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Variance theories quantify the variance that one or more independent variables cause in a dependent variable. In software engineering (SE), variance theories are used to quantify -- among others -- the impact of tools, techniques, and other treatments on software development outcomes. To acquire variance theories, evidence from individual empirical studies needs to be synthesized to more generally valid conclusions. However, research synthesis in SE is mostly limited to meta-analysis, which requires homogeneity of the synthesized studies to infer generalizable variance. In this paper, we aim to extend the practice of research synthesis beyond meta-analysis. To this end, we derive a conceptual framework for the evolution of variance theories and demonstrate its use by applying it to an active research field in SE. The resulting framework allows researchers to put new evidence in a clear relation to an existing body of knowledge and systematically expand the scientific frontier of a studied phenomenon.

The ubiquitous noise in quantum system hinders the advancement of quantum information processing and has driven the emergence of different hardware-efficient quantum error correction protocols. Among them, qubits with structured noise, especially with biased noise, are one of the most promising platform to achieve fault-tolerance due to the high error thresholds of quantum error correction codes tailored for them. Nevertheless, their quantum operations are challenging and the demonstration of their performance beyond the fault-tolerant threshold remain incomplete. Here, we leverage Schr\"odinger cat states in a scalable planar superconducting nonlinear oscillator to thoroughly characterize the high-fidelity single-qubit quantum operations with systematic quantum tomography and benchmarking tools, demonstrating the state-of-the-art performance of operations crossing the fault-tolerant threshold of the XZZX surface code. These results thus embody a transformative milestone in the exploration of quantum systems with structured error channels. Notably, our framework is extensible to other types of structured-noise systems, paving the way for systematic characterization and validation of novel quantum platforms with structured noise., Comment: 19 pages, 12 figures

Dissipative tunneling remains a cornerstone effect in quantum mechanics. In chemistry, it plays a crucial role in governing the rates of chemical reactions, often modeled as the motion along the reaction coordinate from one potential well to another. The relative positions of energy levels in these wells strongly influence the reaction dynamics. Chemical research will benefit from a fully adjustable, asymmetric double-well equipped with precise measurement capabilities of the tunneling rates. In this paper, we show a quantum simulator system that consists of a continuously driven Kerr parametric oscillator with a third order non-linearity that can be operated in the quantum regime to create a fully tunable asymmetric double-well. Our experiment leverages a low-noise, all-microwave control system with a high-efficiency readout, based on a tunnel Josephson junction circuit, of the which-well information. We explore the reaction rates across the landscape of tunneling resonances in parameter space. We uncover two new and counter-intuitive effects: (i) a weak asymmetry can significantly decrease the activation rates, even though the well in which the system is initialized is made shallower, and (ii) the width of the tunneling resonances alternates between narrow and broad lines as a function of the well depth and asymmetry. We predict by numerical simulations that both effects will also manifest themselves in ordinary chemical double-well systems in the quantum regime. Our work is a first step for the development of analog molecule simulators of proton transfer reactions based on quantum superconducting circuits., Comment: Edited some of the text and figures for clarity and corrected typos

Quantum computing holds the promise of solving classically intractable problems. Enabling this requires scalable and hardware-efficient quantum processors with vanishing error rates. This perspective manuscript describes how bosonic codes, particularly grid state encodings, offer a pathway to scalable fault-tolerant quantum computing in superconducting circuits. By leveraging the large Hilbert space of bosonic modes, quantum error correction can operate at the single physical unit level, therefore reducing drastically the hardware requirements to bring fault-tolerant quantum computing to scale. Going beyond the well-known Gottesman-Kitaev-Preskill (GKP) code, we discuss how using multiple bosonic modes to encode a single qubit offers increased protection against control errors and enhances its overall error-correcting capabilities. Given recent successful demonstrations of critical components of this architecture, we argue that it offers the shortest path to achieving fault tolerance in gate-based quantum computing processors with a MHz logical clock rate., Comment: This is a perspective paper presenting Nord Quantique's vision towards hardware-efficient FTQC

