve issues of strategy and product determination,
and these occur before a ‘project’ to develop the new
product is commenced. Another example involves
the ‘software-as-a-service (SaaS)’ delivery paradigm.
Here we note that the emphasis changes from a ‘de-
veloper driven’ to a customer-driven’ environment,
where the on-going relationship between develop-
ment group and customer becomes key (Stuckenberg
and Heinzl, 2010). Again, this is not part of a ‘project’
as we generally understand it.
Clarke and O’Connor propose a reference frame-
work for situational factors affecting software devel-
opment (Clarke and O’Connor, 2012). One aim is
to develop a profile of the situational characteris-
tics of a software development setting” and to use
this to support process definition and optimisation.
The framework includes eight classifications: Person-
nel, Requirements, Application, Technology, Organi-
sation, Operation, Management and Business, further
divided into 44 factors. Our critique of this approach
is that it remains ‘factors-based’. Although factors are
grouped into classifications, there is no meaning that
helps us understand relevance. For example, the fac-
tor ‘Cohesion’ represents a number of different kinds
of meaning’, including “team members who have not
worked for you”, “ability to work with uncertain ob-
jectives” and “team geographically distant”. These
three meanings can be viewed as quite different.
Kruchten presents a contextual model based on
experience for situating agile practices. The aim of
the model is to “guide the adoption and adaptation of
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agile development practices”, particulary in contexts
that are “outside of the agile sweet spot” (Kruchten,
2011). The model is interesting to those committed to
an assumption of ‘agile practices as basis but may be
adapted’. However, it is situated in the solution space
of agile projects. Wang notes that the need to align
practices with business goals is a limitation of agile
practices which “do not generally concern themselves
with the surrounding business context in which the
software development is taking place (Wang et al.,
2012). As for the Avison and Pries-Heje study above,
this model excludes some important contexts and has
narrower scope than we require.
Orlikowski carried out an exploration of a
globally-dispersed, multinational product develop-
ment organisation, and observed a number of bound-
aries that served to shape and challenge the distributed
product development (Orlikowski, 2002). These
boundaries are temporal (multiple time zones), ge-
ographical (multiple global locations), social (many
participants engaged in joint development work),
cultural (multiple nationalities), historical (different
product versions), technical (complex system, vari-
ous infrastructures, variety of standards) and politi-
cal (different interests, local versus global priorities).
In Orlikowski’s research, the problem space is de-
scribed. However, the work does not relate specif-
ically to software organisations and the criticism of
‘single organisation’ remains. Aspects such as busi-
ness goals and the ongoing relationship between cus-
tomer(s) and development group are not included.
Zachman created a 2-dimensional framework
for describing an enterprise architecture (Zachman,
2009). The first framework dimension comprises the
columns Why, Who, What, Where, When and How and
the second dimension contains a number of perspec-
tives on the organisation. Although the meanings of
the first dimension columns are not useful to our re-
search (for example, the meaning of What as a list or
model of artifacts does not support practice categori-
sation), we recognise the column categories as pro-
viding a potentially sound, orthogonal basis for our
investigation. Zachman’s notion of differing perspec-
tives on the organisation is not relevant for our study.
3 DIMENSIONAL MODEL OF
THE PROBLEM SPACE
The overall goal for our research is to understand the
relationships between practices and context in order
that we might advise organisations on practices that
are appropriate for their particular situation. The cur-
rent goal is to establish a model based on the soft-
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Figure 1: Model dimensions.
ware problem space that will support investigations
into situated practices.
As preliminary to creating a workable model, we
studied the literature in other disciplines, for exam-
ple, management, organisational science and product
development. The outcome is an abstraction based
on the works of Orlikowski (Orlikowski, 2002) and
Zachman (Zachman, 2009). The abstraction has six
dimensions Why, Who, What, Where, When and How,
each dimension representing a key aspect of the prob-
lem space. In Figure 1, we overview the meanings of
these aspects along with some examples.
Space and Time (Where). How stakeholders are
separated in space and time will place constraints
upon practices relating to communication and
co-ordination. The separation might affect any
team interface and so this dimension has many
possible scenarios. Some examples are remote
clients, outsourcing testing and non-colocated
teams.
Culture (Who). The world-views of stakeholders
will influence which practices are likely to be suc-
cessful. This dimension is manifested in how
people are structured to carry out work. Issues
of power, language and expectations about ‘how
things work’ will be relevant. A group within a
larger organisation may be constrained to adopt
the processes of the larger group. A management
team and development team will probably have
different world-views. A group that likes and ex-
pects change might want to experiment with new
technologies. A team of developers that works on
several projects at the same time differs culturally
from a team that is dedicated to a single project.
