Modern Software Engineering Techniques Research Articles

Open Force Field BespokeFit: Automating Bespoke Torsion Parametrization at Scale.

The development of accurate transferable force fields is key to realizing the full potential of atomistic modeling in the study of biological processes such as protein-ligand binding for drug discovery. State-of-the-art transferable force fields, such as those produced by the Open Force Field Initiative, use modern software engineering and automation techniques to yield accuracy improvements. However, force field torsion parameters, which must account for many stereoelectronic and steric effects, are considered to be less transferable than other force field parameters and are therefore often targets for bespoke parametrization. Here, we present the Open Force Field QCSubmit and BespokeFit software packages that, when combined, facilitate the fitting of torsion parameters to quantum mechanical reference data at scale. We demonstrate the use of QCSubmit for simplifying the process of creating and archiving large numbers of quantum chemical calculations, by generating a dataset of 671 torsion scans for druglike fragments. We use BespokeFit to derive individual torsion parameters for each of these molecules, thereby reducing the root-mean-square error in the potential energy surface from 1.1 kcal/mol, using the original transferable force field, to 0.4 kcal/mol using the bespoke version. Furthermore, we employ the bespoke force fields to compute the relative binding free energies of a congeneric series of inhibitors of the TYK2 protein, and demonstrate further improvements in accuracy, compared to the base force field (MUE reduced from 0.560.390.77 to 0.420.280.59 kcal/mol and R2 correlation improved from 0.720.350.87 to 0.930.840.97).

Python Battery Mathematical Modelling (PyBaMM)

As the UK battery modelling community grows, there is a clear need for software that uses modern software engineering techniques to facilitate cross-institutional collaboration and democratise research progress. The Python package PyBaMM aims to provide a flexible platform for implementation and comparison of new models and numerical methods. This is achieved by implementing models as expression trees and processing them in a modular fashion through a pipeline. Comprehensive testing provides robustness to changes and hence eases the implementation of model extensions. PyBaMM is open source and available on GitHub. For more information visit <a href="https://www.pybamm.org" target="_blank">www.pybamm.org</a>.

Fast pure ion chromatograms extraction method for LC-MS

Liquid chromatography coupled with mass spectrometry (LC-MS) has shown great potential in analysis complex samples. However, informative feature extraction is still challenge since the electrospray ionization in LC-MS tends to produce ninety percent or more ions not originated from compounds of interest. The concept of pure ion chromatogram (PIC) is effective to extract informative ions, but tradition PIC methods are time-consuming because of their theories and programming languages. In this study, we present a novel method, called Fast Pure Ions Chromatograms (FPIC), for extracting PICs from raw LC-MS dataset effectively and quickly. This method can search ion of PIC from its maximum bi-directionally and adaptively, which can improve the stability and reduce the computation time drastically. A further speedup has been achieved by exploiting modern software engineering techniques. FPIC was validated by analyzing four LC-MS datasets: MM14 and MM48, simulated MM48 and quantification (MTBLS234) datasets. Results show that FPIC outperformed traditional methods in the recall, precision and F-score, and it has good reliability of quantification. Furthermore, the method is very fast with few adjustable parameters, which leads to an approximately 125-fold speedup over PITracer and 18-fold speedup over XCMS. An open source implementation of the FPIC method is available at https://github.com/zmzhang/pymass.

Continuous Integration for Concurrent MOOSE Framework and Application Development on GitHub

For the past several years, Idaho National Laboratory’s MOOSE framework team has employed modern software engineering techniques (continuous integration, joint application/framework source code repos- itories, automated regression testing, etc.) in developing closed-source multiphysics simulation software (Gaston et al., Journal of Open Research Software vol. 2, article e10, 2014). In March 2014, the MOOSE framework was released under an open source license on GitHub, significantly expanding and diversifying the pool of current active and potential future contributors on the project. Despite this recent growth, the same philosophy of concurrent framework and application development continues to guide the project’s development roadmap. Several specific practices, including techniques for managing multiple repositories, conducting automated regression testing, and implementing a cascading build process are discussed in this short paper. Special attention is given to describing the manner in which these practices naturally synergize with the GitHub API and GitHub-specific features such as issue tracking, Pull Requests, and project forks.

Tools and techniques for non-invasive explicit parallelization

This paper presents an overview of our experiments in integrating modern software engineering tools and techniques with the process of developing parallel applications for distributed memory architectures. The main goal was to determine the methods that have the potential of reducing the complexities associated with explicit parallelization. We experimented with template metaprogramming, aspect-oriented programming, program transformation engine, and a domain-specific language called Hi-PaL. The pros and cons of using each technique for explicit parallelization are presented in this paper. Our experiments demonstrate that through a combination of modern software engineering tools and techniques, the effort involved in explicit parallelization can be reduced by 90 % without any significant loss in performance.

