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We study Gaifman locality and Hanf locality of an extension of first-order logic with modulo p counting quantifiers (FO+MODp , for short) with arbitrary numerical predicates. We require that the validity of formulas is independent of the particular interpretation of the numerical predicates and refer to such formulas as arb-invariant formulas. This paper gives a detailed picture of locality and non-locality properties of arb-invariant FO+MODp . For example, on the class of all finite structures, for any p 2, arb-invariant FO+MODp is neither Hanf nor Gaifman local with respect to a sublinear locality radius. However, in case that p is an odd prime power, it is weakly Gaifman local with a polylogarithmic locality radius. And when restricting attention to the class of string structures, for odd prime powers p, arb-invariant FO+MODp is both Hanf and Gaifman local with a polylogarithmic locality radius. Our negative results build on examples of order-invariant FO+MODp formulas presented in Niemist ̈o’s PhD thesis. Our positive results make use of the close connection between FO+MODp and Boolean circuits built from NOT-gates and AND-, OR-, and MOD p - gates of arbitrary fan-in.
We consider the isolated spelling error correction problem as a specific subproblem of the more general string-to-string translation problem. In this context, we investigate four general string-to-string transformation models that have been suggested in recent years and apply them within the spelling error correction paradigm. In particular, we investigate how a simple ‘k-best decoding plus dictionary lookup’ strategy performs in this context and find that such an approach can significantly outdo baselines such as edit distance, weighted edit distance, and the noisy channel Brill and Moore model to spelling error correction. We also consider elementary combination techniques for our models such as language model weighted majority voting and center string combination. Finally, we consider real-world OCR post-correction for a dataset sampled from medieval Latin texts.
Research in the field of Digital Humanities, also known as Humanities Computing, has seen a steady increase over the past years. Situated at the intersection of computing science and the humanities, present efforts focus on making resources such as texts, images, musical pieces and other semiotic artifacts digitally available, searchable and analysable. To this end, computational tools enabling textual search, visual analytics, data mining, statistics and natural language processing are harnessed to support the humanities researcher. The processing of large data sets with appropriate software opens up novel and fruitful approaches to questions in the traditional humanities. This report summarizes the Dagstuhl seminar 14301 on “Computational Humanities - bridging the gap between Computer Science and Digital Humanities”.
1998 ACM Subject Classification I.2.7 Natural Language Processing, J.5 Arts and Humanities
In order to promote the accessibility of biodiversity data in historic and contemporary literature, we introduce a new interdisciplinary project called BIOfid (FID=Fachinformationsdienst, a service for providing specialized information). The project aims at a mobilization of data available in print only by combining digitization of scientific biodiversity literature with the development of innovative text mining tools for complex, eventually semantic searches throughout the complete text corpus. A major prerequisite for the development of such search tools is the provision of sophisticated anatomy ontologies on the one hand, and of complete lists of species names (currently considered valid as well as all synonyms) at a global scale on the other hand. In the initial stage, we chose examples from German publications of the past 250 years dealing with the geographic distribution and ecology of vascular plants (Tracheophyta), birds (Aves), as well as moths and butterflies (Lepidoptera) in Germany. These taxa have been prioritized according to current demands of German research groups (about 50 sites) aiming at analyses and modeling of distribution patterns and their changes through time. In the long term, we aim at providing data and open source software applicable for any taxon and geographic region. For this purpose, a platform for open access journals for long-term availability of professional e-journals will be established. All generated data will also be made accessible through GFBio (German Federation for Biological Data). BIOfid is supported by the LIS-Scientific Library Services and Information Systems program of the German Research Foundation (DFG).
