MOTIVATION: Wikipedia is a vital open educational resource in computational biology; however, a significant knowledge gap exists between English and non-English Wikipedias. Reducing this knowledge gap via intensive editing events, or "editathons," would be beneficial in reducing language barriers that disadvantage learners whose native language is not English. Results: We present a framework to guide educators in organizing editathons for learners to improve and create relevant Wikipedia articles. As a case study, we present the results of an editathon held at the 2024 ISCB Latin America conference, in which ten new articles were created for the Spanish-language edition of Wikipedia. We also present a web tool, "compbio-on-wiki," which identifies relevant English Wikipedia articles missing in other languages. We demonstrate the value of editathons to expand the accessibility and visibility of computational biology content in multiple languages. AVAILABILITY AND IMPLEMENTATION: Source code for the compbio-on-wiki Toolforge site is available at: https://github.com/lubianat/compbio-on-wiki.

MOTIVATION: Wikipedia is a vital open educational resource in computational biology. The quality of computational biology coverage in English-language Wikipedia has improved steadily in recent years. However, there is an increasingly large 'knowledge gap' between computational biology resources in English-language Wikipedia, and Wikipedias in non-English languages. Reducing this knowledge gap by providing educational resources in non-English languages would reduce language barriers which disadvantage non-native English speaking learners across multiple dimensions in computational biology. RESULTS: Here, we provide a comprehensive assessment of computational biology coverage in Spanish-language Wikipedia, the second most accessed Wikipedia worldwide. Using Spanish-language Wikipedia as a case study, we generate quantitative and qualitative data before and after a targeted educational event, specifically, a Spanish-focused student editing competition. Our data demonstrates how such events and activities can narrow the knowledge gap between English and non-English educational resources, by improving existing articles and creating new articles. Finally, based on our analysis, we suggest ways to prioritize future initiatives to improve open educational resources in other languages. AVAILABILITY AND IMPLEMENTATION: Scripts for data analysis are available at: https://github.com/ISCBWikiTeam/spanish.

MOTIVATION: Wikipedia is one of the most important channels for the public communication of science and is frequently accessed as an educational resource in computational biology. Joint efforts between the International Society for Computational Biology (ISCB) and the Computational Biology taskforce of WikiProject Molecular Biology (a group of expert Wikipedia editors) have considerably improved computational biology representation on Wikipedia in recent years. However, there is still an urgent need for further improvement in quality, especially when compared to related scientific fields such as genetics and medicine. Facilitating involvement of members from ISCB Communities of Special Interest (COSIs) would improve a vital open education resource in computational biology, additionally allowing COSIs to provide a quality educational resource highly specific to their subfield. RESULTS: We generate a list of around 1500 English Wikipedia articles relating to computational biology and describe the development of a binary COSI-Article matrix, linking COSIs to relevant articles and thereby defining domain-specific open educational resources. Our analysis of the COSI-Article matrix data provides a quantitative assessment of computational biology representation on Wikipedia against other fields and at a COSI-specific level. Furthermore, we conducted similarity analysis and subsequent clustering of COSI-Article data to provide insight into potential relationships between COSIs. Finally, based on our analysis, we suggest courses of action to improve the quality of computational biology representation on Wikipedia.

MOTIVATION: De novo motif discovery algorithms find statistically over-represented sequence motifs that may function as transcription factor binding sites. Current methods often report large numbers of motifs, making it difficult to perform further analyses and experimental validation. The motif selection problem seeks to identify a minimal set of putative regulatory motifs that characterize sequences of interest (e.g. ChIP-Seq binding regions). RESULTS: In this study, the motif selection problem is mapped to variants of the set cover problem that are solved via tabu search and by relaxed integer linear programing (RILP). The algorithms are employed to analyze 349 ChIP-Seq experiments from the ENCODE project, yielding a small number of high-quality motifs that represent putative binding sites of primary factors and cofactors. Specifically, when compared with the motifs reported by Kheradpour and Kellis, the set cover-based algorithms produced motif sets covering 35% more peaks for 11 TFs and identified 4 more putative cofactors for 6 TFs. Moreover, a systematic evaluation using nested cross-validation revealed that the RILP algorithm selected fewer motifs and was able to cover 6% more peaks and 3% fewer background regions, which reduced the error rate by 7%. AVAILABILITY AND IMPLEMENTATION: The source code of the algorithms and all the datasets are available at https://github.com/YichaoOU/Set_cover_tools. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The International Society of Computational Biology and Bioinformatics (ISCB) brings together scientists from a wide range of disciplines, including biology, medicine, computer science, mathematics and statistics.Practitioners in these fields are constantly dealing with information in visual form: from microscope images and photographs of gels to scatter plots, network graphs and phylogenetic trees, structural formulae and protein models to flow diagrams, visual aids for problem-solving are omnipresent.The ISCB Art in Science Competition 2017 at the ISCB/ECCB 2017 conference in Prague offered a way to show the beauty of science in art form.Past artworks in this annual exhibition at ISMB combined outstanding beauty and aesthetics with deep insight that perfectly validated the exhibit's approach or went beyond the problem's solution.Others were surprising and inspiring through the transition from science to art, opening eyes and minds to reflect on the work being undertaken.Thirty unique pieces were showcased in the Art in Science competition at ISCB/ECCB 2017 in Prague.There winners (reproduced below) were selected by the Art in Science review committee (Figs 123).

