DeltaImpactFinder: Assessing Semantic Merge Conflicts with Dependency Analysis

In software development, version control systems (VCS) provide branching and merging support tools. Such tools are popular among developers to concurrently change a code-base in separate lines and reconcile their changes automatically afterwards. However, two changes that are correct independently can introduce bugs when merged together. We call semantic merge conflicts this kind of bugs. Change impact analysis (CIA) aims at estimating the effects of a change in a codebase. In this paper, we propose to detect semantic merge conflicts using CIA. On a merge, DELTAIMPACTFINDER analyzes and compares the impact of a change in its origin and destination branches. We call the difference between these two impacts the delta-impact. If the delta-impact is empty, then there is no indicator of a semantic merge conflict and the merge can continue automatically. Otherwise, the delta-impact contains what are the sources of possible conflicts.Comment: International Workshop on Smalltalk Technologies 2015, Jul 2015, Brescia, Ital

Semantic processing of EHR data for clinical research

There is a growing need to semantically process and integrate clinical data from different sources for clinical research. This paper presents an approach to integrate EHRs from heterogeneous resources and generate integrated data in different data formats or semantics to support various clinical research applications. The proposed approach builds semantic data virtualization layers on top of data sources, which generate data in the requested semantics or formats on demand. This approach avoids upfront dumping to and synchronizing of the data with various representations. Data from different EHR systems are first mapped to RDF data with source semantics, and then converted to representations with harmonized domain semantics where domain ontologies and terminologies are used to improve reusability. It is also possible to further convert data to application semantics and store the converted results in clinical research databases, e.g. i2b2, OMOP, to support different clinical research settings. Semantic conversions between different representations are explicitly expressed using N3 rules and executed by an N3 Reasoner (EYE), which can also generate proofs of the conversion processes. The solution presented in this paper has been applied to real-world applications that process large scale EHR data.Comment: Accepted for publication in Journal of Biomedical Informatics, 2015, preprint versio

RefDiff: Detecting Refactorings in Version Histories

Refactoring is a well-known technique that is widely adopted by software engineers to improve the design and enable the evolution of a system. Knowing which refactoring operations were applied in a code change is a valuable information to understand software evolution, adapt software components, merge code changes, and other applications. In this paper, we present RefDiff, an automated approach that identifies refactorings performed between two code revisions in a git repository. RefDiff employs a combination of heuristics based on static analysis and code similarity to detect 13 well-known refactoring types. In an evaluation using an oracle of 448 known refactoring operations, distributed across seven Java projects, our approach achieved precision of 100% and recall of 88%. Moreover, our evaluation suggests that RefDiff has superior precision and recall than existing state-of-the-art approaches.Comment: Paper accepted at 14th International Conference on Mining Software Repositories (MSR), pages 1-11, 201

Towards a Tool-based Development Methodology for Pervasive Computing Applications

Despite much progress, developing a pervasive computing application remains a challenge because of a lack of conceptual frameworks and supporting tools. This challenge involves coping with heterogeneous devices, overcoming the intricacies of distributed systems technologies, working out an architecture for the application, encoding it in a program, writing specific code to test the application, and finally deploying it. This paper presents a design language and a tool suite covering the development life-cycle of a pervasive computing application. The design language allows to define a taxonomy of area-specific building-blocks, abstracting over their heterogeneity. This language also includes a layer to define the architecture of an application, following an architectural pattern commonly used in the pervasive computing domain. Our underlying methodology assigns roles to the stakeholders, providing separation of concerns. Our tool suite includes a compiler that takes design artifacts written in our language as input and generates a programming framework that supports the subsequent development stages, namely implementation, testing, and deployment. Our methodology has been applied on a wide spectrum of areas. Based on these experiments, we assess our approach through three criteria: expressiveness, usability, and productivity

A-Lister: a tool for analysis of differentially expressed omics entities across multiple pairwise comparisons.

BackgroundResearchers commonly analyze lists of differentially expressed entities (DEEs), such as differentially expressed genes (DEGs), differentially expressed proteins (DEPs), and differentially methylated positions/regions (DMPs/DMRs), across multiple pairwise comparisons. Large biological studies can involve multiple conditions, tissues, and timepoints that result in dozens of pairwise comparisons. Manually filtering and comparing lists of DEEs across multiple pairwise comparisons, typically done by writing custom code, is a cumbersome task that can be streamlined and standardized.ResultsA-Lister is a lightweight command line and graphical user interface tool written in Python. It can be executed in a differential expression mode or generic name list mode. In differential expression mode, A-Lister accepts as input delimited text files that are output by differential expression tools such as DESeq2, edgeR, Cuffdiff, and limma. To allow for the most flexibility in input ID types, to avoid database installation requirements, and to allow for secure offline use, A-Lister does not validate or impose restrictions on entity ID names. Users can specify thresholds to filter the input file(s) by column(s) such as p-value, q-value, and fold change. Additionally, users can filter the pairwise comparisons within the input files by fold change direction (sign). Queries composed of intersection, fuzzy intersection, difference, and union set operations can also be performed on any number of pairwise comparisons. Thus, the user can filter and compare any number of pairwise comparisons within a single A-Lister differential expression command. In generic name list mode, A-Lister accepts delimited text files containing lists of names as input. Queries composed of intersection, fuzzy intersection, difference, and union set operations can then be performed across these lists of names.ConclusionsA-Lister is a flexible tool that enables the user to rapidly narrow down large lists of DEEs to a small number of most significant entities. These entities can then be further analyzed using visualization, pathway analysis, and other bioinformatics tools

A study of System Interface Sets (SIS) for the host, target and integration environments of the Space Station Program (SSP)

System interface sets (SIS) for large, complex, non-stop, distributed systems are examined. The SIS of the Space Station Program (SSP) was selected as the focus of this study because an appropriate virtual interface specification of the SIS is believed to have the most potential to free the project from four life cycle tyrannies which are rooted in a dependance on either a proprietary or particular instance of: operating systems, data management systems, communications systems, and instruction set architectures. The static perspective of the common Ada programming support environment interface set (CAIS) and the portable common execution environment (PCEE) activities are discussed. Also, the dynamic perspective of the PCEE is addressed

Quantifying the implicit process flow abstraction in SBGN-PD diagrams with Bio-PEPA

For a long time biologists have used visual representations of biochemical networks to gain a quick overview of important structural properties. Recently SBGN, the Systems Biology Graphical Notation, has been developed to standardise the way in which such graphical maps are drawn in order to facilitate the exchange of information. Its qualitative Process Diagrams (SBGN-PD) are based on an implicit Process Flow Abstraction (PFA) that can also be used to construct quantitative representations, which can be used for automated analyses of the system. Here we explicitly describe the PFA that underpins SBGN-PD and define attributes for SBGN-PD glyphs that make it possible to capture the quantitative details of a biochemical reaction network. We implemented SBGNtext2BioPEPA, a tool that demonstrates how such quantitative details can be used to automatically generate working Bio-PEPA code from a textual representation of SBGN-PD that we developed. Bio-PEPA is a process algebra that was designed for implementing quantitative models of concurrent biochemical reaction systems. We use this approach to compute the expected delay between input and output using deterministic and stochastic simulations of the MAPK signal transduction cascade. The scheme developed here is general and can be easily adapted to other output formalisms

Structured Review of Code Clone Literature

This report presents the results of a structured review of code clone literature. The aim of the review is to assemble a conceptual model of clone-related concepts which helps us to reason about clones. This conceptual model unifies clone concepts from a wide range of literature, so that findings about clones can be compared with each other