Qualitative Simulation Model for Software Engineering Process
He Zhang
School of CSE, UNSW
National ICT Australia
hezhang@cse.unsw.edu.au
Ming Huo
School of CSE, UNSW
National ICT Australia
mhuo@cse.unsw.edu.au
Barbara Kitchenham
National ICT Australia
barbara.kitchenham@nicta.com.au
Ross Jeffery
School of CSE, UNSW
National ICT Australia
ross.jeffery@nicta.com.au
Abstract
Software process simulation models hold out the
promise of improving project planning and control.
However, quantitative models require a very detailed
understanding of the software process. In particular,
process knowledge needs to be represented
quantitatively which requires extensive, reliable
software project data. When such data is lacking,
quantitative models must impose severe constraints,
restricting the value of the models. In contrast
qualitative models are able to cope with imprecise
knowledge by reasoning at a more abstract level. This
paper illustrates the value and flexibility of qualitative
models by developing a model of the software staffing
process and comparing it with other quantitative
staffing models. We show that the qualitative model
provides more insights into the staffing process than
the quantitative models because it requires fewer
constraints and can thus simulate more behaviors. In
particular, the qualitative model produces three
possible outcomes: adding staff can increases project
duration (i.e. Brooks’ Law), adding staff may not affect
duration, or adding staff may decrease duration. The
qualitative model allows us to determine the conditions
under which the different outcomes can occur.
Keywords
software process modeling, staffing process,
qualitative simulation model, process simulation,
QDE, Brooks’ Law
1. Introduction
In the late 80’s, Abdel-Hamid proposed the use of
quantitative Systems Dynamic models to simulate the
dynamic aspects of a software project [1]. The
approach was intended to attain a better understanding
of project behaviours and to improve both project
planning and project control. Although this approach
has shown great promise, in practice, it is not
frequently used. The main problem with quantitative
simulation models is that they require very detailed
understanding of the processes they simulate. Such
models require reliable data for their initial
construction. Furthermore they require additional data
to tailor the general model to the specific working
practices of a particular company. When knowledge of
the software process is limited or inadequate,
quantitative simulation models impose strict
constraints on the models which results in
deterministic outcomes that neglect other possibilities.
Qualitative simulation (also known as qualitative
reasoning) is a modeling method that copes with a lack
of precise knowledge by reasoning at a more abstract
level than quantitative models. It is a powerful
technique for creating and applying system/process
models especially when the process is only partly
understood. With incomplete knowledge, a simulation
model generates qualitative descriptions of all the
possible behaviours. They are presented as a set of
possible behaviors and states consistent with a QDE
(qualitative differential equation) model of the world,
which expresses natural types of the incomplete
knowledge from real world.
Ramil and Smith developed a qualitative model
with reference to quantitative equations to extract the
qualitative trends of software evolution [2]. They
employed qualitative simulation to reason about the
second-order behaviour patterns of the evolution
process, rather than a set of particular behaviours. This
is the only example of software process modeling with
qualitative simulation.
In this paper, a qualitative simulation model of the
staffing process in software development has been
built. The simulation generates a set of the possible
behaviors which may happen when development team
size changes during the development process. We
examine the possible behaviors and compare them with
the results of previous models and empirical evidence.
Section 2 provides the description on how to build
qualitative simulation models. We describe the
qualitative abstracting structure and constraints of the
software staffing process model in section 3. In section
Proceedings of the 2006 Australian Software Engineering Conference (ASWEC’06)
1530-0803/06 $20.00 © 2006 IEEE