@phdthesis{Hecher2021, author = {Hecher, Markus}, title = {Advanced tools and methods for treewidth-based problem solving}, doi = {10.25932/publishup-51251}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-512519}, school = {Universit{\"a}t Potsdam}, pages = {xv, 184}, year = {2021}, abstract = {In the last decades, there was a notable progress in solving the well-known Boolean satisfiability (Sat) problem, which can be witnessed by powerful Sat solvers. One of the reasons why these solvers are so fast are structural properties of instances that are utilized by the solver's interna. This thesis deals with the well-studied structural property treewidth, which measures the closeness of an instance to being a tree. In fact, there are many problems parameterized by treewidth that are solvable in polynomial time in the instance size when parameterized by treewidth. In this work, we study advanced treewidth-based methods and tools for problems in knowledge representation and reasoning (KR). Thereby, we provide means to establish precise runtime results (upper bounds) for canonical problems relevant to KR. Then, we present a new type of problem reduction, which we call decomposition-guided (DG) that allows us to precisely monitor the treewidth when reducing from one problem to another problem. This new reduction type will be the basis for a long-open lower bound result for quantified Boolean formulas and allows us to design a new methodology for establishing runtime lower bounds for problems parameterized by treewidth. Finally, despite these lower bounds, we provide an efficient implementation of algorithms that adhere to treewidth. Our approach finds suitable abstractions of instances, which are subsequently refined in a recursive fashion, and it uses Sat solvers for solving subproblems. It turns out that our resulting solver is quite competitive for two canonical counting problems related to Sat.}, language = {en} } @phdthesis{Boeken2022, author = {B{\"o}ken, Bj{\"o}rn}, title = {Improving prediction accuracy using dynamic information}, doi = {10.25932/publishup-58512}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-585125}, school = {Universit{\"a}t Potsdam}, pages = {xii, 160}, year = {2022}, abstract = {Accurately solving classification problems nowadays is likely to be the most relevant machine learning task. Binary classification separating two classes only is algorithmically simpler but has fewer potential applications as many real-world problems are multi-class. On the reverse, separating only a subset of classes simplifies the classification task. Even though existing multi-class machine learning algorithms are very flexible regarding the number of classes, they assume that the target set Y is fixed and cannot be restricted once the training is finished. On the other hand, existing state-of-the-art production environments are becoming increasingly interconnected with the advance of Industry 4.0 and related technologies such that additional information can simplify the respective classification problems. In light of this, the main aim of this thesis is to introduce dynamic classification that generalizes multi-class classification such that the target class set can be restricted arbitrarily to a non-empty class subset M of Y at any time between two consecutive predictions. This task is solved by a combination of two algorithmic approaches. First, classifier calibration, which transforms predictions into posterior probability estimates that are intended to be well calibrated. The analysis provided focuses on monotonic calibration and in particular corrects wrong statements that appeared in the literature. It also reveals that bin-based evaluation metrics, which became popular in recent years, are unjustified and should not be used at all. Next, the validity of Platt scaling, which is the most relevant parametric calibration approach, is analyzed in depth. In particular, its optimality for classifier predictions distributed according to four different families of probability distributions as well its equivalence with Beta calibration up to a sigmoidal preprocessing are proven. For non-monotonic calibration, extended variants on kernel density estimation and the ensemble method EKDE are introduced. Finally, the calibration techniques are evaluated using a simulation study with complete information as well as on a selection of 46 real-world data sets. Building on this, classifier calibration is applied as part of decomposition-based classification that aims to reduce multi-class problems to simpler (usually