Optimizing the Testing Process in Module Testing – Functional Testing Interface

Today's business environment has become increasingly unexpected and fast changing because of the global competition. This new environment requires the companies to organize their control differently, e.g. by logistic process thinking. Logistic process thinking in software engineering applies the principles of production process to immaterial products. Processes must be optimized, so that every phase adds value to the customer, and the lead times can be cut shorter to meet the new customer requirements. The purpose of this thesis is to examine and optimize the testing processes of software engineering concentrating on module testing, functional testing and their interface. The concept of logistic process thinking is introduced through production process, value added model and process management. Also theory of testing based on literature is presented, concentrating on module testing and functional testing. The testing processes of the Case Company are presented together with the project models in which they are implemented. The real life practices in module testing and functional testing and their interface are examined through interviews. These practices are analyzed against the processes and the testing theory, through which ideas for optimizing the testing process are introduced. The project world of the Case Company is also introduced together with two example testing projects in different life cycle phases. The examples give a view of how much effort of the project is put in different types of testing.

Prospective motion correction of 3D echo-planar imaging data for functional MRI using optical tracking.

We evaluated the performance of an optical camera based prospective motion correction (PMC) system in improving the quality of 3D echo-planar imaging functional MRI data. An optical camera and external marker were used to dynamically track the head movement of subjects during fMRI scanning. PMC was performed by using the motion information to dynamically update the sequence's RF excitation and gradient waveforms such that the field-of-view was realigned to match the subject's head movement. Task-free fMRI experiments on five healthy volunteers followed a 2×2×3 factorial design with the following factors: PMC on or off; 3.0mm or 1.5mm isotropic resolution; and no, slow, or fast head movements. Visual and motor fMRI experiments were additionally performed on one of the volunteers at 1.5mm resolution comparing PMC on vs PMC off for no and slow head movements. Metrics were developed to quantify the amount of motion as it occurred relative to k-space data acquisition. The motion quantification metric collapsed the very rich camera tracking data into one scalar value for each image volume that was strongly predictive of motion-induced artifacts. The PMC system did not introduce extraneous artifacts for the no motion conditions and improved the time series temporal signal-to-noise by 30% to 40% for all combinations of low/high resolution and slow/fast head movement relative to the standard acquisition with no prospective correction. The numbers of activated voxels (p<0.001, uncorrected) in both task-based experiments were comparable for the no motion cases and increased by 78% and 330%, respectively, for PMC on versus PMC off in the slow motion cases. The PMC system is a robust solution to decrease the motion sensitivity of multi-shot 3D EPI sequences and thereby overcome one of the main roadblocks to their widespread use in fMRI studies.

Functional error modeling for uncertainty quantification in hydrogeology

Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.

The UlaG protein familly defines novel structural and functional motifs grafted on an ancient RNase fold

Background: Bacterial populations are highly successful at colonizing new habitats and adapting to changing environmental conditions, partly due to their capacity to evolve novel virulence and metabolic pathways in response to stress conditions and to shuffle them by horizontal gene transfer (HGT). A common theme in the evolution of new functions consists of gene duplication followed by functional divergence. UlaG, a unique manganese-dependent metallo-b-lactamase (MBL) enzyme involved in L-ascorbate metabolism by commensal and symbiotic enterobacteria, provides a model for the study of the emergence of new catalytic activities from the modification of an ancient fold. Furthermore, UlaG is the founding member of the so-called UlaG-like (UlaGL) protein family, a recently established and poorly characterized family comprising divalent (and perhaps trivalent)metal-binding MBLs that catalyze transformations on phosphorylated sugars and nucleotides. Results: Here we combined protein structure-guided and sequence-only molecular phylogenetic analyses to dissect the molecular evolution of UlaG and to study its phylogenomic distribution, its relatedness with present-day UlaGL protein sequences and functional conservation. Phylogenetic analyses indicate that UlaGL sequences are present in Bacteria and Archaea, with bona fide orthologs found mainly in mammalian and plant-associated Gramnegative and Gram-positive bacteria. The incongruence between the UlaGL tree and known species trees indicates exchange by HGT and suggests that the UlaGL-encoding genes provided a growth advantage under changing conditions. Our search for more distantly related protein sequences aided by structural homology has uncovered that UlaGL sequences have a common evolutionary origin with present-day RNA processing and metabolizing MBL enzymes widespread in Bacteria, Archaea, and Eukarya. This observation suggests an ancient origin for the UlaGL family within the broader trunk of the MBL superfamily by duplication, neofunctionalization and fixation. Conclusions: Our results suggest that the forerunner of UlaG was present as an RNA metabolizing enzyme in the last common ancestor, and that the modern descendants of that ancestral gene have a wide phylogenetic distribution and functional roles. We propose that the UlaGL family evolved new metabolic roles among bacterial and possibly archeal phyla in the setting of a close association with metazoans, such as in the mammalian gastrointestinal tract or in animal and plant pathogens, as well as in environmental settings. Accordingly, the major evolutionary forces shaping the UlaGL family include vertical inheritance and lineage-specific duplication and acquisition of novel metabolic functions, followed by HGT and numerous lineage-specific gene loss events.

