Identifizierung quantifizierbarer Bewertungsinhalte und -kategorien mittels Text Mining - Kersting, Joschka
Reading between the lines has so far been reserved for humans. The present dissertation addresses this research gap using machine learning methods. Implicit expressions are not comprehensible by computers and cannot be localized in the text. However, many texts arise on interpersonal topics that, unlike commercial evaluation texts, often imply information only by means of longer phrases. Examples are the kindness and the attentiveness of a doctor, which are only paraphrased (“he didn’t even look me in the eye”). The analysis of such data, especially the identification and localization of implicit statements, is a research gap (1). This work uses so-called Aspect-based Sentiment Analysis as a method for this purpose. It remains open how the aspect categories to be extracted can be discovered and thematically delineated based on the data (2). Furthermore, it is not yet explored how a collection of tools should look like, with which implicit phrases can be identified and thus made explicit (3). Last, it is an open question how to correlate the identified phrases from the text data with other data, including the investigation of the relationship between quantitative scores (e.g., school grades) and the thematically related text (4). Based on these research gaps, the research question is posed as follows: Using text mining methods, how can implicit rating content be properly interpreted and thus made explicit before it is automatically categorized and quantified? The uniqueness of this dissertation is based on the automated recognition of implicit linguistic statements alongside explicit statements. These are identified in unstructured text data so that features expressed only in the text can later be compared across data sources, even though they were not included in rating categories such as stars or school grades. German-language physician ratings from websites in three countries serve as the sample domain. The solution approach consists of data creation, a pipeline for text processing and analyses based on this. In the data creation, aspect classes are identified and delineated across platforms and marked in text data. This results in six datasets with over 70,000 annotated sentences and detailed guidelines. The models that were created based on the training data extract and categorize the aspects. In addition, the sentiment polarity and the evaluation weight, i. e., the importance of each phrase, are determined. The models, which are combined in a pipeline, are used in a prototype in the form of a web application. The analyses built on the pipeline quantify the rating contents by linking the obtained information with further data, thus allowing new insights. As a result, a toolbox is provided to identify quantifiable rating content and categories using text mining for a sample domain. This is used to evaluate the approach, which in principle can also be adapted to any other domain.

Knowledge Base Enhanced & User-centric Dialogue Design for OTF Computing - Ahmed, Mobeen
This thesis aims to provide a bidirectional chatbot solution for the requirement engineering process. The Sonderforschungsbereich (SFB) 901 intends to provide the composition of software service On-the-Fly (OTF). The sub-project (B1) of the SFB 901 project deals with the parameters of service configuration. OTF Computing aims to eradicate the dependency on the requirement engineers for the software development process. However, there is no existing bidirectional chatbot solution that analyses user software requirements and provides viable suggestions to the user regarding their service. Previously, CORDULA chatbot was developed to analyze the software requirements but cannot keep the conversation’s context. The Rasa framework is integrated with the knowledge base to solve the issue, the knowledge base provides domain-specific knowledge to the chatbot. The software description is passed through the natural language understanding process to give consciousness to the chatbot. This process involves various machine learning models, including app family classification, to correctly identify the domain for user OTF service. The statistical models like naïve Bayes, kNN and SVM are compared with transformer models for this classification task. Furthermore, the entities (functional requirements) are also separated from the user description. The chatbot provides the suggestion of requirements from the preliminary service template with the support of the knowledge base. Furthermore, the generated response is compared with the state-of-the-art DialoGPT transformer model and ChatterBot conversational library. These models are trained over the software development related conversational dataset. All the responses are ranked using the DialoRPT model, and the BLEU score to evaluates the models’ responses. Moreover, the chatbot mod- els are tested with human participants, they used and scored the chatbot responses based on effectiveness, efficiency and satisfaction. The overall response accuracy is also measured by averaging the user approval over the generated responses.

Domain-aware Text Professionalization using Sequence-to-Sequence Neural Networks - Palushi, Juela

Propaganda Technique Detection Using Connotation Frames - Budanurmath, Vinaykumar

Political Speaker Transfer: Learning to Generate Text in the Styles of Barack Obama and Donald Trump - Bülling, Jonas

Computational Text Professionalization using Neural Sequence-to-Sequence Models - Mishra, Avishek

Organic Programming of Dynamic Real-Time Applications - Khaluf, Lial

Requirements Engineering im OTF-Computing: Informationsextraktion und Unvollständigkeitskompensation mittels domänenspezifischer Wissensbasis - Friesen, Edwin