Bioinformatics is recognized as part of the essential knowledge base of numerous career paths in biomedical research and healthcare. However, there is little agreement in the field over what that knowledge entails or how best to provide it. These disagreements are compounded by the wide range of populations in need of bioinformatics training, with divergent prior backgrounds and intended application areas. The Curriculum Task Force of the International Society of Computational Biology (ISCB) Education Committee has sought to provide a framework for training needs and curricula in terms of a set of bioinformatics core competencies that cut across many user personas and training programs. The initial competencies developed based on surveys of employers and training programs have since been refined through a multiyear process of community engagement. This report describes the current status of the competencies and presents a series of use cases illustrating how they are being applied in diverse training contexts. These use cases are intended to demonstrate how others can make use of the competencies and engage in the process of their continuing refinement and application. The report concludes with a consideration of remaining challenges and future plans.

Data mining algorithms and sequencing methods (such as RNA-seq and ChIP-seq) are being combined to discover genomic regulatory motifs that relate to a variety of phenotypes. However, motif discovery algorithms often produce very long lists of putative transcription factor binding sites, hindering the discovery of phenotype-related regulatory elements by making it difficult to select a manageable set of candidate motifs for experimental validation. To address this issue, the authors introduce the motif selection problem and provide coverage-based search heuristics for its solution. Analysis of 203 ChIP-seq experiments from the ENCyclopedia of DNA Elements project shows that our algorithms produce motifs that have high sensitivity and specificity and reveals new insights about the regulatory code of the human genome. The greedy algorithm performs the best, selecting a median of two motifs per ChIP-seq transcription factor group while achieving a median sensitivity of 77 percent.

Starting a professional society is not something that should be entered into lightly: it requires work and dedication that can detract from your research projects and other career objectives [15]. It certainly should not be attempted on your own. But there are many potential benefits and rewards in terms of promoting the profile of your discipline (which, in turn, can affect your grant success), boosting your own profile, developing useful management and leadership skills, finding mentors, and forming essential contacts and partnerships, as science is becoming increasingly collaborative. A successful society will be a source of lifelong learning and new ideas, will open up career opportunities for students and investigators, and will provide a much stronger voice for your discipline than an isolated scientist.