Experimentation is an essential method for causal inference in any empirical discipline. Crossover-design experiments are common in Software Engineering (SE) research. In these, subjects apply more than one treatment in different orders. This design increases the amount of obtained data and deals with subject variability but introduces threats to internal validity like the learning and carryover effect. Vegas et al. reviewed the state of practice for crossover designs in SE research and provided guidelines on how to address its threats during data analysis while still harnessing its benefits. In this paper, we reflect on the impact of these guidelines and review the state of analysis of crossover design experiments in SE publications between 2015 and March 2024. To this end, by conducting a forward snowballing of the guidelines, we survey 136 publications reporting 67 crossover-design experiments and evaluate their data analysis against the provided guidelines. The results show that the validity of data analyses has improved compared to the original state of analysis. Still, despite the explicit guidelines, only 29.5% of all threats to validity were addressed properly. While the maturation and the optimal sequence threats are properly addressed in 35.8% and 38.8% of all studies in our sample respectively, the carryover threat is only modeled in about 3% of the observed cases. The lack of adherence to the analysis guidelines threatens the validity of the conclusions drawn from crossover design experiments

Bosonic codes offer a hardware-efficient strategy for quantum error correction by redundantly encoding quantum information in the large Hilbert space of a harmonic oscillator. However, experimental realizations of these codes are often limited by ancilla errors propagating to the encoded logical qubit during syndrome measurements. The Kerr-cat qubit has been proposed as an ancilla for these codes due to its theoretically-exponential noise bias, which would enable fault-tolerant error syndrome measurements, but the coupling required to perform these syndrome measurements has not yet been demonstrated. In this work, we experimentally realize driven parametric coupling of a Kerr-cat qubit to a high-quality-factor microwave cavity and demonstrate a gate set enabling universal quantum control of the cavity. We measure the decoherence of the cavity in the presence of the Kerr-cat and discover excess dephasing due to heating of the Kerr-cat to excited states. By engineering frequency-selective dissipation to counteract this heating, we are able to eliminate this dephasing, thereby demonstrating a high on-off ratio of control. Our results pave the way toward using the Kerr-cat to fault-tolerantly measure error syndromes of bosonic codes.

Requirements quality research, which is dedicated to assessing and improving the quality of requirements specifications, is dependent on research artifacts like data sets (containing information about quality defects) and implementations (automatically detecting and removing these defects). However, recent research exposed that the majority of these research artifacts have become unavailable or have never been disclosed, which inhibits progress in the research domain. In this work, we aim to improve the availability of research artifacts in requirements quality research. To this end, we (1) extend an artifact recovery initiative, (2) empirically evaluate the reasons for artifact unavailability using Bayesian data analysis, and (3) compile a concise guideline for open science artifact disclosure. Our results include 10 recovered data sets and 7 recovered implementations, empirical support for artifact availability improving over time and the positive effect of public hosting services, and a pragmatic artifact management guideline open for community comments. With this work, we hope to encourage and support adherence to open science principles and improve the availability of research artifacts for the requirements research quality community.

Requirements engineering aims to fulfill a purpose, i.e., inform subsequent software development activities about stakeholders' needs and constraints that must be met by the system under development. The quality of requirements artifacts and processes is determined by how fit for this purpose they are, i.e., how they impact activities affected by them. However, research on requirements quality lacks a comprehensive overview of these activities and how to measure them. In this paper, we specify the research endeavor addressing this gap and propose an initial model of requirements-affected activities and their attributes. We construct a model from three distinct data sources, including both literature and empirical data. The results yield an initial model containing 24 activities and 16 attributes quantifying these activities. Our long-term goal is to develop evidence-based decision support on how to optimize the fitness for purpose of the RE phase to best support the subsequent, affected software development process. We do so by measuring the effect that requirements artifacts and processes have on the attributes of these activities. With the contribution at hand, we invite the research community to critically discuss our research roadmap and support the further evolution of the model.