A systematic review of applying modern software engineering techniques to developing robotic systems

Robots have become collaborators in our daily life. While robotic systems become more and more complex, the need to engineer their software development grows as well. The traditional approaches used in developing these software systems are reaching their limits; currently used methodologies and tools fall short of addressing the needs of such complex software development. Separating robotics' knowledge from short-cycled implementation technologies is essential to foster reuse and maintenance. This paper presents a systematic review (SLR) of the current use of modern software engineering techniques for developing robotic software systems and their actual automation level. The survey was aimed at summarizing existing evidence concerning applying such technologies to the field of robotic systems to identify any gaps in current research to suggest areas for further investigation and provide a background for positioning new research activities.

To Boldly Go Where No One Has Gone Before

Architecture mastery is more than professional expertise in modern software engineering methods and techniques. It is mainly in how architects approach design. Particularly, the "things between things" require the architect's full attention: domain concepts hidden between the lines of code; interactions and interfaces residing between components; and even choices between design options. This is the architect's territory, and successful architecture uncovers the things "in-between" as early as possible, make them explicit, and decide about them!

Supporting Agile Change Management by Scenario-Based Regression Simulation

Many system-development projects today are mainly driven by the complexity of their software interacting with sensors or actuators in an embedded context. Autonomous vehicle development is a domain where it seems inevitably necessary to apply modern development techniques to cope with complexity, increase development efficiency, and ensure appropriate quality. Furthermore, changes that are triggered by customers or inventions of competitors, as well as bugs, enforce a comprehensible, if necessary, yet agile development process with stringent quality management. In this paper, we describe the agile efficiency- and quality-focused change management mainly based on scenario-driven regression simulation used in the CarOLO project for the development of an autonomously driving vehicle to compete in the 2007 Defense Advanced Research Projects Agency (DARPA) Urban Challenge program. The main contribution is the demonstration of the modern software engineering techniques' applicability to develop distributed embedded systems.

Increasing the reliability of ecological models using modern software engineering techniques

Modern software development techniques are largely unknown to ecologists. Typically, ecological models and other software tools are developed for limited research purposes, and additional capabilities are added later, usually in an ad hoc manner. Modern software engineering techniques can substantially increase scientific rigor and confidence in ecological models and tools. These techniques have the potential to transform how ecological software is conceived and developed, improve precision, reduce errors, and increase scientific credibility. We describe our re‐engineering of the forest landscape model LANDIS (LANdscape DIsturbance and Succession) to illustrate the advantages of using common software engineering practices.

NEU-MODEL: A multi-level object-oriented dynamic emulation laboratory

Computational neuroscience aims to elucidate the mechanisms of neural information processing and population dynamics, through a methodology of incorporating biological data into complex mathematical models. Existing simulation environments model at a particular level of detail; none allow a multi-level approach to neural modelling. Moreover, most are not engineered to produce compute-efficient solutions, an important issue because sufficient processing power is a major impediment in the field. This project aims to apply modern software engineering techniques to create a flexible high performance neural modelling environment, which will allow rigorous exploration of model parameter effects, and modelling at multiple levels of abstraction.

The molecular modeling toolkit: A new approach to molecular simulations

The Molecular Modeling Toolkit is a library that implements common molecular simulation techniques, with an emphasis on biomolecular simulations. It uses modern software engineering techniques (object-oriented design, a high-level language) to overcome limitations associated with the large monolithic simulation programs that are commonly used for biomolecules. Its principal advantages are (1) easy extension and combination with other libraries due to modular library design; (2) a single high-level general-purpose programming language (Python) is used for library implementation as well as for application scripts; (3) use of documented and machine-independent formats for all data files; and (4) interfaces to other simulation and visualization programs. © 2000 John Wiley & Sons, Inc. J Comput Chem 21: 79–85, 2000

Future directions for combining molecular and continuum models in protein simulations

In order to perform useful computer simulations on protein molecules, models that combine atomistic and continuum approaches will be necessary. The use of continuum models will reduce the number of system variables and allow studies of longer time scales. On the other hand, one will still need to retain atomic detail in certain parts of the protein molecule, such as an enzyme active site. Most of the important advances to date have been continuum models of the surrounding solvent, but simplified descriptions of the protein itself also are being developed. Finally, in order to study these several different levels of complexity simultaneously in a single simulation, it will be necessary to use modern software engineering techniques.

Specification, design and Modula-2 implementation of a low cost industrial control system

The purpose of this paper is to show the application of modern software engineering techniques to the construction of a small/medium size package for real time control. This package, denoted by SCM (acronym of “Sistema de Control Modular”), has been written in Modula-2 and presents all advantages offered by this high-level structured programming language. It has been implemented on a PC-AT compatible computer.

The Application of Modern Software Engineering Techniques in the Development of a Process Control Package

This paper discusses the techniques which have been used in a chemical industry user environment to develop a compact software package for regulatory and sequential/supervisory process control. The real-time language RTL/2 has been used to program the entire package. A problemoriented sequence control language is provided; it combines the advantages of maintainability and security of a high-level language and the ease of debugging and robustness of interpretive execution within the constraints of a memory-only environment by retaining an easily understood intermediate form in the on-line computer. The package is intended for future use in a node of a distributed computer control system.