mRUBiS: An Exemplar for Model-Based Architectural Self-Healing and Self-Optimization

Self-adaptive software systems are often structured into an adaptation engine that manages an adaptable software by operating on a runtime model that represents the architecture of the software (model-based architectural self-adaptation). Despite the popularity of such approaches, existing exemplars provide application programming interfaces but no runtime model to develop adaptation engines. Consequently, there does not exist any exemplar that supports developing, evaluating, and comparing model-based self-adaptation off the shelf. Therefore, we present mRUBiS, an extensible exemplar for model-based architectural self-healing and self-optimization. mRUBiS simulates the adaptable software and therefore provides and maintains an architectural runtime model of the software, which can be directly used by adaptation engines to realize and perform self-adaptation. Particularly, mRUBiS supports injecting issues into the model, which should be handled by self-adaptation, and validating the model to assess the self-adaptation. Finally, mRUBiS allows developers to explore variants of adaptation engines (e.g., event-driven self-adaptation) and to evaluate the effectiveness, efficiency, and scalability of the engines

Selection of third party software in Off-The-Shelf-based software development: an interview study with industrial practitioners

The success of software development using third party components highly depends on the ability to select a suitable component for the intended application. The evidence shows that there is limited knowledge about current industrial OTS selection practices. As a result, there is often a gap between theory and practice, and the proposed methods for supporting selection are rarely adopted in the industrial practice. This paper's goal is to investigate the actual industrial practice of component selection in order to provide an initial empirical basis that allows the reconciliation of research and industrial endeavors. The study consisted of semi-structured interviews with 23 employees from 20 different software-intensive companies that mostly develop web information system applications. It provides qualitative information that help to further understand these practices, and emphasize some aspects that have been overlooked by researchers. For instance, although the literature claims that component repositories are important for locating reusable components; these are hardly used in industrial practice. Instead, other resources that have not received considerable attention are used with this aim. Practices and potential market niches for software-intensive companies have been also identified. The results are valuable from both the research and the industrial perspectives as they provide a basis for formulating well-substantiated hypotheses and more effective improvement strategies.Peer ReviewedPostprint (author's final draft

Diversity with AntiVirus products: Additional empirical studies

In this paper we describe the design of a new set of empirical studies we will run to test the gains in detection capabilities from using diverse AntiVirus products. This new work builds on previous work on this topic reported in [1, 2, 3]. We describe the motivation for this work, how it extends the previous work and what studies we will conduct

An Experimental Study of Reduced-Voltage Operation in Modern FPGAs for Neural Network Acceleration

We empirically evaluate an undervolting technique, i.e., underscaling the circuit supply voltage below the nominal level, to improve the power-efficiency of Convolutional Neural Network (CNN) accelerators mapped to Field Programmable Gate Arrays (FPGAs). Undervolting below a safe voltage level can lead to timing faults due to excessive circuit latency increase. We evaluate the reliability-power trade-off for such accelerators. Specifically, we experimentally study the reduced-voltage operation of multiple components of real FPGAs, characterize the corresponding reliability behavior of CNN accelerators, propose techniques to minimize the drawbacks of reduced-voltage operation, and combine undervolting with architectural CNN optimization techniques, i.e., quantization and pruning. We investigate the effect of environmental temperature on the reliability-power trade-off of such accelerators. We perform experiments on three identical samples of modern Xilinx ZCU102 FPGA platforms with five state-of-the-art image classification CNN benchmarks. This approach allows us to study the effects of our undervolting technique for both software and hardware variability. We achieve more than 3X power-efficiency (GOPs/W) gain via undervolting. 2.6X of this gain is the result of eliminating the voltage guardband region, i.e., the safe voltage region below the nominal level that is set by FPGA vendor to ensure correct functionality in worst-case environmental and circuit conditions. 43% of the power-efficiency gain is due to further undervolting below the guardband, which comes at the cost of accuracy loss in the CNN accelerator. We evaluate an effective frequency underscaling technique that prevents this accuracy loss, and find that it reduces the power-efficiency gain from 43% to 25%.Comment: To appear at the DSN 2020 conferenc

Fault tolerance via diversity for off-the-shelf products: A study with SQL database servers

If an off-the-shelf software product exhibits poor dependability due to design faults, then software fault tolerance is often the only way available to users and system integrators to alleviate the problem. Thanks to low acquisition costs, even using multiple versions of software in a parallel architecture, which is a scheme formerly reserved for few and highly critical applications, may become viable for many applications. We have studied the potential dependability gains from these solutions for off-the-shelf database servers. We based the study on the bug reports available for four off-the-shelf SQL servers plus later releases of two of them. We found that many of these faults cause systematic noncrash failures, which is a category ignored by most studies and standard implementations of fault tolerance for databases. Our observations suggest that diverse redundancy would be effective for tolerating design faults in this category of products. Only in very few cases would demands that triggered a bug in one server cause failures in another one, and there were no coincident failures in more than two of the servers. Use of different releases of the same product would also tolerate a significant fraction of the faults. We report our results and discuss their implications, the architectural options available for exploiting them, and the difficulties that they may present