Product Life-cycle Stage (When). A situated prod-
uct moves through a tailored life-cycle that in-
cludes, for example, initial creation, adolescence,
maturity and retirement. It is likely that the prac-
tices that affect outcomes will be different at var-
ious points in the cycle (Kirk and MacDonell,
2009). For example, much of the new product
development (NPD) literature indicates that prac-
AModelforSoftwareContexts
199
tices such as clarification of NPD goals, iden-
tification of value proposition, cross-functional
teams and go/no-go gates are more important
than ‘in-development’ practices for successful
outcomes. Later in the cycle, when the product
is in use and there are many requests for new
functionality from different sources, change man-
agement practices become key. Still later, when
the product is nearing retirement, it is likely that
practices to keep ‘important’ customers happy
may be most important, during a transition to
a newer, more relevant product. MacCormack
et al. discuss three life-stage related contexts:
new product start-up, best approached by devel-
opment practices that support emergence; product
growth, which requiresan agile approach for man-
aging rapid product evolution; and product matu-
rity, which requires efficient processes that reduce
costs. (MacCormack et al., 2012). Furneaux and
Wade discuss product discontinuance and provide
a model to support the formation of clear dis-
continuance intentions as a prelude to decision-
making (Furneaux and Wade, 2010).
Product Constraints (What). The nature of the
software product may require consideration of
standards, product external interfaces and quality
expectations. Software for the chemical industry
may require adherence to specific process and/or
product standards. Embedded software, middle-
ware and stand-alone applications involve differ-
ent kinds of product interface and possibly differ-
ent practices relating to product integration. Soft-
ware for medical equipment may require formal
quality practices to be in place.
Engagement Constraints (How). The demographic
of the receivers of the software product may in-
fluence product specification and delivery mech-
anisms. Delivering custom software to a sin-
gle customer probably indicates practices such as
evolutionary specification, many deliveries, pro-
totyping and customer involvement. Deploying a
telephony middleware product to a vertical mar-
ket with different feature expectations may re-
quire a well-defined roadmap, product-line ap-
proach, strong customer relationships, effective
pre-delivery testing and a defined and infrequent
delivery cycle (as the receiving organisations may
need to ratify middleware within their own sys-
tems). Deploying to many probably requires
greater focus on requirements and change man-
agement. An early adopter market may expect fast
delivery with frequent updates.
Organisational Drivers (Why). The key strategic
goal of the producer organisation will affect
strategic decisions which in turn may affect any
of the above dimensions. A goal of ‘corner the
market’ may be addressed with a strategy of new
product innovation (when), fast delivery (how)
and involving customers in development (who).
A goal of ‘be a great employer’ infers a focus on
human-related practices, and may result in a deci-
sion to adopt new process methodologies as they
arise to support a strategy of ‘always working on
the leading edge of technology’ (who). A goal
of ‘go global’ may exclude practices that require
heavy involvement of end-users.
4 THE CASE STUDY
A model effectively represents a theory and is useful
only if it helps explain existing observed phenomena
or can be used to predict. In this section, we discuss
a study that describes issues with process implemen-
tation and illustrate the use of the model to support
explanations for the identified issues.
Bjarnason, Wnuk and Regnell investigate the
causes of overscoping in large, market-driven organi-
sations by carrying out semi-structured interviews in
a case company and then validating results via a ques-
tionnaire (Bjarnason et al., 2012). The case com-
pany develops embedded systems for a global mar-
ket and implements a product line approach, where
products reuse the common platform’s functionality
and qualities. Major releases typically contain 60-
80 new features, implemented as 20-25 projects with
separate requirements teams (RTs) and development
teams (DTs) containing 40-80 developers. The organ-
isation was in process of implementing a more agile
approach and the research was aimed at understand-
ing the differences between the two approaches.
The authors identify six causes of overscoping and
then carry out a root cause analysis on the identi-
fied causes. In Figure 2, we show the identified ‘root
causes’ along with the contexts that were found by the
authors to be associated with each root cause.
Inflow from Multiple Sources. The authors state
that a “large, uncontrollable inflow of require-
ments has the potential to cause overscopingwhen
not managed and balanced against the amount
of available capacity”. The context is an evolv-
ing platform, with each platform release involv-
ing “typically around 60-80 new features”. This
situation is typical of the software product life-
stage, adolescence, as there is a need to satisfy
in a timely manner many requests from disparate
sources (Kirk and MacDonell, 2009). We thus
map to the When dimension.