Was kommt zuerst? Erkennung von zeitlichen Abläufen infunktionalen Softwareanforderungsbeschreibungen - Grobbel, Florian

Was ist gemeint? Strukturell ambige Sätze als Herausforderung für Parsing-Ansätze - Theda, Mona

Indikatorbasierte Erkennung und Kompensation von ungenauen und unvollständig beschriebenen Softwareanforderungen - Bäumer, Frederik Simon
The vision of OTF Computing is to have the software needs of end users in the future covered by an automatic composition of existing software services. Here we focus on natural language software requirements that end users formulate and submit to OTF providers as requirement specifications. These requirements serve as the sole foundation for the composition of software; but they can be inaccurate and incomplete. Up to now, software developers have identified and corrected these deficits by using a bidirectional consolidation process. However, this type of quality assurance is no longer included in OTF Computing - the classic consolidation process is dropped. This is where this work picks up, dealing with the inaccuracies of freely formulated software design requirements. To do this, we developed the CORDULA (Compensation of Requirements Descriptions Using Linguistic Analysis) system that recognizes and compensates for language deficiencies (e.g., ambiguity, vagueness and incompleteness) in requirements written by inexperienced end users. CORDULA supports the search for suitable software services that can be combined in a composition by transferring requirement specifications into canonical core functionalities. This dissertation provides the first-ever method for holistically recording and improving language deficiencies in user-generated requirement specifications by dealing with ambiguity, incompleteness and vagueness in parallel and in sequence.

Denn wir wissen, was gemeint ist: Erweiterung bestehender Lösungen zur lexikalischen Disambiguierung durch einen kontextsensitiven Whitelist-Ansatz - Krammer, Isabel

Active Learning of User Requirement Specifications in Dynamic Software Service Markets - Wever, Marcel Dominik

Evaluation of Software Reputation Matching Based on App Reviews - Sergio Djoum Temdjim, Albin

Erweiterung eines kontextsensitiven Autovervollständigungstools zur natürlichsprachlichen Softwarespezifikation - Rehmer, Lennart

Fuzzy Matching of Comprehensive Service Specifications - Platenius, Marie Christin

Frag die Anwender: Extraktion und Klassifikation von funktionalen Softwareanforderungen aus User-Generated-Content - Dollmann, Markus

Ontologie-Erstellung mittels Text-Mining aus App-Marktplätzen am Beispiel des Google Marketplace - Heck, Eduard

Ontologie-basierte Extraktion funktionaler Softwareanforderungen am Fallbeispiel mobiler Kommunikationsapplikationen - Schwentker, Christoph

Herausforderungen im Umgang mit unvollständigen Softwareanforderungen durch Semantic Role Labeling - Reckhorn, Lena

Modellierung von domänenspezifischen Ontologien im Anwendungsfall funktionaler Softwareanforderungen - Stanco, Stefan

Solving Heterogeneity for a Successful Service Market - Arifulina, Svetlana

Vergleich von Disambiguierungsansätzen bei Anforderungsbeschreibungen - Vollmers, Daniel

Fuzzy Matching von Vor- und Nachbedingungen in Servicespezikationen - Börding, Paul

Ein Framework für Fuzzy Service Matching basierend auf Fuzzy Sets - Neumann, Conrad

Design of an Evaluation Strategy for Fuzzy Service Matching - Bruns, Melanie

Automatic Service Discovery and Composition for heterogeneous service partners - Huma, Zille

Combination of Service Matching Steps in Consideration of Efficiency and Fuzziness - Gao, Yuan

Modeling and Matching of Reputation of Services in On-The-Fly Computing - Bano, Dorina

Measuring Transformation-induced Uncertainty in Service Matching: A Feasibility Study - Bunse, Mirko

Improving Service Specifications for the Service Matching on a Service Market - Taherinajafabadi, Vahide

Handling Incomplete Service Specifications using Fuzzy Matching - Vijapurwala, Shafi

