Machine Learning for Software Engineering: Models, Methods, and Applications

Machine Learning (ML) is the discipline that studies methods for automatically inferring models from data. Machine learning has been successfully applied in many areas of software engineering ranging from behaviour extraction, to testing, to bug fixing. Many more applications are yet be defined. However, a better understanding of ML methods, their assumptions and guarantees would help software engineers adopt and identify the appropriate methods for their desired applications. We argue that this choice can be guided by the models one seeks to infer. In this technical briefing, we review and reflect on the applications of ML for software engineering organised according to the models they produce and the methods they use. We introduce the principles of ML, give an overview of some key methods, and present examples of areas of software engineering benefiting from ML. We also discuss the open challenges for reaching the full potential of ML for software engineering and how ML can benefit from software engineering methods

Noninvasive Determination of Epidermal and Stratum Corneum Thickness in vivo Using Two-Photon Microscopy and Optical Coherence Tomography: Impact of Body Area, Age, and Gender

Background: High-resolution images of the epidermis are important to understand the transdermal penetration and changes in epidermal components. Both ex vivo and in vivo technologies are available to picture the epidermal thickness (ET). So far, the illustration of the stratum corneum (SC) has not been possible without artifacts. Objective: Precision in vivo measurement of the ET and SC, duly considering the impact of location on the body, age, and gender. Methods: In this pilot study on 20 skin-healthy subjects aged 18-66 years, the ET was imaged by two-photon microscopy (2PM) and optical coherence tomography (OCT), and the SC by using 2PM at five different body sites. Results: On solar-exposed body areas, both the epidermis and SC are thicker compared to solar-protected areas (p < 0.05), the epidermis at the gluteal region being the thickest (p < 0.05). The ET decreases with age (p < 0.05). Males show a thicker epidermis than females (p < 0.05). Conclusion: 2PM provides a noninvasive method for imaging the epidermis and especially the SC in vivo and is optimally suited for the application of histological criteria

Testing abstract behavioral specifications

We present a range of testing techniques for the Abstract Behavioral Specification (ABS) language and apply them to an industrial case study. ABS is a formal modeling language for highly variable, concurrent, component-based systems. The nature of these systems makes them susceptible to the introduction of subtle bugs that are hard to detect in the presence of steady adaptation. While static analysis techniques are available for an abstract language such as ABS, testing is still indispensable and complements analytic methods. We focus on fully automated testing techniques including blackbox and glassbox test generation as well as runtime assertion checking, which are shown to be effective in an industrial setting

Grip strength values and cut-off points based on over 200,000 adults of the German National Cohort - a comparison to the EWGSOP2 cut-off points

BACKGROUND: The European Working Group on Sarcopenia in Older People (EWGSOP) updated in 2018 the cut-off points for low grip strength to assess sarcopenia based on pooled data from 12 British studies. OBJECTIVE: Comparison of the EWGSOP2 cut-off points for low grip strength to those derived from a large German sample. METHODS: We assessed the grip strength distribution across age and derived low grip strength cut-off points for men and women (peak mean -2.5 × SD) based on 200,389 German National Cohort (NAKO) participants aged 19–75 years. In 1,012 Cooperative Health Research in the Region of Augsburg (KORA)-Age participants aged 65–93 years, we calculated the age-standardised prevalence of low grip strength and time-dependent sensitivity and specificity for all-cause mortality. RESULTS: Grip strength increased in the third and fourth decade of life and declined afterwards. Calculated cut-off points for low grip strength were 29 kg for men and 18 kg for women. In KORA-Age, the age-standardised prevalence of low grip strength was 1.5× higher for NAKO-derived (17.7%) compared to EWGSOP2 (11.7%) cut-off points. NAKO-derived cut-off points yielded a higher sensitivity and lower specificity for all-cause mortality. CONCLUSIONS: Cut-off points for low grip strength from German population-based data were 2 kg higher than the EWGSOP2 cut-off points. Higher cut-off points increase the sensitivity, thereby suggesting an intervention for more patients at risk, while other individuals might receive additional diagnostics/treatment without the urgent need. Research on the effectiveness of intervention in patients with low grip strength defined by different cut-off points is needed

Framework and baseline examination of the German National Cohort (NAKO)

The German National Cohort (NAKO) is a multidisciplinary, population-based prospective cohort study that aims to investigate the causes of widespread diseases, identify risk factors and improve early detection and prevention of disease. Specifically, NAKO is designed to identify novel and better characterize established risk and protection factors for the development of cardiovascular diseases, cancer, diabetes, neurodegenerative and psychiatric diseases, musculoskeletal diseases, respiratory and infectious diseases in a random sample of the general population. Between 2014 and 2019, a total of 205,415 men and women aged 19–74 years were recruited and examined in 18 study centres in Germany. The baseline assessment included a face-to-face interview, self-administered questionnaires and a wide range of biomedical examinations. Biomaterials were collected from all participants including serum, EDTA plasma, buffy coats, RNA and erythrocytes, urine, saliva, nasal swabs and stool. In 56,971 participants, an intensified examination programme was implemented. Whole-body 3T magnetic resonance imaging was performed in 30,861 participants on dedicated scanners. NAKO collects follow-up information on incident diseases through a combination of active follow-up using self-report via written questionnaires at 2–3 year intervals and passive follow-up via record linkages. All study participants are invited for re-examinations at the study centres in 4–5 year intervals. Thereby, longitudinal information on changes in risk factor profiles and in vascular, cardiac, metabolic, neurocognitive, pulmonary and sensory function is collected. NAKO is a major resource for population-based epidemiology to identify new and tailored strategies for early detection, prediction, prevention and treatment of major diseases for the next 30 years. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10654-022-00890-5

Die Basiserhebung der NAKO Gesundheitsstudie: Teilnahme an den Untersuchungsmodulen, Qualitätssicherung und Nutzung von Sekundärdaten

BACKGROUND: The German National Cohort (NAKO) is an interdisciplinary health study aimed at elucidating causes for common chronic diseases and detecting their preclinical stages. This article provides an overview of design, methods, participation in the examinations, and their quality assurance based on the midterm baseline dataset (MBD) of the recruitment. METHODS: More than 200,000 women and men aged 20–69 years derived from random samples of the German general population were recruited in 18 study centers (2014–2019). The data collection comprised physical examinations, standardized interviews and questionnaires, and the collection of biomedical samples for all participants (level 1). At least 20% of all participants received additional in-depth examinations (level 2), and 30,000 received whole-body magnet resonance imaging (MRI). Additional information will be collected through secondary data sources such as medical registries, health insurances, and pension funds. This overview is based on the MBD, which included 101,839 participants, of whom 11,371 received an MRI. RESULTS: The mean response proportion was 18%. The participation in the examinations was high with most of the modules performed by over 95%. Among MRI participants, 96% completed all 12 MRI sequences. More than 90% of the participants agreed to the use of complementary secondary and registry data. DISCUSSION: Individuals selected for the NAKO were willing to participate in all examinations despite the time-consuming program. The NAKO provides a central resource for population-based epidemiologic research and will contribute to developing innovative strategies for prevention, screening and prediction of chronic diseases.HINTERGRUND: Die NAKO Gesundheitsstudie ist ein bundesweites interdisziplinäres Forschungsvorhaben mit dem Ziel, die Ursachen für chronische Krankheiten und deren vorklinische Stadien zu untersuchen. Der Artikel gibt einen Überblick über das Studiendesign, die Methoden, die Teilnahme an den Untersuchungen und ihre Qualitätssicherung zur Halbzeit der Basiserhebung. METHODEN: Für die Basiserhebung wurden mehr als 200.000 Frauen und Männer im Alter von 20–69 Jahren aus Zufallsstichproben der Allgemeinbevölkerung in 18 Studienzentren rekrutiert (2014–2019). Die Basiserhebung beinhaltet Untersuchungen, Befragungen und Biomaterialien für alle Teilnehmerinnen und Teilnehmer (Level 1), ein erweitertes Programm für mindestens 20 % (Level 2) und eine Magnetresonanztomografie (MRT) für 30.000 Teilnehmerinnen und Teilnehmer. Sekundär- und Registerdaten werden über Krankheitsregister, Kranken- und Rentenversicherungen erhoben. Die Auswertung bezieht die Datenbasis zur Halbzeit der Basiserhebung mit 101.839 Teilnehmerinnen und Teilnehmern ein, davon 11.371 mit einer MRT-Untersuchung. ERGEBNISSE: Die mittlere Responsequote zur Halbzeit betrug insgesamt 18 %. Die Teilnahme an den Untersuchungen lag überwiegend bei mehr als 95 %. Bei 96 % der MRT-Teilnehmerinnen und Teilnehmer konnten alle 12 MRT-Sequenzen vollständig durchgeführt werden. Der Erschließung und wissenschaftlichen Nutzung ergänzender Sekundär- und Registerdaten stimmten mehr als 90 % der Teilnehmerinnen und Teilnehmer zu. DISKUSSION: Die Bereitschaft, möglichst alle Untersuchungsmodule durchzuführen, war trotz des zeitlichen Aufwandes außerordentlich hoch. Dadurch wird die NAKO zu einer zentralen Ressource für die epidemiologische Forschung in Deutschland. Sie wird es ermöglichen, neue Strategien zur Früherkennung, Vorhersage und Primärprävention chronischer Krankheiten zu entwickeln