Online experimentation in automotive software engineering

Context: Online experimentation has long been the gold standard for evaluating software towards the actual needs and preferences of customers. In the Software-as-a-Service domain, various online experimentation techniques are applied and proven successful. As software is becoming the main differentiator for automotive products, the automotive sector has started to express an interest in adopting online experimentation to strengthen their software development process. Objective: In this research, we aim to systematically address the challenges in adopting online experimentation in the automotive domain.Method: We apply a multidisciplinary approach to this research. To understand the state-of-practise in online experimentation in the industry, we conduct case studies with three manufacturers. We introduce our experimental design and evaluation methods to real vehicles driven by customers at scale. Moreover, we run experiments to quantitatively evaluate experiment design and causal inference models. Results: Four main research outcomes are presented in this thesis. First, we propose an architecture for continuous online experimentation given the limitations experienced in the automotive domain. Second, after identifying an inherent limitation of sample sizes in the automotive domain, we apply and evaluate an experimentation design method. The method allows us to utilise pre-experimental data for generating balanced groups even when sample sizes are limited. Third, we present an alternative approach to randomised experiments and demonstrate the application of Bayesian causal inference in online software evaluation. With the models, we enable software online evaluation without the need for a fully randomised experiment. Finally, we relate the formal assumption in the Bayesian causal models to the implications in practise, and we demonstrate the inference models with cases from the automotive domain. Outlook: In our future work, we plan to explore causal structural and graphical models applied in software engineering, and demonstrate the application of causal discovery in machine learning-based autonomous drive software

An architecture for enabling A/B experiments in automotive embedded software

A/B experimentation is a known technique for data-driven product development and has demonstrated its value in web-facing businesses. With the digitalisation of the automotive industry, the focus in the industry is shifting towards software. For automotive embedded software to continuously improve, A/B experimentation is considered an important technique. However, the adoption of such a technique is not without challenge. In this paper, we present an architecture to enable A/B testing in automotive embedded software. The design addresses challenges that are unique to the automotive industry in a systematic fashion. Going from hypothesis to practice, our architecture was also applied in practice for running online experiments on a considerable scale. Furthermore, a case study approach was used to compare our proposal with state-of-practice in the automotive industry. We found our architecture design to be relevant and applicable in the efforts of adopting continuous A/B experiments in automotive embedded software.Comment: To appear in the 45th Annual IEEE Conference on Computers, Software and Applications (COMPSAC'2021

DHX33 transcriptionally controls genes involved in the cell cycle

The RNA helicase DHX33 has been shown to be a critical regulator of cell proliferation and growth. However, the underlying mechanisms behind DHX33 function remain incompletely understood. We present original evidence in multiple cell lines that DHX33 transcriptionally controls the expression of genes involved in the cell cycle, notably cyclin, E2F1, cell division cycle (CDC), and minichromosome maintenance (MCM) genes. DHX33 physically associates with the promoters of these genes and controls the loading of active RNA polymerase II onto these promoters. DHX33 deficiency abrogates cell cycle progression and DNA replication and leads to cell apoptosis. In zebrafish, CRISPR-mediated knockout of DHX33 results in downregulation of cyclin A2, cyclin B2, cyclin D1, cyclin E2, cdc6, cdc20, E2F1, and MCM complexes in DHX33 knockout embryos. Additionally, we found the overexpression of DHX33 in a subset of non-small-cell lung cancers and in Ras-mutated human lung cancer cell lines. Forced reduction of DHX33 in these cancer cells abolished tumor formation in vivo. Our study demonstrates for the first time that DHX33 acts as a direct transcriptional regulator to promote cell cycle progression and plays an important role in driving cell proliferation during both embryo development and tumorigenesis

Selecting a semantic similarity measure for concepts in two different CAD model data ontologies