binary) prediction tasks. For the involved fusing step performed at prediction time, a new approach based on evidence theory is presented that uses classifier calibration to model mass functions. This allows the analysis of decomposition-based classification against a strictly formal background and to prove closed-form equations for the overall combinations. Furthermore, the same formalism leads to a consistent integration of dynamic class information, yielding a theoretically justified and computationally tractable dynamic classification model. The insights gained from this modeling are combined with pairwise coupling, which is one of the most relevant reduction-based classification approaches, such that all individual predictions are combined with a weight. This not only generalizes existing works on pairwise coupling but also enables the integration of dynamic class information. Lastly, a thorough empirical study is performed that compares all newly introduced approaches to existing state-of-the-art techniques. For this, evaluation metrics for dynamic classification are introduced that depend on corresponding sampling strategies. Thereafter, these are applied during a three-part evaluation. First, support vector machines and random forests are applied on 26 data sets from the UCI Machine Learning Repository. Second, two state-of-the-art deep neural networks are evaluated on five benchmark data sets from a relatively recent reference work. Here, computationally feasible strategies to apply the presented algorithms in combination with large-scale models are particularly relevant because a naive application is computationally intractable. Finally, reference data from a real-world process allowing the inclusion of dynamic class information are collected and evaluated. The results show that in combination with support vector machines and random forests, pairwise coupling approaches yield the best results, while in combination with deep neural networks, differences between the different approaches are mostly small to negligible. Most importantly, all results empirically confirm that dynamic classification succeeds in improving the respective prediction accuracies. Therefore, it is crucial to pass dynamic class information in respective applications, which requires an appropriate digital infrastructure.}, language = {en} } @misc{PrasseIversenLienhardetal.2022, author = {Prasse, Paul and Iversen, Pascal and Lienhard, Matthias and Thedinga, Kristina and Herwig, Ralf and Scheffer, Tobias}, title = {Pre-Training on In Vitro and Fine-Tuning on Patient-Derived Data Improves Deep Neural Networks for Anti-Cancer Drug-Sensitivity Prediction}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, issn = {1866-8372}, doi = {10.25932/publishup-57734}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-577341}, pages = {1 -- 14}, year = {2022}, abstract = {Large-scale databases that report the inhibitory capacities of many combinations of candidate drug compounds and cultivated cancer cell lines have driven the development of preclinical drug-sensitivity models based on machine learning. However, cultivated cell lines have devolved from human cancer cells over years or even decades under selective pressure in culture conditions. Moreover, models that have been trained on in vitro data cannot account for interactions with other types of cells. Drug-response data that are based on patient-derived cell cultures, xenografts, and organoids, on the other hand, are not available in the quantities that are needed to train high-capacity machine-learning models. We found that pre-training deep neural network models of drug sensitivity on in vitro drug-sensitivity databases before fine-tuning the model parameters on patient-derived data improves the models' accuracy and improves the biological plausibility of the features, compared to training only on patient-derived data. From our experiments, we can conclude that pre-trained models outperform models that have been trained on the target domains in the vast majority of cases.