266,915 research outputs found
Innovation Initiatives in Large Software Companies: A Systematic Mapping Study
To keep the competitive advantage and adapt to changes in the market and
technology, companies need to innovate in an organised, purposeful and
systematic manner. However, due to their size and complexity, large companies
tend to focus on maintaining their business, which can potentially lower their
agility to innovate. This study aims to provide an overview of the current
research on innovation initiatives and to identify the challenges of
implementing the initiatives in the context of large software companies. The
investigation was performed using a systematic mapping approach of published
literature on corporate innovation and entrepreneurship. Then it was
complemented with interviews with four experts with rich industry experience.
Our study results suggest that, there is a lack of high quality empirical
studies on innovation initiative in the context of large software companies. A
total of 7 studies are conducted in such context, which reported 5 types of
initiatives: intrapreneurship, bootlegging, internal venture, spin-off and
crowdsourcing. Our study offers three contributions. First, this paper
represents the map of existing literature on innovation initiatives inside
large companies. The second contribution is to provide an innovation initiative
tree. The third contribution is to identify key challenges faced by each
initiative in large software companies. At the strategic and tactical levels,
there is no difference between large software companies and other companies. At
the operational level, large software companies are highly influenced by the
advancement of Internet technology. Large software companies use open
innovation paradigm as part of their innovation initiatives. We envision a
future work is to further empirically evaluate the innovation initiative tree
in large software companies, which involves more practitioners from different
companies
Crafting a Systematic Literature Review on Open-Source Platforms
This working paper unveils the crafting of a systematic literature review on
open-source platforms. The high-competitive mobile devices market, where
several players such as Apple, Google, Nokia and Microsoft run a platforms- war
with constant shifts in their technological strategies, is gaining increasing
attention from scholars. It matters, then, to review previous literature on
past platforms-wars, such as the ones from the PC and game-console industries,
and assess its implications to the current mobile devices platforms-war. The
paper starts by justifying the purpose and rationale behind this literature
review on open-source platforms. The concepts of open-source software and
computer-based platforms were then discussed both individually and in unison,
in order to clarify the core-concept of 'open-source platform' that guides this
literature review. The detailed design of the employed methodological strategy
is then presented as the central part of this paper. The paper concludes with
preliminary findings organizing previous literature on open-source platforms
for the purpose of guiding future research in this area.Comment: As presented in 10th IFIP WG 2.13 International Conference on Open
Source Systems, OSS 2014, San Jos\'e, Costa Rica, May 6-9, 201
Measuring Software Process: A Systematic Mapping Study
Context: Measurement is essential to reach predictable performance and high capability processes. It provides
support for better understanding, evaluation, management, and control of the development process
and project, as well as the resulting product. It also enables organizations to improve and predict its process’s
performance, which places organizations in better positions to make appropriate decisions. Objective:
This study aims to understand the measurement of the software development process, to identify studies,
create a classification scheme based on the identified studies, and then to map such studies into the scheme
to answer the research questions. Method: Systematic mapping is the selected research methodology for this
study. Results: A total of 462 studies are included and classified into four topics with respect to their focus
and into three groups based on the publishing date. Five abstractions and 64 attributes were identified,
25 methods/models and 17 contexts were distinguished. Conclusion: capability and performance were the
most measured process attributes, while effort and performance were the most measured project attributes.
Goal Question Metric and Capability Maturity Model Integration were the main methods and models used
in the studies, whereas agile/lean development and small/medium-size enterprise were the most frequently
identified research contexts.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-RMinisterio de Economía y Competitividad TIN2016-76956-C3-2- RMinisterio de Economía y Competitividad TIN2015-71938-RED
Automated analysis of feature models: Quo vadis?
Feature models have been used since the 90's to describe software product lines as a way of reusing common parts in a family of software systems. In 2010, a systematic literature review was published summarizing the advances and settling the basis of the area of Automated Analysis of Feature Models (AAFM). From then on, different studies have applied the AAFM in different domains. In this paper, we provide an overview of the evolution of this field since 2010 by performing a systematic mapping study considering 423 primary sources. We found six different variability facets where the AAFM is being applied that define the tendencies: product configuration and derivation; testing and evolution; reverse engineering; multi-model variability-analysis; variability modelling and variability-intensive systems. We also confirmed that there is a lack of industrial evidence in most of the cases. Finally, we present where and when the papers have been published and who are the authors and institutions that are contributing to the field. We observed that the maturity is proven by the increment in the number of journals published along the years as well as the diversity of conferences and workshops where papers are published. We also suggest some synergies with other areas such as cloud or mobile computing among others that can motivate further research in the future.Ministerio de Economía y Competitividad TIN2015-70560-RJunta de Andalucía TIC-186
Sustainability in Software Engineering
The intersection between software engineering re- search and the problems related to sustainability and green IT has been the subject of increasing attention. In spite of that, we observe that sustainability is still not clearly defined, or understood, in the field of software engineering. This lack of clarity leads to confusion about e.g. what is relevant to measure or the research implications over time or space.
This paper provides an overview of how the research so far has defined sustainability, and how this definition has been used to guide which research areas. To this end, we carried out a systematic mapping study for selecting, classifying and analyzing relevant publications. In this study, we investigate which knowledge areas and which time scope of sustainability effects are mostly targeted in scientific research. Our analysis shows research trends and discusses gaps to be filled
A literature review of expert problem solving using analogy
We consider software project cost estimation from a problem solving perspective. Taking a cognitive psychological approach, we argue that the algorithmic basis for CBR tools is not representative of human problem solving and this mismatch could account for inconsistent results. We describe the fundamentals of problem solving, focusing on experts solving ill-defined problems. This is supplemented by a systematic literature review of empirical studies of expert problem solving of non-trivial problems. We identified twelve studies. These studies suggest that analogical reasoning plays an important role in problem solving, but that CBR tools do not model this in a biologically plausible way. For example, the ability to induce structure and therefore find deeper analogies is widely seen as the hallmark of an expert. However, CBR tools fail to provide support for this type of reasoning for prediction. We conclude this mismatch between experts’ cognitive processes and software tools contributes to the erratic performance of analogy-based prediction
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