The Curriculum Task Force (CTF) of ISCB’s Education Committee seeks to define curricular guidelines for those who educate or train bioinformatics professionals at all career stages. A recent report of the CTF [1] presented a draft set of bioinformatics core competencies, derived from the results of surveys of (1) core facility directors, (2) career opportunities, and (3) existing curricula. Since the publication of its 2014 report, the CTF has focused on the application of the guidelines in varied contexts to identify areas where refinement is needed. As a first step, the task force held an open meeting at the ISMB conference in July 2014. The ideas discussed at the meeting spawned four working groups (WGs), which focus on (i) defining core competencies for specific types and levels of bioinformatics training, (ii) mapping the curriculum guidelines and competencies to existing materials in order to identify the need for development of new materials, and (iii) identifying where revision of the guidelines may be valuable. The CTF is engaging the ISCB community through open WG meetings at ISCB’s official conferences. Thus far, the WGs have convened at the ISCB Great Lakes Bioinformatics Conference (Purdue University, May 2015) and at the ISMB/ECCB Conference (Dublin, Ireland, July 2015). Additionally, the CTF held a workshop at the Annual General Meeting of the Global Organization of Bioinformatics Learning, Education and Training (Cape Town, South Africa, November 2015). Specifically, the draft competencies have been employed in a wide range of activities and contexts (see Table 1 and [2–11]), including the development of new curricula, the analysis of existing curricula, and the creation of new roles involving bioinformatics. These activities have resulted in the identification of several areas where refinement would be useful: Table 1 Summary of the activities of the ISCB Curriculum Task Force. Identify different levels or phases of competency. It would be helpful to define different phases of competency development, or different levels of competency appropriate for distinct roles. Define competency profiles for disciplines that don’t fit into our current silos. Bioengineering provides an illustrative example of a discipline that requires core competency in bioinformatics but does not fit into our current categories. There are almost certainly others. It would be helpful if we could provide some guidance on how to produce ‘hybrid’ competency profiles, perhaps borrowing some competencies from the TF’s core set and others from different disciplines. The LifeTrain initiative (www.lifetrain.eu) [2, 3] is collecting competency profiles for a range of disciplines of relevance to the biomedical sciences and may provide a useful resource kit for this. Broaden the scope of the competency profiles in response to cutting-edge and emerging research. Current areas requiring improvement include incorporating competencies that capture a fundamental understanding of the biological principles central to analyzing biomolecular data, and broadening the user WG to include applications beyond medicine. Provide guidance on the evidence required to assess whether someone has acquired each competency. For undergraduate, Master’s and PhD programs, learning outcomes for each competency, perhaps with examples of appropriate means of assessment, would be valuable. For established professionals who need to assimilate competencies into their working lives, a different approach may be required (such as keeping a portfolio to capture evidence of competency); the CTF should seek guidance from relevant professional bodies, especially in regulated professions such as healthcare. Provide indicative course content or examples of programs that map to the competency requirements. We do not wish to prescribe what course providers should teach or how they should teach it; however, if a course provider is designing a course to meet a specific competency requirement, it may be helpful to find examples of other programs that do this successfully. One way of achieving this is by mapping existing training content to the TF’s competencies. Another way might be to provide an indication, perhaps based on several courses, of the course content that would meet the competency requirements. This would give course providers the freedom to build their own course syllabi without having to reinvent the wheel. Initiatives to collect examples of Creative Commons (or otherwise reusable) course materials will provide an extremely valuable bank of training materials that could be mapped to the core competencies.

The Great Lakes Bioinformatics Consortium (GLBC) is pleased to announce its ninth annual conference, the Great Lakes Bioinformatics Conference (GLBIO), to be held May 16–18, 2014 in Cincinnati, OH. GLBIO 2014 will be hosted by Cincinnati Children’s Hospital Medical Center in conjunction with the University of Cincinnati. The conference, an official conference of the International Society for Computational Biology (ISCB), provides an interdisciplinary forum for the discussion of research findings and methods, and development of long-term relationships and networking opportunities, for researchers within the region, as well as from around the world. The program will include oral presentations, poster presentations, invited keynote speakers and tutorials. From novice to expert, attendees partake in a variety of workshops, tutorials, presentations, posters, networking events and exhibits. Keynote speakers include Gary Bader, The Donnelly Centre at the University of Toronto; Tanya Y. Berger-Wolf, Department of Computer Science, University of Illinois; Charles Brooks, University of Michigan and Mike Hawrylycz, Allen Institute for Brain Science. Hands-on tutorials will be led by Sorin Draghici, Wayne State University (advanced gene network); Anil Jegga, Children’s Hospital Medical Center, University of Cincinnati (advanced gene network); Jarek Meller, Children’s Hospital Medical Center, University of Cincinnati (an introduction to bioinformatics); Isaac Neuhaus, University of CA at San Francisco (visualization web interface JavaScript for programmers); Larsson Omberg, Sage Bionetworks (an introduction to Sage Synapys platform) and more! Interested in being a part of this dynamic group of speakers? See the GLBIO 2014 Web site for details and links, at www.iscb.org/glbio. GLBIO 2014 will also feature professional and career development sessions sponsored by Federation of American Societies of Experimental Biology (FASEB) Minority Access to Research Careers (MARC). This unique program will include a career fair, wherein students will receive career guidance (including a curriculum vitae (CV) critique) and will have the opportunity to meet with recruiters. Conference educational session topics will include Algorithm Development and Machine Learning, Bioimage Analysis, Biological Networks, Chemical Biology, Disease Models and Molecular Medicine, Evolutionary, Comparative and Metagenomics and many more! GLBIO has established a strong reputation for building relationships among a nationally prominent bioscience research community, showcasing the North American Great Lakes region as a perfect place to conduct computer-aided research in the life sciences. Of the 250 attendees of GLBIO 2013, 70% of conference attendees said they would attend the 2014 conference and 96% stated they would recommend the GLBIO conference to a colleague. For more information, please go to www.iscb.org/glbio to learn more about this exciting and unique gathering of industry experts and collegiate giants. Mark your calendar today and join us in Cincinnati at GLBIO 2014! Interested in supporting GLBIO 2014 through sponsorship or exhibiting? Please contact Stacy Slagor, Director of Corporate Relations and Development, ISCB, at [email protected]. About the Great Lakes Bioinformatics Consortium: The Great Lakes Bioinformatics Consortium strives to enhance educational opportunities and research infrastructure throughout the region, to make the Great Lakes a world leader in bioinformatics and to facilitate new discoveries in data-intensive biological research. The annual research meeting (GLBIO) serves as an informal communication and networking forum for professional development. We believe that by bringing together the Great Lakes bioinformatics community on a regular basis, many new initiatives will be born. The GLBC foresees development of regional research center grant proposals to identify central strengths for research centers in the Great Lakes region and to create funded centers for bioinformatics research. Additionally, the GLBC envisions scholarship and training investments that are focused on developing talent within the Great Lakes region. About the International Society for Computational Biology : The ISCB (www.iscb.org) is the sole society representing computational biology and bioinformatics on a worldwide scale. ISCB serves a global community of >3000 scientists who are dedicated to advancing the scientific understanding of living systems through computation. It convenes the world’s experts and future leaders in top conferences, including the Intelligent Systems in Molecular Biology (ISMB) Conference, and features journals that promote discovery and expand access to computational biology and bioinformatics. It delivers valuable information about training, education, employment and other relevant news. ISCB also provides an influential voice on government policies and scientific policies that are important to its members and to the general public.