We present results on transverse momentum (pT) and rapidity (y) differential production cross sections, mean transverse momentum and mean transverse momentum square of inclusive J/ψ and ψ(2S) at forward rapidity (2.5 < y < 4) as well as ψ(2S)-to-J/ψ cross section ratios. These quantities are measured in pp collisions at center of mass energies s√=5.02 and 13 TeV with the ALICE detector. Both charmonium states are reconstructed in the dimuon decay channel, using the muon spectrometer. A comprehensive comparison to inclusive charmonium cross sections measured at s√=2.76, 7 and 8 TeV is performed. A comparison to non-relativistic quantum chromodynamics and fixed-order next-to-leading logarithm calculations, which describe prompt and non-prompt charmonium production respectively, is also presented. A good description of the data is obtained over the full pT range, provided that both contributions are summed. In particular, it is found that for pT > 15 GeV/c the non-prompt contribution reaches up to 50% of the total charmonium yield.
We explore space improvements in LRP, a polymorphically typed call-by-need functional core language. A relaxed space measure is chosen for the maximal size usage during an evaluation. It Abstracts from the details of the implementation via abstract machines, but it takes garbage collection into account and thus can be seen as a realistic approximation of space usage. The results are: a context lemma for space improving translations and for space equivalences; all but one reduction rule of the calculus are shown to be space improvements, and the exceptional one, the copy-rule, is shown to increase space only moderately.
Several further program transformations are shown to be space improvements or space equivalences, in particular the translation into machine expressions is a space equivalence. These results are a step Forward in making predictions about the change in runtime space behavior of optimizing transformations in callbyneed functional languages.
Motivated by tools for automaed deduction on functional programming languages and programs, we propose a formalism to symbolically represent $\alpha$-renamings for meta-expressions. The formalism is an extension of usual higher-order meta-syntax which allows to $\alpha$-rename all valid ground instances of a meta-expression to fulfill the distinct variable convention. The renaming mechanism may be helpful for several reasoning tasks in deduction systems. We present our approach for a meta-language which uses higher-order abstract syntax and a meta-notation for recursive let-bindings, contexts, and environments. It is used in the LRSX Tool -- a tool to reason on the correctness of program transformations in higher-order program calculi with respect to their operational semantics. Besides introducing a formalism to represent symbolic $\alpha$-renamings, we present and analyze algorithms for simplification of $\alpha$-renamings, matching, rewriting, and checking $\alpha$-equivalence of symbolically $\alpha$-renamed meta-expressions.
We introduce rewriting of meta-expressions which stem from a meta-language that uses higher-order abstract syntax augmented by meta-notation for recursive let, contexts, sets of bindings, and chain variables. Additionally, three kinds of constraints can be added to meta-expressions to express usual constraints on evaluation rules and program transformations. Rewriting of meta-expressions is required for automated reasoning on programs and their properties. A concrete application is a procedure to automatically prove correctness of program transformations in higher-order program calculi which may permit recursive let-bindings as they occur in functional programming languages. Rewriting on meta-expressions can be performed by solving the so-called letrec matching problem which we introduce. We provide a matching algorithm to solve it. We show that the letrec matching problem is NP-complete, that our matching algorithm is sound and complete, and that it runs in non-deterministic polynomial time.
This is a short summary of a recent survey [FR03] focusing on the observed evidence, that Internet connectivity is positively correlated with spread of democracy at high levels of significance. The results of multivariate correlation analysis and probabilities regression estimate models are based on the combined analysis of mid - 1991’s, to 2001 data series of the Eurostat’s and US Census Bureau, the World Bank, and OECD’s statistical data service which track the growth of information technology and rating of freedom and democracy worldwide.
We present an implementation of an interpreter LRPi for the call-by-need calculus LRP, based on a variant of Sestoft's abstract machine Mark 1, extended with an eager garbage collector. It is used as a tool for exact space usage analyses as a support for our investigations into space improvements of call-by-need calculi.
