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Software startups
(2016)
Software startup companies develop innovative, software-intensive products within limited time frames and with few resources, searching for sustainable and scalable business models. Software startups are quite distinct from traditional mature software companies, but also from micro-, small-, and medium-sized enterprises, introducing new challenges relevant for software engineering research. This paper’s research agenda focuses on software engineering in startups, identifying, in particular, 70+ research questions in the areas of supporting startup engineering activities, startup evolution models and patterns, ecosystems and innovation hubs, human aspects in software startups, applying startup concepts in non-startup environments, and methodologies and theories for startup research. We connect and motivate this research agenda with past studies in software startup research, while pointing out possible future directions. While all authors of this research agenda have their main background in Software Engineering or Computer Science, their interest in software startups broadens the perspective to the challenges, but also to the opportunities that emerge from multi-disciplinary research. Our audience is therefore primarily software engineering researchers, even though we aim at stimulating collaborations and research that crosses disciplinary boundaries. We believe that with this research agenda we cover a wide spectrum of the software startup industry current needs.
This paper builds upon the widely-used resource-based approach to explaining survival of new technology-based firms (NTBFs). However, instead of looking at the NTBF's initial resource configuration, a process-oriented perspective is taken by focusing on the entrepreneur's ability to transform resources in response to triggers resulting from market interactions. Transaction relations reflect these interactions and are thus operationalized with a suggested method for measuring the status of venture emergence (VE) applicable to early-stage NTBFs. NTBFs' value network maturity is reflected in the number and strength of their transaction relations in the four market dimensions customer, investor, partner, and human resource. Business plans of NTBFs represent the artifact that contains this data in the form of transaction relation descriptions. Using content analysis, a multi-step combined human and computer coding process has been developed to annotate and classify transaction relations from business plans in order to empirically determine NTBFs' status of VE. Results of the business plan analysis suggest that the level of transaction relations allows to draw conclusions on the VE status. Moreover, applying the developed process, first analysis of a business plan coding test shows that the transaction relation based VE status significantly relates to NTBF survival capability.
Purpose The purpose of this paper is to find out tourism movement patterns via the tracking of tourists with the help of positioning systems like GPS in the rural area of the Lake Constance destination in Germany. In doing so past, present and future of tourist tracking is illustrated. Design/methodology/approach The tracking is realized via common smartphones extended by an app, with dedicated sensors like position loggers and a survey. The three different approaches are applied in order to compare and cross-check results (triangulation of data and methods). Findings Movement patterns turned out to be diverse and individualistic within the rural destination of Lake Constance and following an ants trail in sub-destinations like the city of Constance. Repeat visitors and first-time visitors alike always visit the bigger cities and main day-trip destinations of the Lake. A possible prediction tool enables new avenues of governing tourism movement patterns. Research limitations/implications The tracking techniques can be developed further into the direction of “quantified self” using gamification in order to make the tracking app even more attractive. Practical implications An algorithm-based prediction tool would offer new perspectives to the management of tourism movements. Social implications Further research is needed to overcome the feeling of invasiveness of the app to allow tracking with that approach. Originality/value This study is original and innovative because of the first-time use of a smartphone app in tourist tracking, the application on a rural destination and the conceptual description of a prediction tool.
This paper proposes a soft input decoding algorithm and a decoder architecture for generalized concatenated (GC) codes. The GC codes are constructed from inner nested binary Bose-Chaudhuri-Hocquenghem (BCH) codes and outer Reed-Solomon codes. In order to enable soft input decoding for the inner BCH block codes, a sequential stack decoding algorithm is used. Ordinary stack decoding of binary block codes requires the complete trellis of the code. In this paper, a representation of the block codes based on the trellises of supercodes is proposed in order to reduce the memory requirements for the representation of the BCH codes. This enables an efficient hardware implementation. The results for the decoding performance of the overall GC code are presented. Furthermore, a hardware architecture of the GC decoder is proposed. The proposed decoder is well suited for applications that require very low residual error rates.
