Extracting Build Changes with BUILDDIFF

Build systems are an essential part of modern software engineering projects. As software projects change continuously, it is crucial to understand how the build system changes because neglecting its maintenance can lead to expensive build breakage. Recent studies have investigated the (co-)evolution of build configurations and reasons for build breakage, but they did this only on a coarse grained level. In this paper, we present BUILDDIFF, an approach to extract detailed build changes from MAVEN build files and classify them into 95 change types. In a manual evaluation of 400 build changing commits, we show that BUILDDIFF can extract and classify build changes with an average precision and recall of 0.96 and 0.98, respectively. We then present two studies using the build changes extracted from 30 open source Java projects to study the frequency and time of build changes. The results show that the top 10 most frequent change types account for 73% of the build changes. Among them, changes to version numbers and changes to dependencies of the projects occur most frequently. Furthermore, our results show that build changes occur frequently around releases. With these results, we provide the basis for further research, such as for analyzing the (co-)evolution of build files with other artifacts or improving effort estimation approaches. Furthermore, our detailed change information enables improvements of refactoring approaches for build configurations and improvements of models to identify error-prone build files.Comment: Accepted at the International Conference of Mining Software Repositories (MSR), 201

What kind of questions do developers ask on Stack Overflow? A comparison of automated approaches to classify posts into question categories

On question and answer sites, such as Stack Overflow (SO), developers use tags to label the content of a post and to support developers in question searching and browsing. However, these tags mainly refer to technological aspects instead of the purpose of the question. Tagging questions with their purpose can add a new dimension to the identification of discussed topics in posts on SO. In this paper, we aim at automating the classification of SO question posts into seven question categories. As a first step, we harmonized existing taxonomies of question categories and then, we manually classified 1,000 SO questions according to our new taxonomy. Additionally to the question category, we marked the phrases that indicate a question category for each of the posts. We then use this data set to automate the classification of posts using two approaches. For the first approach, we manually analyzed the phrases to find patterns. Based on regular expressions, we implemented a classifier, for each of the categories, that determines whether a post belongs to a category. These regular expressions are derived by analyzing patterns in the phrases. In the second approach, we use the curated data set to train classification models of supervised machine learning algorithms (Random Forest and Support Vector Machines). For the machine learning algorithms, we experimented with 1,312 different configurations regarding the preprocessing of the text and the representation of the input data. Then, we compared the performance of the regex approach with the performance of the best configuration that uses machine learning algorithms on a validation set of 110 posts. The results show that using the regular expression approach, we can classify posts into the correct question category with an average precision and recall of 0.90, and an MCC of 0.68. Additionally, we applied the regex approach on all questions of SO that deal with Android app development and investigated the co-occurrence of question categories in posts. We found that the categories API usage, Conceptual, and Discrepancy are the most frequently assigned question categories and that they also occur together frequently. Our approach can be used to support developers in browsing SO discussions or researchers in building recommender systems based on SO

Analytical approach to ground heat losses for high temperature thermal storage systems

A new approach to estimate the heat loss from thermal energy storage tank foundations is presented. Results are presented through analytical correlations based on numerical solutions for the steady-state heat conduction problem for thermal energy slab-on-grade tanks with uniform insulation. Model results were verified with other well-established benchmark problems with similar boundary conditions and validated with experimental data with excellent agreement. In addition to the TES foundation heat loss, new correlations for the maximum temperature and for the radial evolution of the temperature underneath the insulation layer are also provided, giving important information related to the tank foundation design. The correlated variables are of primordial importance in the tank foundation design because, due to the typical high operating storage temperatures, an inappropriate tank foundation insulation would lead not only to a not desired loss of energy but also to an inadmissible increase of the temperatures underneath the insulation layer, affecting the structural stability of the tank. The proposed correlations provide a quick method for the estimation of total tank foundation heat losses and soil maximum temperature reached underneath the insulation layer, saving time, and cost on the engineering tank foundation design process. Finally, a comprehensive parametric analysis of the variables of interest is made and a set of cases covering a wide range of tank sizes, insulation levels, depths to water table, and storage temperatures are solved

Extreme scenarios: the tightest possible constraints on the power spectrum due to primordial black holes

Observational constraints on the abundance of primordial black holes (PBHs) constrain the allowed amplitude of the primordial power spectrum on both the smallest and the largest ranges of scales, covering over 20 decades from 1 - 10^20=Mpc. Despite tight constraints on the allowed fraction of PBHs at their time of formation near horizon entry in the early Universe, the corresponding constraints on the primordial power spectrum are quite weak, typically PR . 10<~2 assuming Gaussian perturbations. Motivated by recent claims that the evaporation of just one PBH would destabilise the Higgs vacuum and collapse the Universe, we calculate the constraints which follow from assuming there are zero PBHs within the observable Universe. Even if evaporating PBHs do not collapse the Universe, this scenario represents the ultimate limit of observational constraints. Constraints can be extended on to smaller scales right down to the horizon scale at the end of in ation, but where power spectrum constraints already exist they do not tighten significantly, even though the constraint on PBH abundance can decrease by up to 46 orders of magnitude. This shows that no future improvement in observational constraints can ever lead to a significant tightening in constraints on in ation (via the power spectrum amplitude). The power spectrum constraints are weak because an order unity perturbation is required in order to overcome pressure forces. We therefore consider an early matter dominated era, during which exponentially more PBHs form for the same initial conditions. We show this leads to far tighter constraints, which approach PR . 10^-9, albeit over a smaller range of scales and are very sensitive to when the early matter dominated era ends. Finally, we show that an extended early matter era is incompatible with the argument that an evaporating PBH would destroy the Universe, unless the power spectrum amplitude decreases by up to ten orders of magnitude