The Kerr-cat qubit is a bosonic qubit in which multi-photon Schrodinger cat states are stabilized by applying a two-photon drive to an oscillator with a Kerr nonlinearity. The suppressed bit-flip rate with increasing cat size makes this qubit a promising candidate to implement quantum error correction codes tailored for noise-biased qubits. However, achieving strong light-matter interactions necessary for stabilizing and controlling this qubit has traditionally required strong microwave drives that heat the qubit and degrade its performance. In contrast, increasing the coupling to the drive port removes the need for strong drives at the expense of large Purcell decay. By integrating an effective band-block filter on-chip, we overcome this trade-off and realize a Kerr-cat qubit in a scalable 2D superconducting circuit with high coherence. This filter provides 30 dB of isolation at the qubit frequency with negligible attenuation at the frequencies required for stabilization and readout. We experimentally demonstrate quantum non-demolition readout fidelity of 99.6% for a cat with 8 photons. Also, to have high-fidelity universal control over this qubit, we combine fast Rabi oscillations with a new demonstration of the X(90) gate through phase modulation of the stabilization drive. Finally, the lifetime in this architecture is examined as a function of the cat size of up to 10 photons in the oscillator achieving a bit-flip time higher than 1 ms and only a linear decrease in the phase-flip time, in good agreement with the theoretical analysis of the circuit. Our qubit shows promise as a building block for fault-tolerant quantum processors with a small footprint.

Tools constitute an essential contribution to natural language processing for requirements engineering (NLP4RE) research. They are executable instruments that make research usable and applicable in practice. In this chapter, we first introduce a systematic classification of NLP4RE tools to improve the understanding of their types and properties. Then, we extend an existing overview with a systematic summary of 126 NLP4RE tools published between April 2019 and June 2023 to ease reuse and evolution of existing tools. Finally, we provide instructions on how to create, maintain, and disseminate NLP4RE tools to support a more rigorous management and dissemination., Comment: The final version of the chapter will eventually appear in a book titled "Natural Language Processing for Requirements Engineering", edited by Alessio Ferrari and Gouri Ginde and published by Springer Nature Group

The quality of requirements specifications may impact subsequent, dependent software engineering (SE) activities. However, empirical evidence of this impact remains scarce and too often superficial as studies abstract from the phenomena under investigation too much. Two of these abstractions are caused by the lack of frameworks for causal inference and frequentist methods which reduce complex data to binary results. In this study, we aim to demonstrate (1) the use of a causal framework and (2) contrast frequentist methods with more sophisticated Bayesian statistics for causal inference. To this end, we reanalyze the only known controlled experiment investigating the impact of passive voice on the subsequent activity of domain modeling. We follow a framework for statistical causal inference and employ Bayesian data analysis methods to re-investigate the hypotheses of the original study. Our results reveal that the effects observed by the original authors turned out to be much less significant than previously assumed. This study supports the recent call to action in SE research to adopt Bayesian data analysis, including causal frameworks and Bayesian statistics, for more sophisticated causal inference., Comment: Published at the first International Workshop on Methodological Issues with Empirical Studies in Software Engineering (WSESE '24)

[Context and Motivation]: The quality of requirements specifications impacts subsequent, dependent software engineering activities. Requirements quality defects like ambiguous statements can result in incomplete or wrong features and even lead to budget overrun or project failure. [Problem]: Attempts at measuring the impact of requirements quality have been held back by the vast amount of interacting factors. Requirements quality research lacks an understanding of which factors are relevant in practice. [Principal Ideas and Results]: We conduct a case study considering data from both interview transcripts and issue reports to identify relevant factors of requirements quality. The results include 17 factors and 11 interaction effects relevant to the case company. [Contribution]: The results contribute empirical evidence that (1) strengthens existing requirements engineering theories and (2) advances industry-relevant requirements quality research., Comment: This preprint has not undergone peer review or any post-submission improvements or corrections. The Version of Record of this contribution is published in "Requirements Engineering: Foundation for Software Quality" (https://doi.org/10.1007/978-3-031-57327-9), and is available online at https://doi.org/10.1007/978-3-031-57327-9_2

It is commonly accepted that the quality of requirements specifications impacts subsequent software engineering activities. However, we still lack empirical evidence to support organizations in deciding whether their requirements are good enough or impede subsequent activities. We aim to contribute empirical evidence to the effect that requirements quality defects have on a software engineering activity that depends on this requirement. We conduct a controlled experiment in which 25 participants from industry and university generate domain models from four natural language requirements containing different quality defects. We evaluate the resulting models using both frequentist and Bayesian data analysis. Contrary to our expectations, our results show that the use of passive voice only has a minor impact on the resulting domain models. The use of ambiguous pronouns, however, shows a strong effect on various properties of the resulting domain models. Most notably, ambiguous pronouns lead to incorrect associations in domain models. Despite being equally advised against by literature and frequentist methods, the Bayesian data analysis shows that the two investigated quality defects have vastly different impacts on software engineering activities and, hence, deserve different levels of attention. Our employed method can be further utilized by researchers to improve reliable, detailed empirical evidence on requirements quality.