50 years of amino acid hydrophobicity scales : revisiting the capacity for peptide classification
(2016)
Background: Physicochemical properties are frequently analyzed to characterize protein-sequences of known and unknown function. Especially the hydrophobicity of amino acids is often used for structural prediction or for the detection of membrane associated or embedded β-sheets and α-helices. For this purpose many scales classifying amino acids according to their physicochemical properties have been defined over the past decades. In parallel, several hydrophobicity parameters have been defined for calculation of peptide properties. We analyzed the performance of separating sequence pools using 98 hydrophobicity scales and five different hydrophobicity parameters, namely the overall hydrophobicity, the hydrophobic moment for detection of the α-helical and β-sheet membrane segments, the alternating hydrophobicity and the exact ß-strand score.
Results: Most of the scales are capable of discriminating between transmembrane α-helices and transmembrane β-sheets, but assignment of peptides to pools of soluble peptides of different secondary structures is not achieved at the same quality. The separation capacity as measure of the discrimination between different structural elements is best by using the five different hydrophobicity parameters, but addition of the alternating hydrophobicity does not provide a large benefit. An in silico evolutionary approach shows that scales have limitation in separation capacity with a maximal threshold of 0.6 in general. We observed that scales derived from the evolutionary approach performed best in separating the different peptide pools when values for arginine and tyrosine were largely distinct from the value of glutamate. Finally, the separation of secondary structure pools via hydrophobicity can be supported by specific detectable patterns of four amino acids.
Conclusion: It could be assumed that the quality of separation capacity of a certain scale depends on the spacing of the hydrophobicity value of certain amino acids. Irrespective of the wealth of hydrophobicity scales a scale separating all different kinds of secondary structures or between soluble and transmembrane peptides does not exist reflecting that properties other than hydrophobicity affect secondary structure formation as well. Nevertheless, application of hydrophobicity scales allows distinguishing between peptides with transmembrane α-helices and β-sheets. Furthermore, the overall separation capacity score of 0.6 using different hydrophobicity parameters could be assisted by pattern search on the protein sequence level for specific peptides with a length of four amino acids.
Magnetoencephalography (MEG) measures neural activity non-invasively and at an excellent temporal resolution. Since its invention (Cohen, 1968, 1972), MEG has proven a most valuable tool in neurocognitive (Salmelin et al., 1994) and clinical research (Stufflebeam et al., 2009; Van ’t Ent et al., 2003). MEG is able to measure rapid changes in electrophysiological neural signals related to sensory and cognitive processes. The magnetic fields measured outside the head by MEG directly reflect the cortical currents generated by the synchronised activity of thousands of neuronal sources. This distinguishes MEG from functional magnetic resonance imaging (fMRI), where measurements are only indirectly related to electrophysiological activity through neurovascular coupling...
Die zunehmende Verbreitung des Internets als universelles Netzwerk zum Transport von Daten aller Art hat in den letzten zwei Dekaden dazu geführt, dass die anfallenden Datenmengen von traditionellen Datenbanksystemen kaum mehr effektiv zu verarbeiten sind. Das liegt zum einen darin, dass ein immer größerer Teil der Erdbevölkerung Zugang zum Internet hat, zum Beispiel via
Internet-fähigen Smartphones, und dessen Dienste nutzen möchte. Zudem tragen immer höhere verfügbare Bandbreiten für den Internetzugang dazu bei, dass die weltweit erzeugten Informationen mittlerweile exponentiell steigen.
Das führte zur Entwicklung und Implementierung von Technologien, um diese immensen Datenmengen wirksam verarbeiten zu können. Diese Technologien können unter dem Sammelbegriff "Big Data" zusammengefasst werden und beschreiben dabei Verfahren, um strukturierte und unstrukturierte Informationen im Tera- und Exabyte-Bereich sogar in Echtzeit verarbeiten zu können. Als Basis dienen dabei Datenbanksysteme, da sie ein bewährtes und praktisches Mittel sind, um Informationen zu strukturieren, zu organisieren, zu manipulieren und effektiv abrufen zu können. Wie bereits erwähnt, hat sich herausgestellt, dass traditionelle Datenbanksysteme, die auf dem relationalen Datenmodell basieren, nun mit Datenmengen konfrontiert sind, mit denen sie nicht sehr gut hinsichtlich der Performance und dem Energieverbrauch skalieren. Dieser Umstand führte zu der Entwicklung von spezialisierten Datenbanksystemen, die andere Daten- und Speichermodelle implementieren und für diese eine deutlich höhere Performance bieten.