Configuration Smells in Continuous Delivery Pipelines: A Linter and a Six-Month Study on GitLab

An effective and efficient application of Continuous Integration (CI) and Delivery (CD) requires software projects to follow certain principles and good practices. Configuring such a CI/CD pipeline is challenging and error-prone. Therefore, automated linters have been proposed to detect errors in the pipeline. While existing linters identify syntactic errors, detect security vulnerabilities or misuse of the features provided by build servers, they do not support developers that want to prevent common misconfigurations of a CD pipeline that potentially violate CD principles (“CD smells”). To this end, we propose CD-Linter, a semantic linter that can automatically identify four different smells in pipeline configuration files. We have evaluated our approach through a large-scale and long-term study that consists of (i) monitoring 145 issues (opened in as many open-source projects) over a period of 6 months, (ii) manually validating the detection precision and recall on a representative sample of issues, and (iii) assessing the magnitude of the observed smells on 5,312 open-source projects on GitLab. Our results show that CD smells are accepted and fixed by most of the developers and our linter achieves a precision of 87% and a recall of 94%. Those smells can be frequently observed in the wild, as 31% of projects with long configurations are affected by at least one smell

PILAR: Plataforma de federación de laboratorios remotos VISIR de electrónica analógica

Resumen—Los laboratorios remotos son ya una herramienta de enseñanza/aprendizaje en diferentes campos de la ingeniería y de la ciencia. El laboratorio remoto VISIR es un ejemplo paradigmático de esta nueva metodología en el campo de la electrónica analógica ya que el alumno puede montar y medir circuitos reales de un modo satisfactorio. En la actualidad en Europa hay cinco instancias desplegadas y activas de VISIR y en Sudamérica hay 5 más, cada una de ellas ofrece distintos circuitos eléctricos y electrónicos de manera que el usuario debe saber dónde está desplegado el circuito que él quiere montar y desplegar para poder acceder a él, lo que es una clara limitación. La solución al problema pasa por federar dicho grupo de laboratorios remotosinfo:eu-repo/semantics/publishedVersio

Configural and featural processing in humans with congenital prosopagnosia.

Prosopagnosia describes the failure to recognize faces, a deficiency that can be devastating in social interactions. Cases of acquired prosopagnosia have often been described over the last century. In recent years, more and more cases of congenital prosopagnosia (CP) have been reported. In the present study we tried to determine possible cognitive characteristics of this impairment. We used scrambled and blurred images of faces, houses, and sugar bowls to separate featural processing strategies from configural processing strategies. This served to investigate whether congenital prosopagnosia results from process-specific deficiencies, or whether it is a face-specific impairment. Using a delayed matching paradigm, 6 individuals with CP and 6 matched healthy controls indicated whether an intact test stimulus was the same identity as a previously presented scrambled or blurred cue stimulus. Analyses of d´ values indicated that congenital prosopagnosia is a face-specific deficit, but that this shortcoming is particularly pronounced for processing configural facial information

Experimenting in PILAR Federation: a Common Path for the Future

The PILAR (Platform Integration of Laboratories based on the Architecture of visiR) Erasmus Plus project started in September 2016 and will last three years. The core of the PILAR project is the VISIR remote laboratory —Virtual Instruments System In Reality—. The project aims for a federation of five of the existing VISIR nodes, sharing experiments, capacity and resources among partners, and to provide access to VISIR remote lab, through PILAR consortium, to students from other educational institutions. PILAR will be the framework from which management tasks will be performed and laboratories/experiments will be shared. PILAR will also foster the Special Interest Group of VISIR under the Global Online Laboratory Consortium (GOLC) of the International Association of Online Engineering (IAOE).info:eu-repo/semantics/publishedVersio

The Arabidopsis leucine-rich repeat receptor kinase MIK2/LRR-KISS connects cell wall integrity sensing, root growth and response to abiotic and biotic stresses

Plants actively perceive and respond to perturbations in their cell walls which arise during growth, biotic and abiotic stresses. However, few components involved in plant cell wall integrity sensing have been described to date. Using a reverse-genetic approach, we identified the Arabidopsis thaliana leucine-rich repeat receptor kinase MIK2 as an important regulator of cell wall damage responses triggered upon cellulose biosynthesis inhibition. Indeed, loss-of-function mik2 alleles are strongly affected in immune marker gene expression, jasmonic acid production and lignin deposition. MIK2 has both overlapping and distinct functions with THE1, a malectin-like receptor kinase previously proposed as cell wall integrity sensor. In addition, mik2 mutant plants exhibit enhanced leftward root skewing when grown on vertical plates. Notably, natural variation in MIK2 (also named LRR-KISS) has been correlated recently to mild salt stress tolerance, which we could confirm using our insertional alleles. Strikingly, both the increased root skewing and salt stress sensitivity phenotypes observed in the mik2 mutant are dependent on THE1. Finally, we found that MIK2 is required for resistance to the fungal root pathogen Fusarium oxysporum. Together, our data identify MIK2 as a novel component in cell wall integrity sensing and suggest that MIK2 is a nexus linking cell wall integrity sensing to growth and environmental cues