The dielectric loss of silicon nitride (Si$_3$N$_4$) limits the performance of microwave-frequency devices that rely on this material for sensing, signal processing, and quantum communication. Using superconducting resonant circuits, we measure the cryogenic loss tangent of either as-deposited or high-temperature annealed stoichiometric Si$_3$N$_4$ as a function of drive strength and temperature. The internal loss behavior of the electrical resonators is largely consistent with the standard tunneling model of two-level systems (TLS), including damping caused by resonant energy exchange with TLS and by the relaxation of non-resonant TLS. We further supplement the TLS model with a self-heating effect to explain an increase in the loss observed in as-deposited films at large drive powers. Critically, we demonstrate that annealing remedies this anomalous power-induced loss, reduces the relaxation-type damping by more than two orders of magnitude, and reduces the resonant-type damping by a factor of three. Employing infrared absorption spectroscopy, we find that annealing reduces the concentration of hydrogen in the Si$_3$N$_4$, suggesting that hydrogen impurities cause substantial dissipation., Comment: 11 pages, 7 figures

Background: The detection and extraction of causality from natural language sentences have shown great potential in various fields of application. The field of requirements engineering is eligible for multiple reasons: (1) requirements artifacts are primarily written in natural language, (2) causal sentences convey essential context about the subject of requirements, and (3) extracted and formalized causality relations are usable for a (semi-)automatic translation into further artifacts, such as test cases. Objective: We aim at understanding the value of interactive causality extraction based on syntactic criteria for the context of requirements engineering. Method: We developed a prototype of a system for automatic causality extraction and evaluate it by applying it to a set of publicly available requirements artifacts, determining whether the automatic extraction reduces the manual effort of requirements formalization. Result: During the evaluation we analyzed 4457 natural language sentences from 18 requirements documents, 558 of which were causal (12.52%). The best evaluation of a requirements document provided an automatic extraction of 48.57% cause-effect graphs on average, which demonstrates the feasibility of the approach. Limitation: The feasibility of the approach has been proven in theory but lacks exploration of being scaled up for practical use. Evaluating the applicability of the automatic causality extraction for a requirements engineer is left for future research. Conclusion: A syntactic approach for causality extraction is viable for the context of requirements engineering and can aid a pipeline towards an automatic generation of further artifacts from requirements artifacts., Comment: ASE '20: Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering

MolecularWebXR is our new website for education, science communication and scientific peer discussion in chemistry and biology built on WebXR. It democratizes multi-user, inclusive virtual reality (VR) experiences that are deeply immersive for users wearing high-end headsets, yet allow participation by users with consumer devices such as smartphones, possibly inserted into cardboard goggles for immersivity, or even computers or tablets. With no installs as it is all web-served, MolecularWebXR enables multiple users to simultaneously explore, communicate and discuss chemistry and biology concepts in immersive 3D environments, manipulating objects with their bare hands, either present in the same real space or scattered throughout the globe thanks to built-in audio features. A series of preset rooms cover educational material on chemistry and structural biology, and an empty room can be populated with material prepared ad hoc using moleculARweb's VMD-based PDB2AR tool. We verified ease of use and versatility by users aged 12-80 in entirely virtual sessions or mixed real-virtual sessions at science outreach events, student instruction, scientific collaborations, and conference lectures. MolecularWebXR is available for free use without registration at https://molecularwebxr.org, and a blog post version of this preprint with embedded videos is available at https://go.epfl.ch/molecularwebxr-blog-post., Comment: 13 pages, 3 figures