}, language = {en} } @misc{AlLabanRegerLucke2022, author = {Al Laban, Firas and Reger, Martin and Lucke, Ulrike}, title = {Closing the Policy Gap in the Academic Bridge}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1310}, issn = {1866-8372}, doi = {10.25932/publishup-58357}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-583572}, pages = {22}, year = {2022}, abstract = {The highly structured nature of the educational sector demands effective policy mechanisms close to the needs of the field. That is why evidence-based policy making, endorsed by the European Commission under Erasmus+ Key Action 3, aims to make an alignment between the domains of policy and practice. Against this background, this article addresses two issues: First, that there is a vertical gap in the translation of higher-level policies to local strategies and regulations. Second, that there is a horizontal gap between educational domains regarding the policy awareness of individual players. This was analyzed in quantitative and qualitative studies with domain experts from the fields of virtual mobility and teacher training. From our findings, we argue that the combination of both gaps puts the academic bridge from secondary to tertiary education at risk, including the associated knowledge proficiency levels. We discuss the role of digitalization in the academic bridge by asking the question: which value does the involved stakeholders expect from educational policies? As a theoretical basis, we rely on the model of value co-creation for and by stakeholders. We describe the used instruments along with the obtained results and proposed benefits. Moreover, we reflect on the methodology applied, and we finally derive recommendations for future academic bridge policies.}, language = {en} } @misc{Cichalla2022, type = {Master Thesis}, author = {Cichalla, Anika Katleen}, title = {Ein konstruktivistisches Modell f{\"u}r die Didaktik der Informatik im Bachelorstudium}, doi = {10.25932/publishup-55071}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-550710}, school = {Universit{\"a}t Potsdam}, pages = {66}, year = {2022}, abstract = {Lehrende in der Lehrkr{\"a}fteausbildung sind stets damit konfrontiert, dass sie den Studierenden innovative Methoden modernen Schulunterrichts traditionell rezipierend vorstellen. In Deutschland gibt es circa 40 Universit{\"a}ten, die Informatik mit Lehramtsbezug ausbilden. Allerdings gibt es nur wenige Konzepte, die sich mit der Verbindung von Bildungswissenschaften und der Informatik mit ihrer Didaktik besch{\"a}ftigen und keine Konzepte, die eine konstruktivistische Lehre in der Informatik verfolgen. Daher zielt diese Masterarbeit darauf ab, diese L{\"u}cke aufgreifen und anhand des „Didaktik der Informatik I" Moduls der Universit{\"a}t Potsdam ein Modell zur konstruktivistischen Hochschullehre zu entwickeln. Dabei soll ein bestehendes konstruktivistisches Lehrmodell auf die Informatikdidaktik {\"u}bertragen und Elemente zur Verbindung von Bildungswissenschaften, Fachwissenschaften und Fachdidaktiken mit einbezogen werden. Dies kann eine Grundlage f{\"u}r die Planung von Informatikdidaktischen Modulen bieten, aber auch als Inspiration zur {\"U}bertragung bestehender innovativer Lehrkonzepte auf andere Fachdidaktiken dienen. Um ein solches konstruktivistisches Lehr-Lern-Modell zu erstellen, wird zun{\"a}chst der Zusammenhang von Bildungswissenschaften, Fachwissenschaften und Fachdidaktiken erl{\"a}utert und anschließend die Notwendigkeit einer Vernetzung hervorgehoben. Hieran folgt eine Darstellung zu relevanten Lerntheorien und bereits entwickelten innovativen Lernkonzepten. Ankn{\"u}pfend wird darauf eingegangen, welche Anforderungen die Kultusminister- Konferenz an die Ausbildung von Lehrkr{\"a}ften stellt und wie diese Ausbildung f{\"u}r die Informatik momentan an der Universit{\"a}t Potsdam erfolgt. Aus allen Erkenntnissen heraus werden Anforderungen an ein konstruktivistisches Lehrmodell festgelegt. Unter Ber{\"u}cksichtigung der Voraussetzungen der Studienordnung f{\"u}r das Lehramt Informatik wird anschließend ein Modell f{\"u}r konstruktivistische Informatikdidaktik vorgestellt. Weiterf{\"u}hrende Forschung k{\"o}nnte sich damit auseinandersetzen, inwiefern sich die Motivation und Leistung im vergleich zum urspr{\"u}nglichen Modul {\"a}ndert und ob die Kompetenzen zur Unterrichtsplanung und Unterrichtsgestaltung durch das neue Modulkonzept st{\"a}rker ausgebaut werden k{\"o}nnen.