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
(!
Figure 2: Mapping of root causes of overscoping.
Lack of Overview of Available Resources. The
root cause was a failure of the DTs to under-
stand each other’s viewpoint around cost, caused
by “communication gaps within the software unit
and between the DTs” as each DT focussed on lo-
cal needs. It is unclear to what extent physical
separation of the DTs (Where) and a difference
in world-view between DTs (Who) affected the
lack of communication. Because the same kinds
of role are involved, we assume the key aspect is
physical separation and map to Where.
Low Development Team Involvement in Early
Stages. The authors identified two root causes.
The first is developer unavailability as developers
work on other maintenance projects. The relevant
dimension is Who. The second concerns gaps in
communication between the requirements units
and development units, leading to the developers
being unaware of the importance of the work.
As for the previous item, we do not know if this
lack of communication is caused by physical or
cultural distance. As it is likely that the different
kinds of unit have different world views, we map
this root cause to both Where and Who.
Requirements not agreed with Development Team.
A significant root cause was found to be low mu-
tual understanding resulting from communication
gaps between different kinds of role and state that
these resulted from “physical and organizational
distances”. We map to Where and Who.
Upfront detailed Requirements Specification.
Those involved in requirements specifications
reported no issues with early, detailed specifica-
tion while those downstream had the opposite
viewpoint. We map as cultural (Who).
Unclear Vision of Overall Goal. The RT leaders re-
ported that a lack of clear business strategy and
vision “resulted in proposing a project scope from
a pure technology standpoint”. We are unclear
whether the context is one of management fail-
ure to clarify business strategy (Why) or failure
to share strategy with the RTs, causing a cul-
tural disconnect (Who), and so map to both. The
authors also found weak scope coordination be-
tween functional areas resulted in a project scope
largely defined by the DTs (instead of the RTs).
We again map to both Where and Who.
From Figure 2, we observe that, from the perspec-
tive of our model, many of the causes of overscoping
in this case are associated with physical and cultural
separation of individuals with different roles. Two
root causes are associated with organisational fail-
ure to clarify business strategy and one with the life-
cycle stage of the situated product. We now examine
changes introduced with the agile implementation.
1. Requirements responsibility transferred from re-
quirements unit into business unit (BU) and soft-
ware unit (SU). BU gathers and prioritises fea-
tures and places in prioritised list. SU estimates
effort and delivery date.
2. Cross-functional development teams created for a
feature include a customer proxy (from BU) and
produce detailed requirements, implement and
test the feature. Iteratively refine requirements,
effort and time-frame estimations.
3. User stories and acceptance criteria produced.
4. Planning and resource allocation in one plan.
We analyse with the support of our model and
show findings in Figure 3.
The requirements process described in item 1
above has established responsibility for scope def-
inition. We ‘remove’ this root cause from Where
AModelforSoftwareContexts
201
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
*!
Figure 3: Profile after agile implementation.
and Who. It is likely that BUs will scope in a less
technology-biased way, and so we remove this
root cause from Who. We note that we have a new
context i.e. a structure of BU and SU. We add this
to Where and Who by underlining.
The creation of cross-functional teams has re-
moved the physical and cultural distance be-
tween requirementsengineers and developers. We
would expect that root causes addressed would in-
clude ‘developer awareness of importance’, mu-
tual understanding of requirements’ and the ‘dis-
agreement about the need for early, detailed
specs’. The latter is not necessarily the case as
including a customer proxy on the team doesn’t
guarantee agreement about specification mecha-
nisms. We remove the first two causes. However,
we note the team now includes a customer proxy
from the BU. It is likely that this new team mem-
ber has different viewpoints from existing mem-
bers. We add this in Who.
The creation of user stories and acceptance crite-
ria for a feature addresses the disagreement about
the need for early, detailed specifications. We re-
move this cause.
An overall approach to planning and resource
allocation addresses ‘developer unavailability in
early stages’ (Who) and changes the context of
parallel development. However, we are unclear
about who owns this overall plan and a possible
change in structure is involved, for example, a
planning group. As we need to understand all pos-
sible effects of the new implementation, for com-
pleteness, we add to Who.
