1,021,266 research outputs found
A Quality Model for Actionable Analytics in Rapid Software Development
Background: Accessing relevant data on the product, process, and usage
perspectives of software as well as integrating and analyzing such data is
crucial for getting reliable and timely actionable insights aimed at
continuously managing software quality in Rapid Software Development (RSD). In
this context, several software analytics tools have been developed in recent
years. However, there is a lack of explainable software analytics that software
practitioners trust. Aims: We aimed at creating a quality model (called
Q-Rapids quality model) for actionable analytics in RSD, implementing it, and
evaluating its understandability and relevance. Method: We performed workshops
at four companies in order to determine relevant metrics as well as product and
process factors. We also elicited how these metrics and factors are used and
interpreted by practitioners when making decisions in RSD. We specified the
Q-Rapids quality model by comparing and integrating the results of the four
workshops. Then we implemented the Q-Rapids tool to support the usage of the
Q-Rapids quality model as well as the gathering, integration, and analysis of
the required data. Afterwards we installed the Q-Rapids tool in the four
companies and performed semi-structured interviews with eight product owners to
evaluate the understandability and relevance of the Q-Rapids quality model.
Results: The participants of the evaluation perceived the metrics as well as
the product and process factors of the Q-Rapids quality model as
understandable. Also, they considered the Q-Rapids quality model relevant for
identifying product and process deficiencies (e.g., blocking code situations).
Conclusions: By means of heterogeneous data sources, the Q-Rapids quality model
enables detecting problems that take more time to find manually and adds
transparency among the perspectives of system, process, and usage.Comment: This is an Author's Accepted Manuscript of a paper to be published by
IEEE in the 44th Euromicro Conference on Software Engineering and Advanced
Applications (SEAA) 2018. The final authenticated version will be available
onlin
Using the ISO/IEC 9126 product quality model to classify defects : a Controlled Experiment
Background: Existing software defect classification schemes support multiple tasks, such as root cause analysis and process improvement guidance. However, existing schemes do not assist in assigning defects to a broad range of high level software goals, such as software quality characteristics like functionality, maintainability, and usability. Aim: We investigate whether a classification based on the ISO/IEC 9126 software product quality model is reliable and useful to link defects to quality aspects impacted. Method: Six different subjects, divided in two groups with respect to their expertise, classified 78 defects from an industrial web application using the ISO/IEC 9126 quality main characteristics and sub-characteristics, and a set of proposed extended guidelines. Results: The ISO/IEC 9126 model is reasonably reliable when used to classify defects, even using incomplete defect reports. Reliability and variability is better for the six high level main characteristics of the model than for the 22 sub- characteristics. Conclusions: The ISO/IEC 9126 software quality model provides a solid foundation for defect classification. We also recommend, based on the follow up qualitative analysis performed, to use more complete defect reports and tailor the quality model to the context of us
Long-Term Average Cost in Featured Transition Systems
A software product line is a family of software products that share a common
set of mandatory features and whose individual products are differentiated by
their variable (optional or alternative) features. Family-based analysis of
software product lines takes as input a single model of a complete product line
and analyzes all its products at the same time. As the number of products in a
software product line may be large, this is generally preferable to analyzing
each product on its own. Family-based analysis, however, requires that standard
algorithms be adapted to accomodate variability.
In this paper we adapt the standard algorithm for computing limit average
cost of a weighted transition system to software product lines. Limit average
is a useful and popular measure for the long-term average behavior of a quality
attribute such as performance or energy consumption, but has hitherto not been
available for family-based analysis of software product lines. Our algorithm
operates on weighted featured transition systems, at a symbolic level, and
computes limit average cost for all products in a software product line at the
same time. We have implemented the algorithm and evaluated it on several
examples
Products and prototypes: Whatâs the difference?
Prototypes are intended to demonstrate or test an idea. Commercial Off-The-Shelf products are intended for ongoing profitable sales. Their quality requirements are different: the former should be as cheap as possible whilst meeting the need for an adequate Proof-of-Concept or Demonstrator; the latter should be fit-for-purpose, cost-effective and an attractive, reliable solution to real world needs.
Selling a prototype as a product risks customer dissatisfaction, com-plaints, legal challenges and reputation damage. Often the protoÂŹtype has to be re-written to meet product quality-level expectations.
This paper reviews the quality properties required of a product ready for delivery. This follows the ISO/IEC 25010 Quality Model, then adds important missing elements that lie âbehind the scenesâ in customer support, product management, legal aspects and defensive programming. It draws on a lifetimeâs experience working on software products, products containing software and Software as a Service, providing facilities to end users
Predicting Software Suitability Using a Bayesian Belief Network
The ability to reliably predict the end quality of software under development presents a significant advantage for a development team. It provides an opportunity to address high risk components earlier in the development life cycle, when their impact is minimized. This research proposes a model that captures the evolution of the quality of a software product, and provides reliable forecasts of the end quality of the software being developed in terms of product suitability. Development team skill, software process maturity, and software problem complexity are hypothesized as driving factors of software product quality. The cause-effect relationships between these factors and the elements of software suitability are modeled using Bayesian Belief Networks, a machine learning method. This research presents a Bayesian Network for software quality, and the techniques used to quantify the factors that influence and represent software quality. The developed model is found to be effective in predicting the end product quality of small-scale software development efforts
Integration of Quality Attributes in Software Product Line Development
Different
approaches
for
building
modern
software
systems
in
complex
and
open
environments
have
been
proposed
in
the
last
few
years.