Rapid advances in the life sciences and in related information technologies necessitate the ongoing refinement of bioinformatics educational programs in order to maintain their relevance. As the discipline of bioinformatics and computational biology expands and matures, it is important to characterize the elements that contribute to the success of professionals in this field. These individuals work in a wide variety of settings, including bioinformatics core facilities, biological and medical research laboratories, software development organizations, pharmaceutical and instrument development companies, and institutions that provide education, service, and training. In response to this need, the Curriculum Task Force of the International Society for Computational Biology (ISCB) Education Committee seeks to define curricular guidelines for those who train and educate bioinformaticians. The previous report of the task force summarized a survey that was conducted to gather input regarding the skill set needed by bioinformaticians [1]. The current article details a subsequent effort, wherein the task force broadened its perspectives by examining bioinformatics career opportunities, surveying directors of bioinformatics core facilities, and reviewing bioinformatics education programs.

The International Society for Computational Biology (ISCB) Education Committee (EduComm) promotes worldwide education and training in computational biology and bioinformatics and serves as a resource and advisor to organizations interested in developing educational programs. The topic of curricula for bioinformatics programs has long been of interest to ISCB and EduComm. Dr. Russ Altman, a founding board member and past president of ISCB, has been associated with one of the first bioinformatics degree programs (at Stanford University) and wrote an article on this topic [1]. Dr. Shoba Ranganathan, as chair of EduComm a decade ago, began organizing a yearly Workshop on Education in Bioinformatics (WEB) at Intelligent Systems for Molecular Biology (ISMB) meetings that generated exchange of information and many productive discussions. Curriculum development was one aspect of bioinformatics education covered in these sessions [2].

BACKGROUND: An important focus of genomic science is the discovery and characterization of all functional elements within genomes. In silico methods are used in genome studies to discover putative regulatory genomic elements (called words or motifs). Although a number of methods have been developed for motif discovery, most of them lack the scalability needed to analyze large genomic data sets. METHODS: This manuscript presents WordSeeker, an enumerative motif discovery toolkit that utilizes multi-core and distributed computational platforms to enable scalable analysis of genomic data. A controller task coordinates activities of worker nodes, each of which (1) enumerates a subset of the DNA word space and (2) scores words with a distributed Markov chain model. RESULTS: A comprehensive suite of performance tests was conducted to demonstrate the performance, speedup and efficiency of WordSeeker. The scalability of the toolkit enabled the analysis of the entire genome of Arabidopsis thaliana; the results of the analysis were integrated into The Arabidopsis Gene Regulatory Information Server (AGRIS). A public version of WordSeeker was deployed on the Glenn cluster at the Ohio Supercomputer Center. CONCLUSION: WordSeeker effectively utilizes concurrent computing platforms to enable the identification of putative functional elements in genomic data sets. This capability facilitates the analysis of the large quantity of sequenced genomic data.