So is About Urbanity
(2016)
Südstadt Tübingen is a successful military land redevelopment project, in which functional mix and urban diversity have been identified as main goals. In the whole development process, joint building venture has been utilized as important urban development instrument. On one hand, this instrument helps citizens development adaptive and affordable living space and let them find own identity to the new quarter; on the other hand, it is also important to cultivate urban diversity and suitable spatial feeling, mix relationship in living and working conditions, so that the quarters will have very flexible structure to accommodate diversified urban life styles.
To learn from the past, we analyse 1,088 "computer as a target" judgements for evidential reasoning by extracting four case elements: decision, intent, fact, and evidence. Analysing the decision element is essential for studying the scale of sentence severity for cross-jurisdictional comparisons. Examining the intent element can facilitate future risk assessment. Analysing the fact element can enhance an organization's capability of analysing criminal activities for future offender profiling. Examining the evidence used against a defendant from previous judgements can facilitate the preparation of evidence for upcoming legal disclosure. Follow the concepts of argumentation diagrams, we develop an automatic judgement summarizing system to enhance the accessibility of judgements and avoid repeating past mistakes. Inspired by the feasibility of extracting legal knowledge for argument construction and employing grounds of inadmissibility for probability assessment, we conduct evidential reasoning of kernel traces for forensic readiness. We integrate the narrative methods from attack graphs/languages for preventing confirmation bias, the argumentative methods from argumentation diagrams for constructing legal arguments, and the probabilistic methods from Bayesian networks for comparing hypotheses.
ERP systems integrate a major part of all business processes and organizations include them in their IT service management. Besides these formal systems, there are additional systems that are rather stand-alone and not included in the IT management tasks. These so-called ‘shadow systems’ also support business processes but hinder a high enterprise integration. Shadow systems appear during their explicit detection or during software maintenance projects such as enhancements or release changes of enterprise systems. Organizations then have to decide if and to what extent they integrate the identified shadow systems into their ERP systems. For this decision, organizations have to compare the capabilities of each identified shadow system with their ERP systems. Based on multiple-case studies, we provide a dependency approach to enable their comparison. We derive categories for different stages of the dependency and base insights into integration possibilities on these stages. Our results show that 64% of the shadow systems in our case studies are related to ERP systems. This means that they share parts or all of their data and/or functionality with the ERP system. Our research contributes to the field of integration as well as to the discussion about shadow systems.
Even though immutability is a desirable property, especially in a multi-threaded environment, implementing immutable Java classes is surprisingly hard because of a lack of language support. We present a static analysis tool using abstract bytecode interpretation that checks Java classes for compliance with a set of rules that together constitute state-based immutability. Being realized as a Find Bugs plug in, the tool can easily be integrated into most IDEs and hence the software development process. Our evaluation on a large, real world codebase shows that the average run-time effort for a single class is in the range of a few milliseconds, with only a very few statistical spikes.
The corrosion resistance of stainless steels is massively influenced by the condition of their surface. The surface quality includes the topography of the surface, the structure and composition of the passive layer, and the surface near structure of the base material. These factors are influenced by final physical/chemical surface treatments. The presented work shows significantly lower corrosion resistance for mechanical machined specimens than for etched specimens. It also turns out that the rougher the surface, the lower the corrosion resistance gets. However, there is no general finding which shows if blasted or grinded surfaces are more appropriate, but a dependency on process parameters and the characteristics on corrosive exposure in terms of corrosion behavior. The results show that not only the surface roughness Ra has an influence on corrosion behavior but also the shape of peaks and valleys which are evolved by surface treatments. Imperfections in the base material, like sulfidic inclusions lead to a weaker passive layer, respectively, to a decrease of the corrosion resistance. By using special passivating techniques the corrosion resistance of stainless steels can be increased to a higher level in comparison to common passivation.