Functional testing in TETRA system

Terrestrial Trunked Radio (TETRA) on moderni digitaalinen matkapuhelinjärjestelmän standardi, joka on suunniteltu täyttämään erityisesti viranomaisten vaativat tarpeet turvallisuuden ja luotettavuuden suhteen. Ohjelmiston testaus on tärkeä osa sen laadun takaamiseksi. Testaus on jaettu useisiin vaiheisiin ja se kattaa koko ohjelmiston elinkaaren: ohjelmiston kehittelystä alkaen asiakkaalle lähetettyyn valmiiseen tuotteeseen saakka. Toiminnallisuustestauksen suorittaa joko ohjelmiston suunnittelijat tai erillinen testausryhmä käyttäen Nokia TETRA-järjestelmän testauslaboratoriota. Testauksen tarkoituksena on varmistaa, että ohjelmisto, sen aliohjelmat ja ominaisuudet täyttävät niille annetut toiminnalliset ja laadulliset vaatimukset. Tämä diplomityö antaa yleiskuvan toiminnallisuustestausprosessista Nokia TETRA järjestelmän laboratoriossa. Se tarjoaa esimerkkitestitapauksen avulla kokonaiskuvan siitä, kuinka toiminnallisuustestausprosessi suoritetaan alusta loppuun.

Functional characterization of the Pneumocystis jirovecii potential drug targets dhfs and abz2 involved in folate biosynthesis.

Pneumocystis species are fungal parasites colonizing mammal lungs with strict host specificity. Pneumocystis jirovecii is the human-specific species and can turn into an opportunistic pathogen causing severe pneumonia in immunocompromised individuals. This disease is currently the second most frequent life-threatening invasive fungal infection worldwide. The most efficient drug, cotrimoxazole, presents serious side effects, and resistance to this drug is emerging. The search for new targets for the development of new drugs is thus of utmost importance. The recent release of the P. jirovecii genome sequence opens a new era for this task. It can now be carried out on the actual targets to be inhibited instead of on those of the relatively distant model Pneumocystis carinii, the species infecting rats. We focused on the folic acid biosynthesis pathway because (i) it is widely used for efficient therapeutic intervention, and (ii) it involves several enzymes that are essential for the pathogen and have no human counterparts. In this study, we report the identification of two such potential targets within the genome of P. jirovecii, the dihydrofolate synthase (dhfs) and the aminodeoxychorismate lyase (abz2). The function of these enzymes was demonstrated by the rescue of the null allele of the orthologous gene of Saccharomyces cerevisiae.

Brain functional abnormality in schizo-affective disorder: an fMRI study.

Background.Schizo-affective disorder has not been studied to any significant extent using functional imaging. The aim of this study was to examine patterns of brain activation and deactivation in patients meeting strict diagnostic criteria for the disorder. METHOD: Thirty-two patients meeting research diagnostic criteria (RDC) for schizo-affective disorder (16 schizomanic and 16 schizodepressive) and 32 matched healthy controls underwent functional magnetic resonance imaging (fMRI) during performance of the n-back task. Linear models were used to obtain maps of activations and deactivations in the groups. RESULTS: Controls showed activation in a network of frontal and other areas and also deactivation in the medial frontal cortex, the precuneus and the parietal cortex. Schizo-affective patients activated significantly less in prefrontal, parietal and temporal regions than the controls, and also showed failure of deactivation in the medial frontal cortex. When task performance was controlled for, the reduced activation in the dorsolateral prefrontal cortex (DLPFC) and the failure of deactivation of the medial frontal cortex remained significant. CONCLUSIONS: Schizo-affective disorder shows a similar pattern of reduced frontal activation to schizophrenia. The disorder is also characterized by failure of deactivation suggestive of default mode network dysfunction.

Refractory intraretinal or subretinal fluid in neovascular age-related macular degeneration treated with intravitreal ranizubimab: Functional and Structural Outcome.