}, language = {de} } @masterthesis{Repp2023, type = {Bachelor Thesis}, author = {Repp, Leo}, title = {Extending the automatic theorem prover nanoCoP with arithmetic procedures}, doi = {10.25932/publishup-57619}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-576195}, school = {Universit{\"a}t Potsdam}, pages = {52}, year = {2023}, abstract = {In dieser Bachelorarbeit implementiere ich den automatischen Theorembeweiser nanoCoP-Ω. Es handelt sich bei diesem neuen System um das Ergebnis einer Portierung von Arithmetik-behandelnden Prozeduren aus dem automatischen Theorembeweiser mit Arithmetik leanCoP-Ω in das System nanoCoP 2.0. Dazu wird zuerst der mathematische Hintergrund zu automatischen Theorembeweisern und Arithmetik gegeben. Ich stelle die Vorg{\"a}ngerprojekte leanCoP, nanoCoP und leanCoP-Ω vor, auf dessen Vorlage nanoCoP-Ω entwickelt wurde. Es folgt eine ausf{\"u}hrliche Erkl{\"a}rung der Konzepte, um welche der nicht-klausale Konnektionskalk{\"u}l erweitert werden muss, um eine Behandlung von arithmetischen Ausdr{\"u}cken und Gleichheiten in den Kalk{\"u}l zu integrieren, sowie eine Beschreibung der Implementierung dieser Konzepte in nanoCoP-Ω. Als letztes folgt eine experimentelle Evaluation von nanoCoP-Ω. Es wurde ein ausf{\"u}hrlicher Vergleich von Laufzeit und Anzahl gel{\"o}ster Probleme im Vergleich zum {\"a}hnlich aufgebauten Theorembeweiser leanCoP-Ω auf Basis der TPTP-Benchmark durchgef{\"u}hrt. Ich komme zu dem Ergebnis, dass nanoCoP-Ω deutlich schneller ist als leanCoP-Ω ist, jedoch weniger gut geeignet f{\"u}r gr{\"o}ßere Probleme. Zudem konnte ich feststellen, dass nanoCoP-Ω falsche Beweise liefern kann. Ich bespreche, wie dieses Problem gel{\"o}st werden kann, sowie einige m{\"o}gliche Optimierungen und Erweiterungen des Beweissystems.}, language = {en} } @inproceedings{DeselOpelSiegerisetal.2023, author = {Desel, J{\"o}rg and Opel, Simone and Siegeris, Juliane and Draude, Claude and Weber, Gerhard and Schell, Timon and Schwill, Andreas and Thorbr{\"u}gge, Carsten and Sch{\"a}fer, Len Ole and Netzer, Cajus Marian and Gerstenberger, Dietrich and Winkelnkemper, Felix and Schulte, Carsten and B{\"o}ttcher, Axel and Thurner, Veronika and H{\"a}fner, Tanja and Ottinger, Sarah and Große-B{\"o}lting, Gregor and Scheppach, Lukas and M{\"u}hling, Andreas and Baberowski, David and Leonhardt, Thiemo and Rentsch, Susanne and Bergner, Nadine and Bonorden, Leif and Stemme, Jonas and Hoppe, Uwe and Weicker, Karsten and Bender, Esther and Barbas, Helena and Hamann, Fabian and Soll, Marcus and Sitzmann, Daniel}, title = {Hochschuldidaktik Informatik HDI 2021}, series = {Commentarii informaticae didacticae}, booktitle = {Commentarii informaticae didacticae}, number = {13}, editor = {Desel, J{\"o}rg and Opel, Simone and Siegeris, Juliane}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, isbn = {978-3-86956-548-4}, issn = {1868-0844}, doi = {10.25932/publishup-56507}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-565070}, pages = {299}, year = {2023}, abstract = {Die Fachtagungen HDI (Hochschuldidaktik Informatik) besch{\"a}ftigen sich mit den unterschiedlichen Aspekten informatischer Bildung im Hochschulbereich. Neben den allgemeinen Themen wie verschiedenen Lehr- und Lernformen, dem Einsatz von Informatiksystemen in der Hochschullehre oder Fragen der Gewinnung von geeigneten Studierenden, deren Kompetenzerwerb oder auch der Betreuung der Studierenden widmet sich die HDI immer auch einem Schwerpunktthema. Im Jahr 2021 war dies die Ber{\"u}cksichtigung von Diversit{\"a}t in der Lehre. Diskutiert wurden beispielsweise die Einbeziehung von besonderen fachlichen und {\"u}berfachlichen Kompetenzen Studierender, der Unterst{\"u}tzung von Durchl{\"a}ssigkeit aus nichtakademischen Berufen, aber auch die Gestaltung inklusiver Lehr- und Lernszenarios, Aspekte des Lebenslangen Lernens oder sich an die Diversit{\"a}t von Studierenden adaptierte oder adaptierende Lehrsysteme. Dieser Band enth{\"a}lt ausgew{\"a}hlte Beitr{\"a}ge der 9. Fachtagung 2021, die in besonderer Weise die Konferenz und die dort diskutierten Themen repr{\"a}sentieren.}, language = {de} } @phdthesis{Middelanis2023, author = {Middelanis, Robin}, title = {Global response to local extremes—a storyline approach on economic loss propagation from weather extremes}, doi = {10.25932/publishup-61112}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-611127}, school = {Universit{\"a}t Potsdam}, pages = {vii, 237}, year = {2023}, abstract = {Due to anthropogenic greenhouse gas emissions, Earth's average surface temperature is steadily increasing. As a consequence, many weather extremes are likely to become more frequent and intense. This poses a threat to natural and human systems, with local impacts capable of destroying exposed assets and infrastructure, and disrupting economic and societal activity. Yet, these effects are not locally confined to the directly affected regions, as they can trigger indirect economic repercussions through loss propagation along supply chains. As a result, local extremes yield a potentially global economic response. To build economic resilience and design effective adaptation measures that mitigate adverse socio-economic impacts of ongoing climate change, it is