Zusätzlich erfordern Datenbanksysteme im Umfeld von "Big Data" wesentlich größere Investitionen in die Anzahl von Servern, was dazu geführt hat, dass immer mehr große und sehr große Datenverarbeitungszentren entstanden sind. In der Zwischenzeit sind die Aufwendungen für Energie zum Betrieb und Kühlen dieser Zentren ein signifikanter Kostenfaktor geworden. Dementsprechend sind bereits Anstrengungen unternommen worden, das Themenfeld Energieeffizienz (die Relation zwischen Performance und Energieverbrauch) von Datenbanksystemen eingehender zu untersuchen.
Mittlerweile sind über 150 Datenbanksysteme bekannt, die ihre eigenen Stärken und Schwächen in Bezug auf Performance, Energieverbrauch und schlussendlich Energieeffizienz haben. Die Endanwender von Datenbanksystemen sehen sich nun in der schwierigen Situation, für einen gegebenen Anwendungsfall das geeigneteste Datenbanksystem in Hinblick auf die genannten Faktoren zu ermitteln. Der Grund dafür ist, dass kaum objektive und unabhängige Vergleichszahlen zur Entscheidungsfindung existieren und dass die Ermittlung von Vergleichszahlen zumeist über die Ausführung von Benchmarks auf verschiedensten technischen Plattformen geschieht. Es ist offensichtlich, dass die mehrfache Ausführung eines Benchmarks mit unterschiedlichsten Parametern (unter anderem die Datenmenge, andere Kombinationen aus technischen Komponenten, Betriebssystem) große Investitionen in Zeit und Technik erfordern, um möglichst breit gefächerte Vergleichszahlen zu erhalten.
Eine Möglichkeit ist es, die Ausführung eines Benchmarks zu simulieren anstatt ihn real zu absolvieren, um die Investitionen in Technik und vor allem Zeit zu minimieren. Diese Simulationen haben auch den Vorteil, dass zum Beispiel die Entwickler von Datenbanksystemen die Auswirkungen auf Performance und Energieeffizienz bei der Änderungen an der Architektur simulieren können anstatt sie durch langwierige Regressionstests evaluieren zu müssen. Damit solche Simulationen eine praktische Relevanz erlangen können, muss natürlich die Differenz zwischen den simulierten und den real gewonnenen Vergleichsmetriken möglichst klein sein. Zudem muss eine geeignete Simulation eine möglichst große Anzahl an Datenbanksystemen und technischen Komponenten nachstellen können.
Die vorliegende Dissertation zeigt, dass eine solche Simulation realistisch ist. Dafür wurde in einem ersten Schritt die Einflussaktoren auf Performance, Energieverbrauch und Energieeffizienz eines Datenbanksystems ermittelt und deren Wirkung anhand von experimentellen Ergebnissen bestimmt. Zusätzlich wurden auch geeignete Metriken und generelle Eigenschaften von Datenbanksystemen und von Benchmarks evaluiert. In einem zweiten Schritt wurde dann ein geeignetes Simulationsmodell erarbeitet und sukzessiv weiterentwickelt. Bei jedem Entwicklungsschritt wurden dann reale Experimente in Form von Benchmarkausführungen für verschiedenste Datenbanksysteme und technische Plattformen durchgeführt. Diese Experimente wurden mittels des Simulationsmodells nachvollzogen, um die Differenz zwischen realen und simulierten Benchmarkergebnissen zu berechnen. Die Ergebnisse des letzten Entwicklungsschrittes zeigen, dass diese Differenz unter acht Prozent liegt. Die vorliegende Dissertation zeigt auch, dass das Simulationsmodell nicht nur dazu geeignet ist, anerkannte Benchmarks zu simulieren, sondern sich im allgemeinen auch dafür eignet, ein Datenbanksystem und die technische Plattform, auf der es ausgeführt wird, generell zu simulieren. Das ermöglicht auch die Simulation anderer Anwendungsfälle, zum Beispiel Regressionstests.