In this paper we describe some utilizing conditions of a recently published tool that offers two basic functions for the classical problem of discovering motifs in a set of promoter sequences. For the first it is assumed that not necessarily all of the sequences possess a common motif of given length l. In this case, CHECKPROMOTER allows an exact identification of maximal subsets of related promoters. The purpose of this program is to recognize putatively co-regulated genes. The second, CHECKMOTIF, solves the problem of checking if the given promoters have a common motif. It uses a fast approximation algorithm for which we were able to derive non-trivial low performance bounds (defined as the ratio of Hamming distance of the obtained solution to that of a theoretically best solution) for the computed outputs. Both programs use a novel weighted Hamming distance paradigm for evaluating the similarity of sets of l-mers, and we are able to compute performance bounds for the proposed motifs. A set of At promoters were used as a benchmark for a comparative test against five known tools. It could be verified that SiteSeeker significantly outperformed these tools.

Some distributed real-time systems interact with external environments that change dynamically, and it is necessary to take the external variables into account when performing task allocation. We developed an approximation algorithm for task allocation, and it finds allocations that are maximally robust against dynamic changes in multiple external variables. Such an algorithm will help to reduce expensive reallocations triggered by changes in unpredictable environments. The algorithm has a polynomial running time, and its robustness optimality is given by an approximation ratio, which equals 2.41 asymptotically, when workloads are large and workload independent utilization of tasks is insignificant.

Integration of middleware scheduling and resource management services enables open distributed real-time embedded (DRE) applications to meet end-to-end quality of service (QoS) requirements in highly variable operating environments. This paper describes our research on integrating CORBA scheduling and resource management services, and presents experiments we conducted to validate and quantify the benefits of this integration. Our experimental results show that integrating distributed scheduling and resource management in middleware for open DRE systems can offer significant improvements in predictability. Specifically, integrating our stand-alone resource management service with a previously unmanaged experimental baseline application reduced the ratio of missed deadlines from 26% to 10%, and the same application performed even better under the control of integrated scheduling and resource management services, with a missed deadline ratio of only 1%.

Summary form only given. We propose architecture and a general optimization framework for dynamic, distributed real-time systems. Interesting features of this model include the consideration of adaptive applications and utility functions. We extend by formalizing the corresponding multicriterial optimization problem. As the most difficult part of this problem, we identified the evaluation and comparison of the quality of single allocations and sets of allocations, respectively. To this end, we propose and examine metrics for measuring the goodness of solutions within our general resource management framework. These metrics lay the basis for further work on developing both online and offline algorithms to tackle the general optimization problem and provide an efficient adaptive resource manager for dynamic, distributed real-time systems.

Summary form only given. We describe the quality-based adaptive resource management architecture, QARMA, a framework for resource management within CORBA. QARMA consists of three major components: the system repository service, the resource management service, and the enactor service. QARMA serves as a basis for integration of existing CORBA services and management mechanisms into a single, coherent framework for resource management. QARMA supports the management of a wide variety of applications developed using various development paradigms, easily integrates with other management and infrastructure components that already exist as CORBA services, and is easily extended to allow the use of new resource management mechanisms as they become available.

Summary form only given. We examine several heuristic algorithms for the maximum allowable workload (MAW) problem for real-time systems with tasks having variable workloads. Briefly, the problem concerns the allocation of tasks to m processors, where each task t is characterized by a function t.r(w) that gives the running time of the task in terms of its workload (or input size) w. The objective of the maximum allowable workload problem is to find an allocation of tasks to processors so that the allocation is feasible (no task misses its deadline) when each task is given a workload of w or smaller and w is maximized. This optimization problem uses a robustness measure that is closely related to the MAIL (maximum allowable increase in load) metric recently proposed by Gertphol et al. The main contribution of this paper is the comparison of several heuristic algorithms for the MAW-RMS problem. Hillclimbing, random search, simulated annealing, and first-fit heuristics are presented and evaluated via simulation. As we show here, the first-fit greedy heuristic produces solutions of a reasonable quality compared to the other algorithms. In addition, we demonstrate the applicability of our model in air defense systems.

