Transfer Learning for Improving Model Predictions in Highly Configurable Software

Modern software systems are built to be used in dynamic environments using configuration capabilities to adapt to changes and external uncertainties. In a self-adaptation context, we are often interested in reasoning about the performance of the systems under different configurations. Usually, we learn a black-box model based on real measurements to predict the performance of the system given a specific configuration. However, as modern systems become more complex, there are many configuration parameters that may interact and we end up learning an exponentially large configuration space. Naturally, this does not scale when relying on real measurements in the actual changing environment. We propose a different solution: Instead of taking the measurements from the real system, we learn the model using samples from other sources, such as simulators that approximate performance of the real system at low cost. We define a cost model that transform the traditional view of model learning into a multi-objective problem that not only takes into account model accuracy but also measurements effort as well. We evaluate our cost-aware transfer learning solution using real-world configurable software including (i) a robotic system, (ii) 3 different stream processing applications, and (iii) a NoSQL database system. The experimental results demonstrate that our approach can achieve (a) a high prediction accuracy, as well as (b) a high model reliability.Comment: To be published in the proceedings of the 12th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS'17

(Why) Is My Prompt Getting Worse? Rethinking Regression Testing for Evolving LLM APIs

Large Language Models (LLMs) are increasingly integrated into software applications. Downstream application developers often access LLMs through APIs provided as a service. However, LLM APIs are often updated silently and scheduled to be deprecated, forcing users to continuously adapt to evolving models. This can cause performance regression and affect prompt design choices, as evidenced by our case study on toxicity detection. Based on our case study, we emphasize the need for and re-examine the concept of regression testing for evolving LLM APIs. We argue that regression testing LLMs requires fundamental changes to traditional testing approaches, due to different correctness notions, prompting brittleness, and non-determinism in LLM APIs.Comment: conference versio

Reify Your Collection Queries for Modularity and Speed!

Modularity and efficiency are often contradicting requirements, such that programers have to trade one for the other. We analyze this dilemma in the context of programs operating on collections. Performance-critical code using collections need often to be hand-optimized, leading to non-modular, brittle, and redundant code. In principle, this dilemma could be avoided by automatic collection-specific optimizations, such as fusion of collection traversals, usage of indexing, or reordering of filters. Unfortunately, it is not obvious how to encode such optimizations in terms of ordinary collection APIs, because the program operating on the collections is not reified and hence cannot be analyzed. We propose SQuOpt, the Scala Query Optimizer--a deep embedding of the Scala collections API that allows such analyses and optimizations to be defined and executed within Scala, without relying on external tools or compiler extensions. SQuOpt provides the same "look and feel" (syntax and static typing guarantees) as the standard collections API. We evaluate SQuOpt by re-implementing several code analyses of the Findbugs tool using SQuOpt, show average speedups of 12x with a maximum of 12800x and hence demonstrate that SQuOpt can reconcile modularity and efficiency in real-world applications.Comment: 20 page

Systematische Untersuchung zur Steuerung der Morphologie in Polymer-Fulleren-Heteroübergangssolarzellen