Fuzzy Matching of Service Price Specifications - Merschjohann, Sven

Reengineering of Component-Based Software Systems in the Presence of Design Deficiencies - von Detten, Markus
The maintenance of component-based software systems requires up-to-date models of their concrete architecture, i.e. the architecture that is realised in the source code. These models help in systematically planning, analysing and executing typical reengineering activities. Often no or only outdated architectural models of such systems exist. Therefore, various reverse engineering methods have been developed which try to recover a system's components, subsystems and connectors. However, these reverse engineering methods are severely impacted by design deciencies in the system's code base, especially violations of the component encapsulation. As long as design deciencies are not considered in the reverse engineering process, they reduce the quality of the recovered component structures. Despite this impact of design deciencies, no existing architecture reconstruction approach explicitly integrates a systematic deciency detection and removal into the recovery process. Therefore, I have developed Archimetrix. Archimetrix is a tool-supported architecture reconstruction process. It enhances a clustering-based architecture recovery approach with an extensible, pattern-based deciency detection. After the detection of deciencies, Archimetrix supports the software architect in removing the de ciencies and provides the means to preview the architectural consequences of such a removal. I also provide a process to identify and formalise additional deciencies. I validated the approach on three case studies which show that Archimetrix is able to identify relevant deciencies and that the removal of these deciencies leads to an increased quality of the recovered architectures, i.e. they are closer to the corresponding conceptual architectures.

Quality Assurance with Dynamic Meta Modeling - Soltenborn, Christian
Dynamic Meta Modeling (DMM) is a semantics specification technique targeted at MOF-based modeling languages, where a language's behavior is defined by means of graphical operational rules which change runtime models. The DMM approach has first been suggested by Engels et al. in 2000; Hausmann has then defined the DMM language on a conceptual level within his PhD thesis in 2006. Consequently, the next step was to bring the existing DMM concepts alive, and then to apply them to different modeling languages, making use of the lessons learned to improve the DMM concepts as well as the DMM tooling. The result of this process is the DMM++ method, which is presented within this thesis. Our contributions are three-fold: First, and according to our experiences with the DMM language, we have introduced new concepts such as refinement by means of rule overriding, and we have strengthened existing concepts such as the dealing with universally quantified structures or attributes. Second, we have developed a test-driven process for semantics specification: A set of test models is created, and their expected behavior is fixed. Then, the DMM rules are created incrementally, finally resulting in a DMM ruleset realizing at least the expected behavior of the test models. Additionally, we have defined a set of coverage criteria for DMM rulesets which allow to measure the quality of a set of test models. Third, we have shown how functional as well as non-functional requirements can be formulated against models and their DMM specifications. The former is achieved by providing a visual language for formulating temporal logic properties, which are then verified with model checking techniques, and by allowing for visual debugging of models failing a requirement. For the latter, the modeler can add performance information to models and analyze their performance properties, e.g. average throughput.

Ontology-based Normalization and Matching of Rich Service Descriptions - Schwichtenberg, Simon

Klassifizierung unterschiedlicher Ansätze zum Matching von Services - Petrausch, Vanessa

Comparison of Various Contract-Based Approaches for Specifying Behavior of On-The-Fly Computing Services - Jagannath, Kavitha

Business Process Models - Change Management - Gerth, Christian
In recent years, the role of process models in the development of enterprise software systems has increased continuously. Today, process models are used at different levels in the development process. For instance, in Service-Oriented Architectures (SOA), high-level business process models become input for the development of IT systems, and in running IT systems executable process models describe choreographies of Web Services. A key driver behind this development is the necessity for a closer alignment of business and IT requirements, to reduce the reaction times in software development to frequent changes in competitive markets.Typically in these scenarios, process models are developed, maintained, and transformed in a team environment by several stakeholders that are often from different business units, resulting in different versions. To obtain integrated process models comprising the changes applied to different versions, the versions need to be consolidated by means of model change management. Change management for process models can be compared to widely used concurrent versioning systems (CVS) and consists of the following major activities: matching of process models, detection of differences, computation of dependencies and conflicts between differences, and merging of process models.Although in general model-driven development (MDD) is accepted as a well-established development approach, there are still some shortcomings that let developers decide against MDD and for more traditional development paradigms. These shortcomings comprise a lack of fully integrated and fully featured development environments for MDD, such as a comprehensive support for model change management.In this thesis, we present a framework for process model change management. The framework is based on an intermediate representation for process models that serves as an abstraction of specific process modeling languages and focuses on common syntactic and semantic core concepts for the modeling of workflow in process models. Based on the intermediate representation, we match process models in versioning scenarios and compute differences between process models generically. Further, we consider the analysis of dependencies between differences and show how conflicts between differences can be computed by taking into account the semantics of the modeling language.As proof-of concept, we have implemented major parts of this framework in terms of a prototype. The detection of differences and dependencies contributed also to the Compare & Merge framework for the IBM WebSphere Business Modeler V 7.0 [1] (WBM), which was released as a product in fall 2009.

Reengineering of Design Deficiencies in Component-Based Software Architectures - Platenius, Marie Christin

Coverage Criteria for Testing DMM Specifications - Arifulina, Svetlana