crucial to gain a comprehensive understanding of indirect impacts and the underlying economic mechanisms. Presenting six articles in this thesis, I contribute towards this understanding. To this end, I expand on local impacts under current and future climate, the resulting global economic response, as well as the methods and tools to analyze this response. Starting with a traditional assessment of weather extremes under climate change, the first article investigates extreme snowfall in the Northern Hemisphere until the end of the century. Analyzing an ensemble of global climate model projections reveals an increase of the most extreme snowfall, while mean snowfall decreases. Assessing repercussions beyond local impacts, I employ numerical simulations to compute indirect economic effects from weather extremes with the numerical agent-based shock propagation model Acclimate. This model is used in conjunction with the recently emerged storyline framework, which involves analyzing the impacts of a particular reference extreme event and comparing them to impacts in plausible counterfactual scenarios under various climate or socio-economic conditions. Using this approach, I introduce three primary storylines that shed light on the complex mechanisms underlying economic loss propagation. In the second and third articles of this thesis, I analyze storylines for the historical Hurricanes Sandy (2012) and Harvey (2017) in the USA. For this, I first estimate local economic output losses and then simulate the resulting global economic response with Acclimate. The storyline for Hurricane Sandy thereby focuses on global consumption price anomalies and the resulting changes in consumption. I find that the local economic disruption leads to a global wave-like economic price ripple, with upstream effects propagating in the supplier direction and downstream effects in the buyer direction. Initially, an upstream demand reduction causes consumption price decreases, followed by a downstream supply shortage and increasing prices, before the anomalies decay in a normalization phase. A dominant upstream or downstream effect leads to net consumption gains or losses of a region, respectively. Moreover, I demonstrate that a longer direct economic shock intensifies the downstream effect for many regions, leading to an overall consumption loss. The third article of my thesis builds upon the developed loss estimation method by incorporating projections to future global warming levels. I use these projections to explore how the global production response to Hurricane Harvey would change under further increased global warming. The results show that, while the USA is able to nationally offset direct losses in the reference configuration, other countries have to compensate for increasing shares of counterfactual future losses. This compensation is mainly achieved by large exporting countries, but gradually shifts towards smaller regions. These findings not only highlight the economy's ability to flexibly mitigate disaster losses to a certain extent, but also reveal the vulnerability and economic disadvantage of regions that are exposed to extreme weather events. The storyline in the fourth article of my thesis investigates the interaction between global economic stress and the propagation of losses from weather extremes. I examine indirect impacts of weather extremes — tropical cyclones, heat stress, and river floods — worldwide under two different economic conditions: an unstressed economy and a globally stressed economy, as seen during the Covid-19 pandemic. I demonstrate that the adverse effects of weather extremes on global consumption are strongly amplified when the economy is under stress. Specifically, consumption losses in the USA and China double and triple, respectively, due to the global economy's decreased capacity for disaster loss compensation. An aggravated scarcity intensifies the price response, causing consumption losses to increase. Advancing on the methods and tools used here, the final two articles in my thesis extend the agent-based model Acclimate and formalize the storyline approach. With the model extension described in the fifth article, regional consumers make rational choices on the goods bought such that their utility is maximized under a constrained budget. In an out-of-equilibrium economy, these rational consumers are shown to temporarily increase consumption of certain goods in spite of rising prices. The sixth article of my thesis proposes a formalization of the storyline framework, drawing on multiple studies including storylines presented in this thesis. The proposed guideline defines eight central elements that can be used to construct a storyline. Overall, this thesis contributes towards a better understanding of economic repercussions of weather extremes. It achieves this by providing assessments of local direct impacts, highlighting mechanisms and impacts of loss propagation, and advancing on methods and tools used.