The Gottesman-Kitaev-Preskill (GKP) code encodes a logical qubit into a bosonic system with resilience against single-photon loss, the predominant error in most bosonic systems. Here we present experimental results demonstrating quantum error correction of GKP states based on reservoir engineering of a superconducting device. Error correction is made autonomous through an unconditional reset of an auxiliary transmon qubit. The lifetime of the logical qubit is shown to be increased from quantum error correction, therefore reaching the point at which more errors are corrected than generated., Comment: 6 pages, 3 figures + 26 pages, 12 figures

Deriving acceptance tests from high-level, natural language requirements that achieve full coverage is a major manual challenge at the interface between requirements engineering and testing. Conditional requirements (e.g., "If A or B then C.") imply causal relationships which - when extracted - allow to generate these acceptance tests automatically. This paper presents a tool from the CiRA (Causality In Requirements Artifacts) initiative, which automatically processes conditional natural language requirements and generates a minimal set of test case descriptions achieving full coverage. We evaluate the tool on a publicly available data set of 61 requirements from the requirements specification of the German Corona-Warn-App. The tool infers the correct test variables in 84.5% and correct variable configurations in 92.3% of all cases, which corroborates the feasibility of our approach., Comment: Tenth International Workshop on Artificial Intelligence and Requirements Engineering

High-quality requirements minimize the risk of propagating defects to later stages of the software development life cycle. Achieving a sufficient level of quality is a major goal of requirements engineering. This requires a clear definition and understanding of requirements quality. Though recent publications make an effort at disentangling the complex concept of quality, the requirements quality research community lacks identity and clear structure which guides advances and puts new findings into an holistic perspective. In this research commentary we contribute (1) a harmonized requirements quality theory organizing its core concepts, (2) an evaluation of the current state of requirements quality research, and (3) a research roadmap to guide advancements in the field. We show that requirements quality research focuses on normative rules and mostly fails to connect requirements quality to its impact on subsequent software development activities, impeding the relevance of the research. Adherence to the proposed requirements quality theory and following the outlined roadmap will be a step towards amending this gap., Comment: Requirements Eng (2023)

Noiseless measurement of a single quadrature in systems of parametrically coupled oscillators is theoretically possible by pumping at the sum and difference frequencies of the two oscillators, realizing a backaction-evading (BAE) scheme. Although this would hold true in the simplest scenario for a system with pure three-wave mixing, implementations of this scheme are hindered by unwanted higher-order parametric processes that destabilize the system and add noise. We show analytically that detuning the two pumps from the sum and difference frequencies can stabilize the system and fully recover the BAE performance, enabling operation at otherwise inaccessible cooperativities. We also show that the acceleration demonstrated in a weak signal detection experiment [PRX QUANTUM 4, 020302 (2023)] was only achievable because of this detuning technique., Comment: 9 pages, 3 figures

We present a way to achieve fully directional, quantum-limited phase-preserving amplification in a four-port, four-mode superconducting Josephson circuit by utilizing interference between six parametric processes that couple all four modes. Full directionality, defined as the reverse isolation surpassing forward gain between the matched input and output ports of the amplifier, ensures its robustness against impedance mismatch that might be present at its output port during applications. Unlike existing directional phase-preserving amplifiers, both the minimal back-action and the quantum-limited added noise of this amplifier remains unaffected by noise incident on its output port. In addition, the matched input and output ports allow direct on-chip integration of these amplifiers with other circuit QED components, facilitating scaling up of superconducting quantum processors.

Requirements quality literature abounds with publications presenting artifacts, such as data sets and tools. However, recent systematic studies show that more than 80% of these artifacts have become unavailable or were never made public, limiting reproducibility and reusability. In this work, we report on an attempt to recover those artifacts. To that end, we requested corresponding authors of unavailable artifacts to recover and disclose them according to open science principles. Our results, based on 19 answers from 35 authors (54% response rate), include an assessment of the availability of requirements quality artifacts and a breakdown of authors' reasons for their continued unavailability. Overall, we improved the availability of seven data sets and seven implementations.

