252 research outputs found
Towards an I/O Conformance Testing Theory for Software Product Lines based on Modal Interface Automata
We present an adaptation of input/output conformance (ioco) testing
principles to families of similar implementation variants as appearing in
product line engineering. Our proposed product line testing theory relies on
Modal Interface Automata (MIA) as behavioral specification formalism. MIA
enrich I/O-labeled transition systems with may/must modalities to distinguish
mandatory from optional behavior, thus providing a semantic notion of intrinsic
behavioral variability. In particular, MIA constitute a restricted, yet fully
expressive subclass of I/O-labeled modal transition systems, guaranteeing
desirable refinement and compositionality properties. The resulting modal-ioco
relation defined on MIA is preserved under MIA refinement, which serves as
variant derivation mechanism in our product line testing theory. As a result,
modal-ioco is proven correct in the sense that it coincides with traditional
ioco to hold for every derivable implementation variant. Based on this result,
a family-based product line conformance testing framework can be established.Comment: In Proceedings FMSPLE 2015, arXiv:1504.0301
Ecological Life Cycle Assessment Modified Novolaks Waste Used in Industrial Wastewater Treatment
Ecological Life Cycle Assessment (LCA) applied in the assessment of the impact
of products on the environment is a technique that allows for the evaluation of the
environmental impact of polymeric flocculants used in industrial wastewater treatment.
The possibility of conducting a full life cycle and thus manufacturing process analysis
allows for reliable and accurate identification of the sources of environmental hazards
and the impact of new products on the environment. Newly synthesized waste-based
polymers are water soluble and possess the properties of flocculants, while reducing the
parameters in industrial wastewater. In the paper, there are presented the results of the
analysis conducted using LCA technique for the assessment of the impact of modified
waste phenol formaldehyde resin (Novolak) on the environment. LCA technique was
used to assess the impact of the new flocculant applied in the process of metallurgical
wastewater treatment taking into account the environmental impact of the fl occulant
manufacturing process
Analysis of Software Binaries for Reengineering-Driven Product Line Architecture\^aAn Industrial Case Study
This paper describes a method for the recovering of software architectures
from a set of similar (but unrelated) software products in binary form. One
intention is to drive refactoring into software product lines and combine
architecture recovery with run time binary analysis and existing clustering
methods. Using our runtime binary analysis, we create graphs that capture the
dependencies between different software parts. These are clustered into smaller
component graphs, that group software parts with high interactions into larger
entities. The component graphs serve as a basis for further software product
line work. In this paper, we concentrate on the analysis part of the method and
the graph clustering. We apply the graph clustering method to a real
application in the context of automation / robot configuration software tools.Comment: In Proceedings FMSPLE 2015, arXiv:1504.0301
A Systematic Review of Tracing Solutions in Software Product Lines
Software Product Lines are large-scale, multi-unit systems that enable
massive, customized production. They consist of a base of reusable artifacts
and points of variation that provide the system with flexibility, allowing
generating customized products. However, maintaining a system with such
complexity and flexibility could be error prone and time consuming. Indeed, any
modification (addition, deletion or update) at the level of a product or an
artifact would impact other elements. It would therefore be interesting to
adopt an efficient and organized traceability solution to maintain the Software
Product Line. Still, traceability is not systematically implemented. It is
usually set up for specific constraints (e.g. certification requirements), but
abandoned in other situations. In order to draw a picture of the actual
conditions of traceability solutions in Software Product Lines context, we
decided to address a literature review. This review as well as its findings is
detailed in the present article.Comment: 22 pages, 9 figures, 7 table
Quantitative Analysis of Probabilistic Models of Software Product Lines with Statistical Model Checking
We investigate the suitability of statistical model checking techniques for
analysing quantitative properties of software product line models with
probabilistic aspects. For this purpose, we enrich the feature-oriented
language FLan with action rates, which specify the likelihood of exhibiting
particular behaviour or of installing features at a specific moment or in a
specific order. The enriched language (called PFLan) allows us to specify
models of software product lines with probabilistic configurations and
behaviour, e.g. by considering a PFLan semantics based on discrete-time Markov
chains. The Maude implementation of PFLan is combined with the distributed
statistical model checker MultiVeStA to perform quantitative analyses of a
simple product line case study. The presented analyses include the likelihood
of certain behaviour of interest (e.g. product malfunctioning) and the expected
average cost of products.Comment: In Proceedings FMSPLE 2015, arXiv:1504.0301
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
Feature-Aware Verification
A software product line is a set of software products that are distinguished
in terms of features (i.e., end-user--visible units of behavior). Feature
interactions ---situations in which the combination of features leads to
emergent and possibly critical behavior--- are a major source of failures in
software product lines. We explore how feature-aware verification can improve
the automatic detection of feature interactions in software product lines.
Feature-aware verification uses product-line verification techniques and
supports the specification of feature properties along with the features in
separate and composable units. It integrates the technique of variability
encoding to verify a product line without generating and checking a possibly
exponential number of feature combinations. We developed the tool suite
SPLverifier for feature-aware verification, which is based on standard
model-checking technology. We applied it to an e-mail system that incorporates
domain knowledge of AT&T. We found that feature interactions can be detected
automatically based on specifications that have only feature-local knowledge,
and that variability encoding significantly improves the verification
performance when proving the absence of interactions.Comment: 12 pages, 9 figures, 1 tabl
From Professional Business Partner to Strategic Talent Leader : What’s Next for Human Resource Management
The HR profession is at a critical inflection point. It can evolve into a true decision science of talent, and aspire to the level of influence of disciplines such as Finance and Marketing, or it can continue the traditional focus on support services and program delivery to organizational clients. In this paper, we suggest that the transition to a decision science is essential and not only feasible, but historically predictable. However, we show that making the transition is not a function of achieving best-practice professional practices. Rather, it requires developing a logical, deep and coherent framework linking organizational talent to strategic success. We show how the evolution of the decision sciences of Finance and Marketing, out of the professional practices of Accounting and Sales, provide the principles to guide the evolution from the current professional practice of HR, to the emerging decision science of talentship
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