Some
efforts
try
to
apply
Software
Product
Line
(SPL)
approach
to
take
advantage
of
the
massive
reuse
for
producing
software
systems
that
share
a
common
set
of
features.
In
general
quality
assurance
is
a
crucial
activity
for
success
in
software
industry,
but
it
is
even
more
important
when
talking
about
Software
Product
Lines
since
the
intensive
reuse
of
assets
makes
the
quality
attributes
(a
measurable
physical
or
abstract
property
of
an
entity)
of
the
assets
to
be
transmitted
to
the
whole
SPL
scope.
However,
despite
the
importance
that
quality
has
in
software
product
line
development,
most
of
the
methodologies
being
applied
in
Software
Product
Line
Development
focus
only
on
managing
the
commonalities
and
variability
within
the
product
line
and
not
giving
support
to
the
non--Âż
functional
requirements
that
the
products
must
fit.
The
main
goal
of
this
master
final
work
is
to introduce
quality
attributes
in
early
stages
of
software
product
line
development
processes
by
means
of
the
definition
of
a
production
plan
that,
on
one
hand,
integrates
quality
as
an
additional
view
for
describing
the
extension
of
the
software
product
line
and,
on
the
other
hand
introduces
the
quality
attributes
as
a
decision
factor
during
product
configuration
and
when
selecting
among
design
alternatives.
Our
approach
has
been
defined
following
the
Model--Âż
Driven
Software
Development
paradigm.
Therefore
all
the
software
artifacts
defined
had
its
correspondent
metamodels
and
the
processes
defined
rely
on
automated
model
transformations.
Finally
in
order
to
illustrate
the
feasibility
of
the
approach
we
have
integrated
the
quality
view
in
an
SPL
example
in
the
context
of
safety
critical
embedded
systems
on
the
automotive
domain.GonzĂĄlez Huerta, J. (2011). Integration of Quality Attributes in Software Product Line Development. http://hdl.handle.net/10251/15835Archivo delegad
Price Indexes for PC Database Software and the Value of Code Compatibility
Changing product quality poses a challenge for the computation of price indexes, in particular in technologically advanced industries. We assess the differences between traditional and quality-corrected indexes by computing hedonic and matched-model price indexes for personal computer database software. Our database covers the price development in Germany from 1986 to 1994. Quality-adjusted software prices decline by 7.4 percent according to our hedonic index. Surprisingly, a matchedmodel index based on linking the prices of directly comparable program versions decreases even faster than the hedonic index (9.3 percent). This unusual result is apparently caused by the simultaneous selling of old and new versions of a given software product. The estimation results also confirm the importance of network effects. Code compatibility, i.e. the capability of executing programs written for the dominant database product, yields a significant price premium. The ability to read and write data in the dominant spreadsheet format (file compatibility) is also associated with higher prices, but the price differential is much smaller than in the case of code compatibility. --price indexes,hedonic methods,technical change
A framework and tool to manage Cloud Computing service quality
Cloud Computing has generated considerable interest in both companies specialized
in Information and Communication Technology and business context in general.
The Sourcing Capability Maturity Model for service (e-SCM) is a capability model for
offshore outsourcing services between clients and providers that offers appropriate strategies
to enhance Cloud Computing implementation. It intends to achieve the required
quality of service and develop an effective working relationship between clients and
providers. Moreover, quality evaluation framework is a framework to control the quality of
any product and/or process. It offers a tool support that can generate software artifacts to
manage any type of product and service efficiently and effectively. Thus, the aim of this
paper was to make this framework and tool support available to manage Cloud Computing
service quality between clients and providers by means of e-SCM.Ministerio de Ciencia e InnovaciĂłn TIN2013-46928-C3-3-RJunta de AndalucĂa TIC-578
A quality model for actionable analytics in rapid software development
Accessing relevant data on the product, process, and usage perspectives of software as well as integrating and analyzing such data is crucial for getting reliable and timely actionable insights aimed at continuously managing software quality in Rapid Software Development (RSD). In this context, several software analytics tools have been developed in recent years. However, there is a lack of explainable software analytics that software practitioners trust. Aims: We aimed at creating a quality model (called Q-Rapids quality model) for actionable analytics in RSD, implementing it, and evaluating its understandability and relevance. Method: We performed workshops at four companies in order to determine relevant metrics as well as product and process factors. We also elicited how these metrics and factors are used and interpreted by practitioners when making decisions in RSD. We specified the Q-Rapids quality model by comparing and integrating the results of the four workshops. Then we implemented the Q-Rapids tool to support the usage of the Q-Rapids quality model as well as the gathering, integration, and analysis of the required data. Afterwards we installed the Q-Rapids tool in the four companies and performed semi-structured interviews with eight product owners to evaluate the understandability and relevance of the Q-Rapids quality model. Results: The participants of the evaluation perceived the metrics as well as the product and process factors of the Q-Rapids quality model as understandable. Also, they considered the Q-Rapids quality model relevant for identifying product and process deficiencies (e.g., blocking code situations). Conclusions: By means of heterogeneous data sources, the Q-Rapids quality model enables detecting problems that take more time to find manually and adds transparency among the perspectives of system, process, and usage.Peer ReviewedPostprint (author's final draft
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