Organic photovoltaics developed step by step and actually work out into a market-based competition to the well-established inorganic thin-film solar cells. The advantages of such polymer solar cells are flexibility, low weight, semi-transparency and comparably high production speed. The combination of these advantages currently outperforms other technologies in its entirety. Furthermore, the rather low power conversion efficiency of organic solar cells can be increased by progressive materials development and optimization of processing and compares to the performance of other inorganic thin-film photovoltaic solar cells. Self-assembly (phase separation and aggregation/crystallization) of the employed photoactive materials, before, during and after deposition of photoactive thin films from a common solution, plays a significant role for the power conversion efficiency. Thus the morphology of the photoactive layer is of fundamental importance for the generation and transport of free charge carriers and also for power losses due to recombination, if charge separation and transport are hindered. It is already known that the phase separation into pristine polymer phases for hole transport and pristine fullerene phases for electron transport is just as important as the formation of a homogeneously mixed phase for free charge carrier generation. Ideally the transport phases are aggregated/crystalline and the homogeneously mixed phase is amorphous. This leads to an energetically favorable organization of the material phases, finally resulting in an improved generation and disproved recombination of free charge carriers.In the present work these influences, phase separation and aggregation of materials, are studied. In particular, the influence of structural order of the pristine polymer phase on the photovoltaic properties of solar cells is in the focus of research. By targeted utilization of the materials properties of the applied polymers, phase separation and aggregation could be controlled precisely and thus the relation between morphology and solar cell parameters could be investigated in detail. It is demonstrated how the morphology in polymer-fullerene heterojunction solar cells can be selectively manipulated by the derivatization of the fullerene, the solution concentration, the polymer:fullerene blend ratio and the polymer: polymer blend ratio in a ternary mixture with the fullerene. Fine-scaled parameter variations lead to very systematic variations of the morphology. This allowed a controlled and optimized proportioning of a three-phase system of aggregated polymer phases and aggregated fullerene phases for charge transport, as well as a homogeneously mixed polymer:fullerene phase for free charge carrier generation. Qualitative and quantitative analysis of the structural order in the polymeric phase and the phase separation of the polymer from the fullerene derivative enabled deeper insights into the bulk morphology. Particularly absorption, photo- and electroluminescence spectroscopy have proven their ease as reliable methods for analysis of structural order. Additionally, X-ray scattering (GiWAXS) and AFM measurements were performed to resemble the three-dimensional bulk morphology. It is originally demonstrated for the first time how electroluminescence spectroscopy allows deeper insight into the nano-morphology at the interface between the polymer and fullerene domains in contact with disordered polymer:fullerene mixed domains. In combination with the measurement of current-voltage characteristics (IV) and external quantum efficiency (EQE), the influence of morphology on the solar cell characteristics is demonstrated. Furthermore, the presented hypothetical optimal morphology of well-dimensioned pristine phases for charge transport and disordered homogeneous mixed phases for free charge generation and barrier for recombination is proven. The combined approach for morphology description is unique and allows for simple and rapid analysis of the active layer morphology, comparable to GiWAXS measurements. To conclude, this work presents fundamental insights into the relationship between structural properties of the photoactive layer and the solar cell functionality.Solarzellen kann durch die fortschreitende Materialentwicklung und Optimierung der Prozessierungsmethoden mit der Effizienz etablierter anorganischer Dünnschichtphotovoltaik konkurrieren. Die Selbstorganisation, d.h. Phasenseparation und Aggregation/Kristallisation der eingesetzten photoaktiven Materialien, vor, während und nach der Abscheidung zu photovoltaisch aktiven dünnen Schichten aus der gemeinsamen Lösung, spielt bei der Leistungsoptimierung eine wesentliche Rolle. Die somit ausgebildete Morphologie der photoaktiven Schicht ist von fundamentaler Bedeutung für die Generation von freien Ladungsträgern und deren Transport und folglich auch für Leistungsverluste durch Rekombination, sofern Ladungsträgertrennung und Transport nicht effektiv stattfinden können. Es ist bekannt, dass die Phasenseparation in reine Polymerphasen für den Transport der