The amyloid precursor protein (APP) was discovered in the 1980s as the precursor protein of the amyloid A4 peptide. The amyloid A4 peptide, also known as A-beta (Aβ), is the main constituent of senile plaques implicated in Alzheimer’s disease (AD). In association with the amyloid deposits, increasing impairments in learning and memory as well as the degeneration of neurons especially in the hippocampus formation are hallmarks of the pathogenesis of AD. Within the last decades much effort has been expended into understanding the pathogenesis of AD. However, little is known about the physiological role of APP within the central nervous system (CNS). Allocating APP to the proteome of the highly dynamic presynaptic active zone (PAZ) identified APP as a novel player within this neuronal communication and signaling network. The analysis of the hippocampal PAZ proteome derived from APP-mutant mice demonstrates that APP is tightly embedded in the underlying protein network. Strikingly, APP deletion accounts for major dysregulation within the PAZ proteome network. Ca2+-homeostasis, neurotransmitter release and mitochondrial function are affected and resemble the outcome during the pathogenesis of AD. The observed changes in protein abundance that occur in the absence of APP as well as in AD suggest that APP is a structural and functional regulator within the hippocampal PAZ proteome. Within this review article, we intend to introduce APP as an important player within the hippocampal PAZ proteome and to outline the impact of APP deletion on individual PAZ proteome subcommunities.
Software evolves. Developers and programmers manifest the needs that arise due to evolving software by making changes to the source code. While developers make such changes, reusing old code and rewriting existing code are inevitable. There are many challenges that a developer faces when manually reusing old code or rewriting existing code. Software tools and program transformation systems aid such reuse or rewriting of program source code. But there are significantly occuring development tasks that are hard to accomplish manually, where the current state-of-the-art tools are still not able to adequately automate these tasks. In this thesis, we discuss some of these unexplored challenges that a developer faces while reusing and rewriting program source code, the significance of such challenges, the existing automation support for these challenges and how we can improve upon them.
Modern software development relies on code reuse, which software developers
typically realize through hand-written abstractions, such as functions,
methods, or classes. However, such abstractions can be challenging to
develop and maintain. An alternative form of reuse is \emph{copy-paste-modify}, in which developers explicitly duplicate source code to adapt the duplicate for a new purpose. Copy-pasted code results in code clones, i.e., groups of code fragments that are similar to each other. Past research strongly suggests that copy-paste-modify is a popular technique among software developers. In this paper, we perform a small user study that shows that copy-paste-modify can be substantially faster to use than manual abstraction.
One might propose that software developers should forego hand-written abstractions in favour of copying and pasting. However, empirical evidence also shows that copy-paste-modify complicates software maintenance and increases the frequency of bugs. Furthermore, the developers in an informal poll we conducted strongly preferred to read code written using abstractions. To address the concern around copy-paste-modify, we propose a tool that merges similar pieces of code and automatically creates suitable abstractions. Our tool allows developers to get the best of both worlds: easy reuse together with custom abstractions. Because different kinds of abstractions may be beneficial in different contexts, our tool provides multiple abstraction mechanisms, which we selected based on a study of popular open-source repositories.