PURPOSE: To investigate the visual acuity results of eyes with neovascular age-related macular degeneration and refractory fluid despite monthly treatment with ranibizumab, and to investigate differences between refractory subretinal fluid and intraretinal cystic changes. METHODS: Retrospective chart review of consecutive treatment-refractory neovascular age-related macular degeneration, defined as persistent intraretinal or subretinal fluid despite monthly ranibizumab injections during 12 months or more. Data were evaluated for baseline characteristics, type and location of the refractory fluid, mean visual acuity change, number of injections, and the time point of first complete disappearance of all fluid on spectral domain optical coherence tomography. RESULTS: Seventy-six eyes (74 patients, mean age, 76.8 years) were identified. The mean follow-up was 33.6 months (range, 12-73 months). The mean number of injections was 11.4 in the first year and 27.7 over follow-up. The refractory fluid was located subfoveally in 61.8%. In 27 eyes (35.5%), the fluid resolved after a mean of 21.8 months (range, 13-49 months). Mean visual acuity increased by 9.0, 7.9, and 7.9 letters by Month 12, Month 24, and Month 36, respectively. Subgroup analysis revealed a higher risk for fibrosis (odds ratio, 3.30) or atrophy (odds ratio, 3.34) in patients with refractory cysts as compared with refractory subretinal fluid. Furthermore, refractory cysts showed a higher risk for a 10-letter visual acuity loss (P = 0.018). CONCLUSION: Fluid refractory to monthly treatment with ranibizumab for neovascular age-related macular degeneration still allowed for well-maintained visual improvement, even in subfoveal location. Late fluid resolution may occur. However, refractory cysts were associated with poorer anatomical and functional outcome than subretinal fluid.

Identification of potential HIV restriction factors by combining evolutionary genomic signatures with functional analyses.

BACKGROUND: Known antiretroviral restriction factors are encoded by genes that are under positive selection pressure, induced during HIV-1 infection, up-regulated by interferons, and/or interact with viral proteins. To identify potential novel restriction factors, we performed genome-wide scans for human genes sharing molecular and evolutionary signatures of known restriction factors and tested the anti-HIV-1 activity of the most promising candidates. RESULTS: Our analyses identified 30 human genes that share characteristics of known restriction factors. Functional analyses of 27 of these candidates showed that over-expression of a strikingly high proportion of them significantly inhibited HIV-1 without causing cytotoxic effects. Five factors (APOL1, APOL6, CD164, TNFRSF10A, TNFRSF10D) suppressed infectious HIV-1 production in transfected 293T cells by >90% and six additional candidates (FCGR3A, CD3E, OAS1, GBP5, SPN, IFI16) achieved this when the virus was lacking intact accessory vpr, vpu and nef genes. Unexpectedly, over-expression of two factors (IL1A, SP110) significantly increased infectious HIV-1 production. Mechanistic studies suggest that the newly identified potential restriction factors act at different steps of the viral replication cycle, including proviral transcription and production of viral proteins. Finally, we confirmed that mRNA expression of most of these candidate restriction factors in primary CD4+ T cells is significantly increased by type I interferons. CONCLUSIONS: A limited number of human genes share multiple characteristics of genes encoding for known restriction factors. Most of them display anti-retroviral activity in transient transfection assays and are expressed in primary CD4+ T cells.

Using species richness and functional traits predictions to constrain assemblage predictions from stacked species distribution models

Aim: Modelling species at the assemblage level is required to make effective forecast of global change impacts on diversity and ecosystem functioning. Community predictions may be achieved using macroecological properties of communities (MEM), or by stacking of individual species distribution models (S-SDMs). To obtain more realistic predictions of species assemblages, the SESAM framework suggests applying successive filters to the initial species source pool, by combining different modelling approaches and rules. Here we provide a first test of this framework in mountain grassland communities. Location: The western Swiss Alps. Methods: Two implementations of the SESAM framework were tested: a "Probability ranking" rule based on species richness predictions and rough probabilities from SDMs, and a "Trait range" rule that uses the predicted upper and lower bound of community-level distribution of three different functional traits (vegetative height, specific leaf area and seed mass) to constraint a pool of environmentally filtered species from binary SDMs predictions. Results: We showed that all independent constraints expectedly contributed to reduce species richness overprediction. Only the "Probability ranking" rule allowed slightly but significantly improving predictions of community composition. Main conclusion: We tested various ways to implement the SESAM framework by integrating macroecological constraints into S-SDM predictions, and report one that is able to improve compositional predictions. We discuss possible improvements, such as further improving the causality and precision of environmental predictors, using other assembly rules and testing other types of ecological or functional constraints.