Examining Figure 3, we observe that most identified
root causes have been addressed. However, some re-
main and some are new. The issue of technology-
biased scoping was associated with a context of
lack of management business strategy and a cultural
disconnect between management and requirements
teams. Muddy management vision pre-change will
remain muddy management vision post-change. The
issue of DTs focusing on their own concerns proba-
bly remains and it is unclear whether the introduced
changes will address all issues arising from this. The
inflow from multiple sources is unchanged and may
be addressed by the new requirements process. How-
ever, this is not certain, as there is no reason to be-
lieve that the ‘champions’ within the BUs of the var-
ious requirements sources will always agree about
scope and priority, particularly if vision is unclear.
The new change management process may not be en-
tirely effective. In addition, the move to agile has in-
troduced four cultural changes, each of which may
be a source of problems. For example, the different
world-views of business and development team mem-
bers may cause misunderstanding and conflict.
Our analysis suggests that the change to a more
agile approach will mitigate issues of over-scoping,
but does not address all root causes and introduces
some new possible issues. This analysis is consistent
with the findings of the authors, who found that “over-
scoping was still a challenge for the case company”.
Respondents reported a need for “clearer company vi-
sion” and this is also consistent with our analysis.
5 DISCUSSION
Our analysis of the Case based on our model exposed
ENASE2013-8thInternationalConferenceonEvaluationofNovelSoftwareApproachestoSoftwareEngineering
202
some post-change contexts that suggest some over-
scoping issues might remain after process change. In-
deed, we identified some new contexts in Where and
Who that might lead to new problems. We, of course,
do not know if there is consistency between our ex-
planation and remaining issues, but suggest that the
use of our model has provided a sound starting point
for further investigations.
We also note the importance of understanding
cause at a deeper level than is perhaps accepted. For
example, identifying a problem of ‘poor communica-
tion’ is only a first step. The deeper cause, for ex-
ample, physical or cultural separation must be under-
stood prior to improvement initiatives, if these initia-
tives are to be effective. Use of the proposed model
provides a mechanism for such understanding. For
example, in the Case, the issue of technology-biased
scoping may have been an issue of lack of manage-
ment strategy or may have been an issue of organ-
isation structure (cultural). We cannot assume the
problem will go away when we form cross-functional
teams. From Figure 3, we saw that a) if the is-
sue was associated with management strategy, cross-
functional teams made no difference and b) if organi-
sation structure, the introduction of cross-functional
teams introduces a new structure which may itself
cause new issues to emerge.
One important aspect of having a model from
which to analyse is the ability to predict what may be
unsuccessful in a process improvement initiative. For
example, Hoda et al. report on the adaptation of agile
practices in a study involving 40 practitioners from 16
software development organisations in New Zealand
(Hoda et al., 2010). One problem identified con-
cerned the need for detailed documentation to com-
ply with certification requirements. Some developers
perceived documentation as being anti-agile, causing
problems of internal team clashes. Had an extensive
analysis of context been carried out in advance, the
conflict between an absolute requirement for docu-
mentation (What) and the evangelism of some team
members (Who) may have been exposed in advance
and mitigation steps taken.
Our approach of establishing a model of the prob-
lem space enables us to now ask focussed research
questions with a view to building up a body of knowl-
edge concerning suitable practices in a given con-
text. For example, if our question is “What prac-
tices are suitable for ensuring correct functionality
during design?”, we must further focus the question
with respect to our dimensional model, by consider-
ing business objectives, physical separation of stake-
holders, cultural considerations, product life-cycle
stage, product-related constraints and engagement-
related constraints.
6 SUMMARY, LIMITATIONS
AND FUTURE WORK
We have postulated the need for a holistic, integrated
approach to investigating context-related best practice
and have proposed an approach based on problem-
space contexts. The model has six dimensions: organ-
isational drivers (why), space and time (where), cul-
ture (who), product life-cycle stage (when), product
constraints (what) and engagement constraints (how).
We have tested our model by using it to analyse a re-
ported implementation study and have suggested ex-
planations for findings. Our contributions are a novel
approach along with a model for understanding situ-
ated software practices.
The major limitation for this research is that both
model creation and validation have been carried out
by the same people with resulting concerns of sub-
jectivity in interpretation of the validation study. As
mitigation, we have aimed to describe our reasoning
as fully as possible given space constraints.
Our vision is for a model that is a minimum span-
ning set’ for the problem space i.e. dimensions are
non-overlapping and cover the space. We will next
map known factors onto our model to test for this.
Other future efforts will include further exploration
of the effectiveness of our model and studies into how
the ‘context blueprint’ changes as specific practices
are implemented.
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