Context: Sustainable corporate behavior is increasingly valued by society and impacts corporate reputation and customer trust. Hence, companies regularly publish sustainability reports to shed light on their impact on environmental, social, and governance (ESG) factors. Problem: Sustainability reports are written by companies themselves and are therefore considered a company-controlled source. Contrary, studies reveal that non-corporate channels (e.g., media coverage) represent the main driver for ESG transparency. However, analysing media coverage regarding ESG factors is challenging since (1) the amount of published news articles grows daily, (2) media coverage data does not necessarily deal with an ESG-relevant topic, meaning that it must be carefully filtered, and (3) the majority of media coverage data is unstructured. Research Goal: We aim to extract ESG-relevant information from textual media reactions automatically to calculate an ESG score for a given company. Our goal is to reduce the cost of ESG data collection and make ESG information available to the general public. Contribution: Our contributions are three-fold: First, we publish a corpus of 432,411 news headlines annotated as being environmental-, governance-, social-related, or ESG-irrelevant. Second, we present our tool-supported approach called ESG-Miner capable of analyzing and evaluating headlines on corporate ESG-performance automatically. Third, we demonstrate the feasibility of our approach in an experiment and apply the ESG-Miner on 3000 manually labeled headlines. Our approach processes 96.7 % of the headlines correctly and shows a great performance in detecting environmental-related headlines along with their correct sentiment. We encourage fellow researchers and practitioners to use the ESG-Miner at https://www.esg-miner.com.

Quantum fluctuations constitute the primary noise barrier limiting cavity-based axion dark matter searches. In an experiment designed to mimic a real axion search, we employ a quantum-enhanced sensing technique to detect a synthetic axion-like microwave tone at an unknown frequency weakly coupled to a resonator, demonstrating a factor of 5.6 acceleration relative to a quantum-limited search for the same tone. The acceleration comes from increases to both the visibility bandwidth and the peak visibility of a detector. This speedup is achieved by dynamically coupling the resonator mode to a second (readout) mode with balanced swapping and two-mode squeezing interactions. A small fractional imbalance between the two interaction rates yields further scan rate enhancement and we demonstrate that an 8-fold acceleration can be achieved., Comment: 9 pages, 5 figures

Context: Advances in technical debt research demonstrate the benefits of applying the financial debt metaphor to support decision-making in software development activities. Although decision-making during requirements engineering has significant consequences, the debt metaphor in requirements engineering is inadequately explored. Objective: We aim to conceptualize how the debt metaphor applies to requirements engineering by organizing concepts related to practitioners' understanding and managing of requirements engineering debt (RED). Method: We conducted two in-depth expert interviews to identify key requirements engineering debt concepts and construct a survey instrument. We surveyed 69 practitioners worldwide regarding their perception of the concepts and developed an initial analytical theory. Results: We propose a RED theory that aligns key concepts from technical debt research but emphasizes the specific nature of requirements engineering. In particular, the theory consists of 23 falsifiable propositions derived from the literature, the interviews, and survey results. Conclusions: The concepts of requirements engineering debt are perceived to be similar to their technical debt counterpart. Nevertheless, measuring and tracking requirements engineering debt are immature in practice. Our proposed theory serves as the first guide toward further research in this area., Comment: Revised manuscript based on reviews

We present the experimental discovery of multiple simultaneous degeneracies in the spectrum of a Kerr oscillator subjected to a squeezing drive. This squeezing, in combination with the Kerr interaction creates an effective static two-well potential in the frame rotating at half the frequency of the sinusoidal driving force. Remarkably, these degeneracies can be turned on-and-off on demand, and their number is tunable. We find that when the detuning $\Delta$ between the frequency of the oscillator and characteristic frequency of the drive equals an even multiple of the Kerr coefficient $K$, $\Delta/K = 2m$, the oscillator displays $m + 1$ exact, parity-protected, spectral degeneracies, insensitive to the drive amplitude. The degeneracies stem from the unusual destructive interference of tunnel paths in the classically forbidden region of the double well static effective potential that models our experiment. Exploiting this interference, we measure a peaked enhancement of the incoherent well-switching lifetime creating a super-protected cat qubit in the ground state manifold of our oscillator. {Our results demonstrate the relationship between degeneracies and noise protection in quantum systems.