}, language = {en} } @article{SchellSchwill2023, author = {Schell, Timon and Schwill, Andreas}, title = {„Es ist kompliziert, alles inklusive Privatleben unter einen Hut zu bekommen"}, series = {Hochschuldidaktik Informatik HDI 2021 (Commentarii informaticae didacticae)}, journal = {Hochschuldidaktik Informatik HDI 2021 (Commentarii informaticae didacticae)}, number = {13}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, isbn = {978-3-86956-548-4}, issn = {1868-0844}, doi = {10.25932/publishup-61388}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-613882}, pages = {53 -- 71}, year = {2023}, abstract = {Eine {\"u}bliche Erz{\"a}hlung verkn{\"u}pft lange Studienzeiten und hohe Abbrecherquoten im Informatikstudium zum einen mit der sehr gut bezahlten Nebent{\"a}tigkeit von Studierenden in der Informatikbranche, die deutlich studienzeitverl{\"a}ngernd sei; zum anderen werde wegen des hohen Bedarfs an Informatikern ein formeller Studienabschluss von den Studierenden h{\"a}ufig als entbehrlich betrachtet und eine Karriere in der Informatikbranche ohne abgeschlossenes Studium begonnen. In dieser Studie, durchgef{\"u}hrt an der Universit{\"a}t Potsdam, untersuchen wir, wie viele Informatikstudierende neben dem Studium innerhalb und außerhalb der Informatikbranche arbeiten, welche Erwartungen sie neben der Bezahlung damit verbinden und wie sich die T{\"a}tigkeit auf ihr Studium und ihre sp{\"a}tere berufliche Perspektive auswirkt. Aus aktuellem Anlass interessieren uns auch die Auswirkungen der Covid-19-Pandemie auf die Arbeitst{\"a}tigkeiten der Informatikstudierenden.}, language = {de} } @phdthesis{SchulzHanke2023, author = {Schulz-Hanke, Christian}, title = {BCH Codes mit kombinierter Korrektur und Erkennung}, doi = {10.25932/publishup-61794}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-617943}, school = {Universit{\"a}t Potsdam}, pages = {ii, 191}, year = {2023}, abstract = {BCH Codes mit kombinierter Korrektur und Erkennung In dieser Arbeit wird auf Grundlage des BCH Codes untersucht, wie eine Fehlerkorrektur mit einer Erkennung h{\"o}herer Fehleranzahlen kombiniert werden kann. Mit dem Verfahren der 1-Bit Korrektur mit zus{\"a}tzlicher Erkennung h{\"o}herer Fehler wurde ein Ansatz entwickelt, welcher die Erkennung zus{\"a}tzlicher Fehler durch das parallele L{\"o}sen einfacher Gleichungen der Form s_x = s_1^x durchf{\"u}hrt. Die Anzahl dieser Gleichungen ist linear zu der Anzahl der zu {\"u}berpr{\"u}fenden h{\"o}heren Fehler. In dieser Arbeit wurde zus{\"a}tzlich f{\"u}r bis zu 4-Bit Korrekturen mit zus{\"a}tzlicher Erkennung h{\"o}herer Fehler ein weiterer allgemeiner Ansatz vorgestellt. Dabei werden parallel f{\"u}r alle korrigierbaren Fehleranzahlen spekulative Fehlerkorrekturen durchgef{\"u}hrt. Aus den bestimmten Fehlerstellen werden spekulative Syndromkomponenten erzeugt, durch welche die Fehlerstellen best{\"a}tigt und h{\"o}here erkennbare Fehleranzahlen ausgeschlossen werden k{\"o}nnen. Die vorgestellten Ans{\"a}tze unterscheiden sich von dem in entwickelten Ansatz, bei welchem die Anzahl der Fehlerstellen durch die Berechnung von Determinanten in absteigender Reihenfolge berechnet wird, bis die erste Determinante 0 bildet. Bei dem bekannten Verfahren ist durch die Berechnung der Determinanten eine faktorielle Anzahl an Berechnungen in Relation zu der Anzahl zu {\"u}berpr{\"u}fender Fehler durchzuf{\"u}hren. Im Vergleich zu dem bekannten sequentiellen Verfahrens nach Berlekamp Massey besitzen die Berechnungen im vorgestellten Ansatz simple Gleichungen und k{\"o}nnen parallel durchgef{\"u}hrt werden.Bei dem bekannten Verfahren zur parallelen Korrektur von 4-Bit Fehlern ist eine Gleichung vierten Grades im GF(2^m) zu l{\"o}sen. Dies erfolgt, indem eine Hilfsgleichung dritten Grades und vier Gleichungen zweiten Grades parallel gel{\"o}st werden. In der vorliegenden Arbeit wurde gezeigt, dass sich eine Gleichung zweiten Grades einsparen l{\"a}sst, wodurch sich eine Vereinfachung der Hardware bei einer parallelen Realisierung der 4-Bit Korrektur ergibt. Die erzielten Ergebnisse wurden durch umfangreiche Simulationen in Software und Hardwareimplementierungen {\"u}berpr{\"u}ft.}, language = {de} }