To demonstrate the feasibility of our approach, we have designed and implemented a prototype merging tool for C++ and evaluated our tool on a number of clones exhibiting some variation, i.e near clones, in popular Open Source packages. We observed that maintainers find our algorithmically created abstractions to be largely preferable to existing duplicated code. Rewriting existing code can be considered as a form of program transformation, where a program in one form is transformed into a program in another form. One significant form of program transformation is data representation migration that involves changing the type of a particular data structure, and then updating all of the operations that has a control or data dependence on that data structure according to the new type. Changing the data representation can provide benefits such as improving efficiency and improving the quality of the computed results. Performing such a transformation is challenging, because it requires applying data-type specific changes to code fragments that may be widely scattered throughout the source code connected by dataflow dependencies. Refactoring systems are typically sensitive to dataflow dependencies, but are not programmable with respect to the features of particular data types. Existing program transformation languages provide the needed flexibility, but do not concisely support reasoning about dataflow dependencies.
To address the needs of data representation migration, we propose a new approach to program transformation that relies on a notion of semantic dependency: every transformation step propagates the transformation process onward to code that somehow depends on the transformed code. Our approach provides a declarative transformation specification language, for expressing type-specific transformation rules. We further provide scoped rules, a mechanism for guiding rule application, and tags, a device for simple program analysis within our framework, to enable more powerful program transformations.
We have implemented a prototype transformation system based on these ideas for C and C++ code and evaluate it against three example specifications, including vectorization, transformation of integers to big integers, and transformation of array-of-structs data types to struct-of-arrays format. Our evaluation shows that our approach can improve program performance and the precision of the computed results, and that it scales to programs of at least 3700 lines.
One of the main things that we as humans do in our lifetime is the recognition and/or classification of all kind of visual objects. It is known that about fifty percentage of the neocortex is responsible for visual processing. This fact tells us that object recognition (OR) is a complex task in our and in the animal brain, but we do it in a fraction of a second.
The main question is: How does the brain exactly do it? Does the brain use some feature extraction algorithm for OR tasks? The hierarchical structure of the visual cortex and studies on a part of the visual cortex called V1 tell us that our brain uses feature extraction for OR tasks by Gabor filters. We also use our previous knowledge in object recognition to detect and recognize the objects which we never saw before. Also, as we grow up we learn new objects faster than before.
These facts imply that the visual cortex of human and other animals uses some common (universal) features at least in the first stages to distinguish between different objects. In this context, we might ask: Do universal features in images exist, such that by using them we are able to efficiently recognize any unknown object? Is it necessary to extract new special features for any new object? How about using existing features from other tasks for this? Is it possible to efficiently use extracted feature of a specific task for other tasks? Are there some general features in natural and non-natural images which can also be used for specific object recognition? For example, can we use extracted features of natural images also for handwritten digit classification?
In this context, our work proposes a new information-based approach and tries to give some answers to the questions above. As a result, in our case we found that we could indeed extract unique features which are valid in all three different kinds of tasks. They give classification results that are about as good as the results reported by the corresponding literature for the specialized systems, or even better ones.
Another problem of the OR task is the recognition of objects, independently of any perception changes. We as humans or also animals can recognize objects in spite of many deformations (e.g. changes in illumination, rotation in any direction or angles, distortion and scaling up or down) in a fraction of a second. When observing an object which we never saw, we can imagine the rotated or scaled up objectin our mind. Here, also the question arises: How does the brain solve this problem? To do this, does the brain learn some mapping algorithm (transformation), independent of the objects or their features?
There are many approaches to model the mapping task. One of the most versatile ones is the idea of dynamically changing mappings, the dynamic link mapping (DLM). Although the dynamic link mapping systems show interesting results, the DLM system has the problem of a high computational complexity. In addition, because it uses the least mean squared error as risk function, the performance for classification is also not optimal. For random values where outliers are present, this system may not work well because outliers influence the mean squared error classification much more than probability-based systems. Therefore, we would like to complete the DLM system by a modified approach.
In our contribution, we will introduce a new system which employs the information criteria (i.e. probabilities) to overcome the outlier problem of the DLM systems and has a smaller computational complexity. The new information based selforganised system can solve the problem of invariant object recognition, especially in the task of rotation in depth, and does not have the disadvantage of current DLM systems and has a smaller computational complexity.