This paper presents a characterization of various current approaches to quality of service (QoS) management in distributed, real-time systems. The characterization is based on an eight-point comparison of selected research: middleware interface, handling of violations, support of distributed applications, monitored data, requirements specification, characteristics of the supported real-time systems, overall system architecture, and quality of service dimensions supported. The comparisons are summarized in a tabular form with key references for further reading.

Abstract—This paper describes a test-bed for technology that unifies agent based computing and adaptive resource management for dynamic real-time systems. We describe a unified framework that combines a hybrid agent based architecture with explicit resource adapting mechanisms. I.

Real-time computing models that are based on benefit (also called utility and value) offer a generic paradigm that captures the spectrum from hard- to firm- to soft-realtime requirements. Furthermore, it allows robust, flexible real-time systems to be developed. Thus, it is the authors' opinion that benefit will become increasingly important in the theory and the practice of real-time computing. This paper discusses the notion of benefit in real-time systems and considers issues that must be addressed in order to fully exploit benefit-based models. It discusses how benefit is used in a variety of real-time paradigms and in example applications. It also identifies various types of benefit and presents a taxonomy that organizes the types. 1

Some classes of real-time systems operate in environments that cannot be modeled with static approaches. In such an environment, we neither have a priori knowledge about the system workload, nor is it possible to have a priori knowledge about worst-case execution time (WCET). There is no guarantee that all the deadlines of the periodic tasks will be met by using the rate monotonic analysis (RMA) approach. This paper presents an empirical and space-efficient way to predict the execution time. Experimental results have shown that for the dynamic real-time system, the best approach is a combination of static system profiling and dynamic prediction.

Time constrained systems which operate in dynamic environments may have unknown worst case scenarios, may have large variances in the sizes of the data and event sets that they process (and thus, have large variances in execution latencies and resource requirements), and may not be statically characterizable, even by time invariant statistical distributions. The paper presents a specification language for describing environment dependent features. Also presented is an abstract model that is constructed (statically) from the specifications, and is augmented (dynamically,) with the state of environment dependent features. The model is used to define techniques for QoS (quality of service) monitoring, QoS diagnosis, and resource allocation analysis. Experimental results show the effectiveness of the approach for specification of real time QoS, detection and diagnosis of QoS failures, and restoration of acceptable QoS via reallocation of distributed computer and network resources.

This paper defines a new paradigm for high performance embedded systems. We present a model of distributed embedded control system software to capture the real-time computing requirements of complex computer-based systems. The hierarchical software architecture defines the notion of a software path the construct identified by studying embedded real-time applications. We present a technique for dynamic scheduling of sporadic paths. The novel feature of the approach is to enhance schedulability through high performance concurrent computing.

This article presents a process for the reengineering of computer-based control systems, and describes tools that automate portions of the process. The intermediate representation (IR) for capturing features of computer-based systems during reverse engineering is presented. A novel feature of the IR is that it incorporates the control system software architecture, a view that enables information to be captured at five levels of granularity: the program level, the task level, the package level, the subprogram level, and the statement level. A reverse engineering toolset that constructs the IR from Ada programs, displays the IR, and computes concurrency, communication and object-orientedness metrics is presented. Also described is the design of hypermedia techniques that enhance the usability of the reverse engineering tools.

An abstract data type mechanism is provided by many modern programming languages, and is often employed during system development to promote modularity and reuse. This paper describes ARC, a parallel virtual machine designed for executing programs that use abstract data types (ADTs). The major contribution of ARC is that it supports Asynchronous Remote Procedure Call (ARPC), a model of parallel execution that works well for programs developed by layering ADTs. To support ARPC, ARC performs data synchronization, automatic parameter restoration, and dynamic load balancing.>

For widespread reuse in a component-based software industry, a component must be designed and developed to be reused. Benefits of reuse are maximized when a component is reused “as is” (possibly with provisions for expected customization, such as through parameters), based only on its specification. The expression of the specification of a component is crucial in this setting. The specification must be formal, yet understandable, as well as abstract and implementation-independent. The specification also must make it possible to demonstrate correctness of an implementation of the specification and permit formal reasoning about its behavior in a client program. This paper explains how it is possible to write specifications with these properties in RESOLVE, a conceptual framework that we have developed for constructing reusable software components.