Enhancing Fault / Intrusion Tolerance through Design and Configuration Diversity

Fault/intrusion tolerance is usually the only viable way of improving the system dependability and security in the presence of continuously evolving threats. Many of the solutions in the literature concern a specific snapshot in the production or deployment of a fault-tolerant system and no immediate considerations are made about how the system should evolve to deal with novel threats. In this paper we outline and evaluate a set of operating systems’ and applications’ reconfiguration rules which can be used to modify the state of a system replica prior to deployment or in between recoveries, and hence increase the replicas chance of a longer intrusion-free operation

Modeling and Simulating a Software Architecture Design Space

Frequently, a similar type of software system is used in the implementation of many different software applications. Databases are an example. Two software development approaches are common to Þll the need for instances from a class of similar systems: (1) repeated custom development of similar instances, one for each different application, or (2) development of one or more general purpose off-the-shelf systems that are used many times in the different applications. Each approach has advantages and disadvantages. Custom development can closely match the requirements of an application, but has an associated high development cost. General purpose systems may have a lower cost when amortized across multiple applications, but may not closely match the requirements of all the different applications. It can be difÞcult for application developers to determine which approach is best for their application. Do any of the existing off-the-shelf systems sufÞciently satisfy the application requirements? If so, which ones provide the best match? Would a custom implementation be sufÞciently better to justify the cost difference between an off-the-shelf solution? These difÞcult buy-versus-build decisions are extremely important in todayÕs fastpaced, competitive, unforgiving software application market. In this thesis we propose and study a software engineering approach for evaluating how well off-the-shelf and custom software architectures within the design space of a class of OODB systems satisfy the requirements for different applications. The approach is based on the ability to explicitly enumerate and represent the key dimensions of commonality and variability in the space of OODB designs. We demonstrate that modeling and simulation of OODB software architectures can be used to help software developers rapidly converge on OODB requirements for an application and identify OODB software architectures that satisfy those requirements. The technical focus of this work is on the circular relationships between requirements, software architectures, and system properties such as OODB functionality, size, and performance. We capture these relationships in a parametrized OODB architectural model, together with an OODB simulation and modeling tool that allows software developers to reÞne application requirements on an OODB, identify corresponding custom and offthe- shelf OODB software architectures, evaluate how well the software architecture properties satisfy the application requirements, and identify potential reÞnements to requirements

Choosing a Company's Building Design: Models for Strategic Design Decisions

Improving the linkage between real estate strategy and building design can help competitive business strategy. Differentiating building design from product design is important. Problems in making design choices derive from received paradigmatic knowledge that misrepresents the design decision processes. Architectural selection problems are explained with reference to design decision processes and dilemmas of testing the design. Because comparison is the underlying method of evaluation, the design competition is discussed as a model to evaluate the design of a company’s proposed high profile buildings in relation to corporate strategy. The Appendix describes the process and the recent and past history of competitions.

The Knowledge Application and Utilization Framework Applied to Defense COTS: A Research Synthesis for Outsourced Innovation

Purpose -- Militaries of developing nations face increasing budget pressures, high operations tempo, a blitzing pace of technology, and adversaries that often meet or beat government capabilities using commercial off-the-shelf (COTS) technologies. The adoption of COTS products into defense acquisitions has been offered to help meet these challenges by essentially outsourcing new product development and innovation. This research summarizes extant research to develop a framework for managing the innovative and knowledge flows. Design/Methodology/Approach – A literature review of 62 sources was conducted with the objectives of identifying antecedents (barriers and facilitators) and consequences of COTS adoption. Findings – The DoD COTS literature predominantly consists of industry case studies, and there’s a strong need for further academically rigorous study. Extant rigorous research implicates the importance of the role of knowledge management to government innovative thinking that relies heavily on commercial suppliers. Research Limitations/Implications – Extant academically rigorous studies tend to depend on measures derived from work in information systems research, relying on user satisfaction as the outcome. Our findings indicate that user satisfaction has no relationship to COTS success; technically complex governmental purchases may be too distant from users or may have socio-economic goals that supersede user satisfaction. The knowledge acquisition and utilization framework worked well to explain the innovative process in COTS. Practical Implications – Where past research in the commercial context found technological knowledge to outweigh market knowledge in terms of importance, our research found the opposite. Managers either in government or marketing to government should be aware of the importance of market knowledge for defense COTS innovation, especially for commercial companies that work as system integrators. Originality/Value – From the literature emerged a framework of COTS product usage and a scale to measure COTS product appropriateness that should help to guide COTS product adoption decisions and to help manage COTS product implementations ex post