To accommodate the growth of the software industry, programming languages are getting increasingly easy to use. The latest trend in the simplification of the software development process is the usage of visual programming environments. To make visual programming effective, the graph-like representation of the source code must be clearly arranged. This thesis details some of the difficulties in automatic layout generation and proposes an interface as well as two different implementations of automatic layout generators to integrate into the VWorkflows visual programming framework.
Algorithms for the Maximum Cardinality Matching Problem which greedily add edges to the solution enjoy great popularity. We systematically study strengths and limitations of such algorithms, in particular of those which consider node degree information to select the next edge. Concentrating on nodes of small degree is a promising approach: it was shown, experimentally and analytically, that very good approximate solutions are obtained for restricted classes of random graphs. Results achieved under these idealized conditions, however, remained unsupported by statements which depend on less optimistic assumptions.
The KarpSipser algorithm and 1-2-Greedy, which is a simplified variant of the well-known MinGreedy algorithm, proceed as follows. In each step, if a node of degree one (resp. at most two) exists, then an edge incident with a minimum degree node is picked, otherwise an arbitrary edge is added to the solution.
We analyze the approximation ratio of both algorithms on graphs of degree at most D. Families of graphs are known for which the expected approximation ratio converges to 1/2 as D grows to infinity, even if randomization against the worst case is used. If randomization is not allowed, then we show the following convergence to 1/2: the 1-2-Greedy algorithm achieves approximation ratio (D-1)/(2D-3); if the graph is bipartite, then the more restricted KarpSipser algorithm achieves the even stronger factor D/(2D-2). These guarantees set both algorithms apart from other famous matching heuristics like e.g. Greedy or MRG: these algorithms depend on randomization to break the 1/2-barrier even for paths with D=2. Moreover, for any D our guarantees are strictly larger than the best known bounds on the expected performance of the randomized variants of Greedy and MRG.
To investigate whether KarpSipser or 1-2-Greedy can be refined to achieve better performance, or be simplified without loss of approximation quality, we systematically study entire classes of deterministic greedy-like algorithms for matching. Therefore we employ the adaptive priority algorithm framework by Borodin, Nielsen, and Rackoff: in each round, an adaptive priority algorithm requests one or more edges by formulating their properties---like e.g. "is incident with a node of minimum degree"---and adds the received edges to the solution. No constraints on time and space usage are imposed, hence an adaptive priority algorithm is restricted only by its nature of picking edges in a greedy-like fashion. If an adaptive priority algorithm requests edges by processing degree information, then we show that it does not surpass the performance of KarpSipser: our D/(2D-2)-guarantee for bipartite graphs is tight and KarpSipser is optimal among all such "degree-sensitive" algorithms even though it uses degree information merely to detect degree-1 nodes. Moreover, we show that if degrees of both nodes of an edge may be processed, like e.g. the Double-MinGreedy algorithm does, then the performance of KarpSipser can only be increased marginally, if at all. Of special interest is the capability of requesting edges not only by specifying the degree of a node but additionally its set of neighbors. This enables an adaptive priority algorithm to "traverse" the input graph. We show that on general degree-bounded graphs no such algorithm can beat factor (D-1)/(2D-3). Hence our bound for 1-2-Greedy is tight and this algorithm performs optimally even though it ignores neighbor information. Furthermore, we show that an adaptive priority algorithm deteriorates to approximation ratio exactly 1/2 if it does not request small degree nodes. This tremendous decline of approximation quality happens for graphs on which 1-2-Greedy and KarpSipser perform optimally, namely paths with D=2. Consequently, requesting small degree nodes is vital to beat factor 1/2.
Summarizing, our results show that 1-2-Greedy and KarpSipser stand out from known and hypothetical algorithms as an intriguing combination of both approximation quality and conceptual simplicity.