Löcher sowie reine Fullerenphasen für den Transport der Elektronen ebenso von Bedeutung ist wie die Ausbildung einer homogenen Mischphase für die Erzeugung der freien Ladungsträger. Idealerweise liegen die Transportphasen aggregiert/kristallin und die Mischphase amorph vor. Dann ergibt sich eine energetisch sinnvolle Organisation der Materialphasen, sodass die Generation freier Ladungsträger maximiert und deren Rekombination minimiert wird.In der vorliegenden Arbeit werden genau diese morphologischen Einflüsse, Phasenseparation und Aggregation der Materialien, untersucht. Insbesondere der Einfluss der strukturellen Ordnung der reinen Polymerphase auf die photovoltaischen Eigenschaften der Solarzelle steht hier im Vordergrund. Durch die gezielte Ausnutzung der Materialeigenschaften der eingesetzten Polymere konnten gezielt und kontrolliert Phasenseparation und Aggregation gesteuert und deren Einfluss auf die Solarzellparameter untersucht werden. Es wird gezeigt, wie die Morphologie von Polymer-Fulleren-Heteroübergangssolarzellen im Detail durch die Fullerenderivatisierung, die Lösungskonzentration und das Polymer:Fulleren-Mischungsverhältnis ebenso wie das Polymer:Polymer-Mischungsverhältnis in einer ternären Mischung mit dem Fulleren gezielt manipuliert werden kann. Mittels feinskalierter Parametervariationen konnten sehr systematische Variationen in der Morphologie induziert werden. Dies ermöglichte eine gezielte, optimierte Proportionierung eines Dreiphasensystems aus getrennt aggregierten Polymer- und Fullerenphasen für den Ladungstransport sowie einer homogenen Polymer:Fulleren-Mischphase zur freien Ladungsträgergeneration. Die vorgestellten Methoden zur qualitativen und quantitativen Beschreibung der polymeren Ordnung sowie der Phasenseparation des Polymers vom Fullerenderivat ermöglichen tiefere Einblicke in die Volumenmorphologie. Die quantitative Analyse von Absorptions-, Photo- und Elektrolumineszenzspektren hat sich hier als besonders einfach zu handhabende Methode erwiesen. Mit der Unterstützung von Röntgenbeugung (GiWAXS) und AFM-Messungen ist es möglich, eine sehr genaue Vorstellung von der dreidimensionalen Schichtmorphologie zu erhalten. Insbesondere die Elektrolumineszenzspektroskopie ermöglichte erstmalig einen tieferen Einblick in die Nanomorphologie an den Grenzflächen zwischen geordneten Polymer- und Fullerendomänen sowie ungeordneten Polymer:Fulleren-Mischphasen. Die Einflüsse der Morphologie auf die Solarzelleigenschaften konnten letztendlich in Verbindung mit der Messung der Strom-Spannungs-Kennlinien (I-V) und der externen Quanteneffizienz (EQE) abgeleitet werden. Damit konnte das vorgestellte Bild der hypothetisch optimalen Morphologie bestehend aus wohldimensionierten reinen geordneten Ladungstransportphasen sowie ungeordneten homogenen Mischphasen als Rekombinationsbarriere und Generationsschicht für freie Ladungsträger nachgewiesen werden. Der vorgestellte kombinierte Ansatz zur Morphologiebeschreibung ist bislang einzigartig und ermöglicht, abgesehen von den GiWAXS-Messungen, in Zukunft eine einfache und schnelle Analyse der Aktivschichtmorphologie. Darüber hinaus wird in dieser Arbeit ein tieferes Verständnis der Beziehung zwischen den Struktureigenschaften der photoaktiven Schicht und der Solarzellfunktion entwickelt

Integrating the common variability language with multilanguage annotations for web engineering

Web applications development involves managing a high diversity of files and resources like code, pages or style sheets, implemented in different languages. To deal with the automatic generation of custom-made configurations of web applications, industry usually adopts annotation-based approaches even though the majority of studies encourage the use of composition-based approaches to implement Software Product Lines. Recent work tries to combine both approaches to get the complementary benefits. However, technological companies are reticent to adopt new development paradigms such as feature-oriented programming or aspect-oriented programming. Moreover, it is extremely difficult, or even impossible, to apply these programming models to web applications, mainly because of their multilingual nature, since their development involves multiple types of source code (Java, Groovy, JavaScript), templates (HTML, Markdown, XML), style sheet files (CSS and its variants, such as SCSS), and other files (JSON, YML, shell scripts). We propose to use the Common Variability Language as a composition-based approach and integrate annotations to manage fine grained variability of a Software Product Line for web applications. In this paper, we (i) show that existing composition and annotation-based approaches, including some well-known combinations, are not appropriate to model and implement the variability of web applications; and (ii) present a combined approach that effectively integrates annotations into a composition-based approach for web applications. We implement our approach and show its applicability with an industrial real-world system.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech