Predicting and Evaluating Software Model Growth in the Automotive Industry

The size of a software artifact influences the software quality and impacts the development process. In industry, when software size exceeds certain thresholds, memory errors accumulate and development tools might not be able to cope anymore, resulting in a lengthy program start up times, failing builds, or memory problems at unpredictable times. Thus, foreseeing critical growth in software modules meets a high demand in industrial practice. Predicting the time when the size grows to the level where maintenance is needed prevents unexpected efforts and helps to spot problematic artifacts before they become critical. Although the amount of prediction approaches in literature is vast, it is unclear how well they fit with prerequisites and expectations from practice. In this paper, we perform an industrial case study at an automotive manufacturer to explore applicability and usability of prediction approaches in practice. In a first step, we collect the most relevant prediction approaches from literature, including both, approaches using statistics and machine learning. Furthermore, we elicit expectations towards predictions from practitioners using a survey and stakeholder workshops. At the same time, we measure software size of 48 software artifacts by mining four years of revision history, resulting in 4,547 data points. In the last step, we assess the applicability of state-of-the-art prediction approaches using the collected data by systematically analyzing how well they fulfill the practitioners' expectations. Our main contribution is a comparison of commonly used prediction approaches in a real world industrial setting while considering stakeholder expectations. We show that the approaches provide significantly different results regarding prediction accuracy and that the statistical approaches fit our data best

Differential diagnostic value of CD5 and CD117 expression in thoracic tumors: A large scale study of 1465 non-small cell lung cancer cases

Background: Thoracic pathologists are frequently faced with tissue specimens from intrathoracic/mediastinal tumors. Specifically the differentiation between thymic and pulmonary squamous cell carcinomas (SqCC) can be challenging. In order to clarify the differential diagnostic value of CD5 and CD117 in this setting, we performed a large scale expression study of both markers in 1465 non-small cell lung cancer (NSCLC) cases. Methods: Tissue microarrays of formalin-fixed paraffin-embedded resection specimens of 1465 NSCLC were stained with antibodies against CD117 and CD5. Positivity of both markers was correlated with clinicopathological variables. Results: CD117 was positive in 145 out of 1457 evaluable cases (9.9 %) and CD5 was positive in 133 out of 1427 evaluable cases (9.3 %). 28 cases (1.9 %) showed coexpression of CD117 and CD5. Among the 145 cases that were positive for CD117, 97 (66.8 %) were adenocarcinomas (ADC), 34 (23.4 %) were SqCC, 5 (3.4 %) were adenosquamous carcinomas (ADSqCC), 8 (5.5 %) were large cell carcinomas (LC), and one (0.6 %) was a pleomorphic carcinoma (PC). In the CD5 positive group consisting of 133 cases, 123 (92.4 %) were ADC, 0 (0 %) were SqCC, 4 (3.0 %) were ADSqCC, 3 (2.2 %) LC and 3 (2.2 %) were PC. None of the 586 SqCC showed expression of CD5. No association of CD117- or CD5 positivity to patients’ age, pathological stages or to T-, N-, or M- categories was observed. Conclusions: A substantial subset of NSCLC exhibit positivity of CD117 and CD5. Since CD5 expression was not observed in pulmonary SqCC, but is expressed in the majority of thymic squamous cell carcinomas, the application of this immunomarker is a valuable tool in the differential diagnosis of thoracic neoplasms

Mutations in POLE and survival of colorectal cancer patients – link to disease stage and treatment

Recent molecular profiling studies reported a new class of ultramutated colorectal cancers (CRCs), which are caused by exonuclease domain mutations (EDMs) in DNA polymerase ϵ (POLE). Data on the clinical implications of these findings as to whether these mutations define a unique CRC entity with distinct clinical outcome are lacking. We performed Sanger sequencing of the POLE exonuclease domain in 431 well-characterized patients with microsatellite stable (MSS) CRCs of a population-based patient cohort. Mutation data were analyzed for associations with major epidemiological, clinical, genetic, and pathological parameters including overall survival (OS) and disease-specific survival (DSS). In 373 of 431 MSS CRC, all exons of the exonuclease domain were analyzable. Fifty-four mutations were identified in 46 of these samples (12.3%). Besides already reported EDMs, we detected many new mutations in exons 13 and 14 (corresponding to amino acids 410–491) as well as in exon 9 and exon 11 (corresponding to aa 268–303 and aa 341–369). However, we did not see any significant associations of EDMs with clinicopathological parameters, including sex, age, tumor location and tumor stage, CIMP, KRAS, and BRAF mutations. While with a median follow-up time of 5.0 years, survival analysis of the whole cohort revealed nonsignificantly different adjusted hazard ratios (HRs) of 1.35 (95% CI: 0.82–2.25) and 1.44 (0.81–2.58) for OS and DSS indicating slightly impaired survival of patients with EDMs, subgroup analysis for patients with stage III/IV disease receiving chemotherapy revealed a statistically significantly increased adjusted HR (1.87; 95%CI: 1.02–3.44). In conclusion, POLE EDMs do not appear to define an entirely new clinically distinct disease entity in CRC but may have prognostic or predictive implications in CRC subgroups, whose significance remains to be investigated in future studies

Stratification of pancreatic tissue samples for molecular studies: RNA-based cellular annotation procedure

Abstract Background/objectives Meaningful profiling of pancreatic cancer samples is particularly challenging due to their complex cellular composition. Beyond tumor cells, surgical biopsies contain desmoplastic stroma with infiltrating inflammatory cells, adjacent normal parenchyma, and "non-pancreatic tissues". The risk of misinterpretation rises when the heterogeneous cancer tissues are sub-divided into smaller fragments for multiple analytic procedures. Pre-analytic histological evaluation is the best option to characterize pancreatic tissue samples. Our aim was to develop a complement or alternative procedure to determine the cellular composition of pancreatic cancerous biopsies, basing on intra-analytic molecular annotation. A standard process for sample stratification at a molecular level does not yet exist. Particularly in the case of retrospective or data depository-based studies, when hematoxylin-eosin stained sections are not available, it supports the correct interpretation of expression profiles. Methods A five-gene transcriptional signature ( RNA CellStrat) was defined that allows cell type-specific stratification of pancreatic tissues. Testing biopsy material from biobanks with this procedure demonstrated high correspondence of molecular (qRT-PCR and microarray) and histologic (hematoxylin-eosin stain) evaluations. Results Notably, about a quarter of randomly selected samples (tissue fragments) were exposed as inappropriate for subsequent clinico-pathological interpretation. Conclusions Via immediate intra-analytical procedure, our RNA-based stratification RNA CellStrat increases the accuracy and reliability of the conclusions drawn from diagnostic and prognostic molecular information

Low expression of aldehyde deyhdrogenase 1A1 (ALDH1A1) is a prognostic marker for poor survival in pancreatic cancer

<p>Abstract</p> <p>Background</p> <p>Aldehyde deyhdrogenase 1 (ALDH1) has been characterised as a cancer stem cell marker in different types of tumours. Additionally, it plays a pivotal role in gene regulation and endows tumour cells with augmented chemoresistance. Recently, ALDH1A1 has been described as a prognostic marker in a pancreatic cancer tissue microarray. The aim of this study was to reevaluate the expression of ALDH1A1 as a prognostic marker on whole-mount tissue sections.</p> <p>Methods</p> <p>Real-time-quantitative-PCR (qRT-PCR) and Western blotting were used to evaluate the expression profile of ALDH1A1 in seven pancreatic cancer cell lines and one non-malignant pancreatic cell line. Immunostaining against ALDH1A1 and Ki-67 was performed on paraffin-embedded samples from 97 patients with pancreatic cancer. The immunohistochemical results were correlated to histopathological and clinical data.</p> <p>Results</p> <p>qRT-PCR and Western blotting revealed a different expression pattern of ALDH1A1 in different malignant and non-malignant pancreatic cell lines. Immunohistochemical analysis demonstrated that ALDH1A1 was confined to the cellular cytoplasm and occurred in 72 cases (74%), whereas it was negative in 25 cases (26%). High expression of ALDH1A1 was significantly correlated to an increased proliferation rate (Spearman correlation, p = 0.01). Univariate and multivariate analyses showed that decreased expression of ALDH1A1 is an independent adverse prognostic factor for overall survival.</p> <p>Conclusions</p> <p>Immunonhistochemical analysis on whole-mount tissue slides revealed that ALDH1A1 is more abundantly expressed in pancreatic cancer than initially reported by a tissue microarray analysis. Moreover, high expression of ALDH1A1 correlated significantly with the proliferation of tumour cells. Intriguingly, this study is the first which identifies low expression of ALDH1A1 as an independent adverse prognostic marker for overall survival in pancreatic cancer.</p

Loss of aquaporin-4 expression and putative function in non-small cell lung cancer

<p>Abstract</p> <p>Background</p> <p>Aquaporins (AQPs) have been recognized to promote tumor progression, invasion, and metastasis and are therefore recognized as promising targets for novel anti-cancer therapies. Potentially relevant AQPs in distinct cancer entities can be determined by a comprehensive expression analysis of the 13 human AQPs.</p> <p>Methods</p> <p>We analyzed the presence of all AQP transcripts in 576 different normal lung and non-small cell lung cancer (NSCLC) samples using microarray data and validated our findings by qRT-PCR and immunohistochemistry.</p> <p>Results</p> <p>Variable expression of several AQPs (AQP1, -3, -4, and -5) was found in NSCLC and normal lung tissues. Furthermore, we identified remarkable differences between NSCLC subtypes in regard to AQP1, -3 and -4 expression. Higher transcript and protein levels of AQP4 in well-differentiated lung adenocarcinomas suggested an association with a more favourable prognosis. Beyond water transport, data mining of co-expressed genes indicated an involvement of AQP4 in cell-cell signalling, cellular movement and lipid metabolism, and underlined the association of AQP4 to important physiological functions in benign lung tissue.</p> <p>Conclusions</p> <p>Our findings accentuate the need to identify functional differences and redundancies of active AQPs in normal and tumor cells in order to assess their value as promising drug targets.</p

Basement membrane components are key players in specialized extracellular matrices

More than three decades ago, basement membranes (BMs) were described as membrane-like structures capable of isolating a cell from and connecting a cell to its environment. Since this time, it has been revealed that BMs are specialized extracellular matrices (sECMs) with unique components that support important functions including differentiation, proliferation, migration, and chemotaxis of cells during development. The composition of these sECM is as unique as the tissues to which they are localized, opening the possibility that such matrices can fulfill distinct functions. Changes in BM composition play significant roles in facilitating the development of various diseases. Furthermore, tissues have to provide sECM for their stem cells during development and for their adult life. Here, we briefly review the latest research on these unique sECM and their components with a special emphasis on embryonic and adult stem cells and their niches

Leistungsbewertung zeitkritischer Datenübertragung in automobilen Kommunikationssystemen

For almost 30 years, the airbag has been part of a car’s passive safety components to protect occupants in a crash. In 1980, in the former S-Class from Mercedes-Benz, the system triggered only one driver airbag, though it was composed of 170 parts. Today, highly integrated electronic control units for deployment of front, side or window airbags are standard equipment even in compact cars. At all times, the airbag control was built as an autarkic system for self-contained detection of crash severity and deployment of protection means. With continuing improvements in sensors, electronics and algorithmic concepts for sensor data processing in the airbag control, the time spans between impact and airbag deployment could be reduced to about 30 milliseconds. Every millisecond in reaction time which can be saved, directly contributes to a reduction of injury severity for the occupants. Thus, even shorter time spans for deployment would be desirable. However, the performance of passive safety systems, which react on a collision, and of constructive means, in terms of increased stiffness of the vehicle body, is widely exhausted. The networking and interplay of passive and active safety components, like the electronic stability program or the radar-based headway control, appears to be a promising instrument to compensate for this. Active safety components engage actively into the vehicle dynamics in case of a dangerous driving situation in order to avoid a crash, e.g. if the car turns into a side-slip or the distance to a vehicle in front falls below a certain threshold. If sensor data, which are computed by active safety components in a dangerous driving situation, are communicated to the airbag control, it will be able to react faster and more effective in case a crash cannot be avoided in the following. For example, previous knowledge of a risky situation might be used to lower algorithmic thresholds for airbag deployment in order to achieve a shorter reaction time in case of emergency compared to a purely passive reaction on the impact. Such a networking of active and passive safety has to be performed using the in-car communication infrastructure, consisting of bus systems like CAN or FlexRay and gateways to interconnect single bus segments. Real-time capabilities and timeliness of data transfer – which means data arrives at the receiver within a predefined time interval – are of essential importance for the effectiveness of networked applications for occupant protection. Otherwise, the crash might occur before the passive components were able to receive and process sensor data from active safety systems. For development of networked, highly time-critical vehicle safety systems, sophisticated evaluation of data transmission is indispensable at an early stage of system design. In this dissertation, concepts and methods are presented to conduct comprehensive performance evaluation studies of in-car communication and to support efficient safety systems in future vehicles. A hardware- and software-based measurement infrastructure was built, which allows to figure out effects of data transmission in normal operation mode, the so-called use-case, by evaluation of recorded communication data and to derive important system parameters from the samples. These parameters serve as realistic input for a system model, which resembles the functional and timing behavior of relevant system components using UML-based statecharts and discrete event simulation. The simulation allows for capturing various communication scenarios and for obtaining meaningful performance measures, like end-to-end transmission delays. For the field of time-critical safety applications, measures for the worst-case of system operation are also vitally important. Therefore, the analytical method of Network Calculus was extended to meet the requirements of automotive communication systems and applied to this area for the first time ever. The analytic results resemble guaranteed upper bounds for delays in data transmission and allow, together with the outcomes from real-life measurements and from use-case simulation, for a distinct evaluation of the networked system in early design phases. Performance measures could be obtained for both the use-case and the worst-case of system operation, supporting a comprehensive evaluation, which can be adapted to the actual criticality of the application and leads to a significant increase in performance of future networked vehicle safety systems.Seit fast 30 Jahren bietet der Airbag als Komponente der passiven Fahrzeugsicherheit den Insassen Schutz bei einem Unfall. 1980, in der damaligen Mercedes-Benz S-Klasse, aktivierte das System lediglich einen Fahrerairbag und bestand aus 170 Bauteilen. Heute sind hochintegrierte, elektronische Steuerungen für Front-, Seiten- oder Kopf-Airbags bereits in Kleinwagen Serienausstattung. Die Airbagsteuerung war seit jeher als autarkes System ausgelegt, das eigenständig die Schwere der Kollision detektiert und die Schutzmittel aktiviert. Durch stetige Verbesserungen im Bereich der Sensorik, der Elektronik im Steuergerät und der algorithmischen Konzepte der Sensordatenverarbeitung konnten die Reaktionszeiten bis zur Auslösung der Airbags auf ca. 30 Millisekunden reduziert werden. Da jede Millisekunde, die die Systeme der passiven Sicherheit nach Kollisionsbeginn früher aktiviert werden können, dazu beiträgt, die Verletzungsschwere der Insassen zu reduzieren, wären jedoch noch kürzere Auslösezeiten wünschenswert. Passive Konzepte allein, also die Reaktion auf eine Kollision, scheinen weitestgehend ausgereizt, ebenso wie konstruktive Maßnahmen zur Erhöhung der Karosseriesteifigkeit. Ein vielversprechender Ansatz ist die Vernetzung von Systemen der passiven Fahrzeugsicherheit mit aktiven Sicherheitskompontenten, wie dem Elektronischen Stabilitätsprogramm oder der Radar-basierten Abstandsregelung. Diese Systeme greifen durch gezielte Aktionen in einer Gefahrensituation in das Fahrgeschehen ein um einen Unfall zu verhindern, z.B. wenn das Fahrzeug ins Schleudern gerät oder der Abstand zum vorausfahrenden Fahrzeug einen kritischen Wert unterschreitet. Werden die Sensordaten, die die aktiven Systeme in einer frühen Gefährdungsphase errechnen, an die Airbagsteuerung kommuniziert und es kommt zur Kollision, kann auf diese schneller und effektiver reagiert werden, z.B. indem Auslöseschwellen in den Airbagalgorithmen bei akuter Gefährdung herabgesetzt werden und bei konkretem Eintritt der Kollision die Airbags mit diesem Vorwissen früher gezündet werden können als bei einer rein passiven Systemauslegung. Eine solche Vernetzung von aktiven und passiven Komponenten muss über die Fahrzeug-interne Kommunikationsinfrastruktur aus Bussystemen wie CAN oder FlexRay und Gateways zur Verbindung einzelner Bussegmente geschehen. Hierbei ist die Echtzeitfähigkeit, also die Übertragung der Daten in einem prädizierbaren Zeitintervall, von essentieller Bedeutung für die Effektivität der vernetzten Fahrzeugsicherheitsfunktionen. Zu lange Übertragungszeiten können dazu führen, dass die Kollision bereits eingetreten ist, bevor die Sensordaten in den passiven Systemen überhaupt empfangen und verarbeitet werden konnten. Für die Entwicklung vernetzter, hochgradig zeitkritischer Systeme der Fahrzeugsicherheit ist somit eine Evaluation der Datenübertragung bereits in frühen Phasen des Entwurfsprozesses unerlässlich. Die vorliegende Dissertation stellt Konzepte und Methoden vor, die für eine umfassende Leistungsbewertung Fahrzeug-interner Kommunikation erarbeitet wurden und die Auslegung effizienter, zukünftiger Sicherheitssysteme entscheidend unterstützen. Es wurde eine Hardware- und Software-basierte Messinfrastruktur geschaffen, die es erlaubt, anhand aufgezeichneter Kommunikationsdaten Effekte bei der Datenübertragung im realen Fahrzeugbetrieb, dem sogenannten use-case, aufzuzeigen und wichtige Systemparameter zu identifizieren. Diese Parameter dienen als realistische Eingabedaten für ein Systemmodell, das Funktionalität und zeitliches Verhalten der relevanten Komponenten mittels UML-basierter Zustandsdiagramme und diskreter Ereignissimulation nachbildet. In der Simulation können verschiedenste Kommunikationsszenarien untersucht und aussagekräftige Leistungskenngrößen, wie Ende-zu-Ende Übertragungslatenzen, ermittelt werden. Gerade im Bereich zeit- und sicherheitskritischer Anwendungen des Insassenschutzes sind jedoch auch Aussagen über das Systemverhalten im schlimmstmöglichen Fall, dem worst-case, von großer Relevanz. Um auch für dieses Szenario gültige Ergebnisse zu erlangen, wurde die analytische Methode des Network Calculus für Fragestellungen der Fahrzeug-internen Kommunikation erweitert und erstmals angewandt. Die analytischen Resultate stellen garantierte obere Schranken für die Verzögerungen bei der Datenübertragung dar und erlauben, zusammen mit den Erkenntnissen aus den Messungen an realen Fahrzeugen und den Ergebnissen der Simulation, eine frühzeitige Bewertung des vernetzten Sicherheitssystems. Leistungskenngrößen können sowohl für den Normalbetrieb wie auch für schlimmstmögliche Systemszenarien ermittelt werden, wodurch eine umfassende, an die Kritikalität der jeweiligen Anwendung angepasste Bewertung in einer frühen Designphase und eine signifikante Effizienzsteigerung zukünftiger, vernetzter Fahrzeugsicherheitsfunktionen möglich ist