Semantic similarity measure technology based approach is one of the most popular approaches aiming at implementing semantic mapping between two different CAD model data ontologies. The most important problem in this approach is how to measure the semantic similarities of concepts between two different ontologies. A number of measure methods focusing on this problem have been presented in recent years. Each method can work well between its specific ontologies. But it is unclear how accurate the measured semantic similarities in these methods are. Moreover, there is yet no evidence that any of the methods presented how to select a measure with high similarity calculation accuracy. To compensate for such deficiencies, this paper proposes a method for selecting a semantic similarity measure with high similarity calculation accuracy for concepts in two different CAD model data ontologies. In this method, the similarity calculation accuracy of each candidate measure is quantified using Pearson correlation coefficient or residual sum of squares. The measure with high similarity calculation accuracy is selected through a comparison of the Pearson correlation coefficients or the residual sums of squares of all candidate measures. The paper also reports an implementation of the proposed method, provides an example to show how the method works, and evaluates the method by theoretical and experimental comparisons. The evaluation result suggests that the measure selected by the proposed method has good human correlation and high similarity calculation accuracy

Corticofugal Modulation of Initial Neural Processing of Sound Information from the Ipsilateral Ear in the Mouse

Background: Cortical neurons implement a high frequency-specific modulation of subcortical nuclei that includes the cochlear nucleus. Anatomical studies show that corticofugal fibers terminating in the auditory thalamus and midbrain are mostly ipsilateral. Differently, corticofugal fibers terminating in the cochlear nucleus are bilateral, which fits to the needs of binaural hearing that improves hearing quality. This leads to our hypothesis that corticofugal modulation of initial neural processing of sound information from the contralateral and ipsilateral ears could be equivalent or coordinated at the first sound processing level. Methodology/Principal Findings: With the focal electrical stimulation of the auditory cortex and single unit recording, this study examined corticofugal modulation of the ipsilateral cochlear nucleus. The same methods and procedures as described in our previous study of corticofugal modulation of contralateral cochlear nucleus were employed simply for comparison. We found that focal electrical stimulation of cortical neurons induced substantial changes in the response magnitude, response latency and receptive field of ipsilateral cochlear nucleus neurons. Cortical stimulation facilitated auditory response and shortened the response latency of physiologically matched neurons whereas it inhibited auditory response and lengthened the response latency of unmatched neurons. Finally, cortical stimulation shifted the best frequencies of cochlear neurons towards those of stimulated cortical neurons

The water lily genome and the early evolution of flowering plants

Water lilies belong to the angiosperm order Nymphaeales. Amborellales, Nymphaeales and Austrobaileyales together form the so-called ANA-grade of angiosperms, which are extant representatives of lineages that diverged the earliest from the lineage leading to the extant mesangiosperms1–3. Here we report the 409-megabase genome sequence of the blue-petal water lily (Nymphaea colorata). Our phylogenomic analyses support Amborellales and Nymphaeales as successive sister lineages to all other extant angiosperms. The N. colorata genome and 19 other water lily transcriptomes reveal a Nymphaealean whole-genome duplication event, which is shared by Nymphaeaceae and possibly Cabombaceae. Among the genes retained from this whole-genome duplication are homologues of genes that regulate flowering transition and flower development. The broad expression of homologues of floral ABCE genes in N. colorata might support a similarly broadly active ancestral ABCE model of floral organ determination in early angiosperms. Water lilies have evolved attractive floral scents and colours, which are features shared with mesangiosperms, and we identified their putative biosynthetic genes in N. colorata. The chemical compounds and biosynthetic genes behind floral scents suggest that they have evolved in parallel to those in mesangiosperms. Because of its unique phylogenetic position, the N. colorata genome sheds light on the early evolution of angiosperms.Supplementary Tables: This file contains Supplementary Tables 1-21.National Natural Science Foundation of China, the open funds of the State Key Laboratory of Crop Genetics and Germplasm Enhancement (ZW201909) and State Key Laboratory of Tree Genetics and Breeding, the Fujian provincial government in China, the European Union Seventh Framework Programme (FP7/2007-2013) under European Research Council Advanced Grant Agreement and the Special Research Fund of Ghent University.http://www.nature.com/naturecommunicationsam2021BiochemistryGeneticsMicrobiology and Plant Patholog