Software Engineering Standards Research Articles

A comprehensive review of techniques for documenting artificial intelligence

PurposeCompanies are increasingly benefiting from artificial intelligence (AI) applications in various domains, but also facing its negative impacts. The challenge lies in the lack of clear governance mechanisms for AI. While documentation is a key governance tool, standard software engineering practices are inadequate for AI. Practitioners are unsure about how to document AI, raising questions about the effectiveness of current documentation guidelines. This review examines whether AI documentation guidelines meet regulatory and industry needs for AI applications and suggests directions for future research.Design/methodology/approachA structured literature review was conducted. In total, 38 papers from top journals and conferences in the fields of medicine and information systems as well as journals focused on fair, accountable and transparent AI were reviewed.FindingsThis literature review contributes to the literature by investigating the extent to which current documentation guidelines can meet the documentation requirements for AI applications from regulatory bodies and industry practitioners and by presenting avenues for future research. This paper finds contemporary documentation guidelines inadequate in meeting regulators’ and professionals’' expectations. This paper concludes with three recommended avenues for future research.Originality/valueThis paper benefits from the insights from comprehensive and up-to-date sources on the documentation of AI applications.

The Advanced Computing Hub at BSC: improving fusion codes following modern software engineering standards

Several dedicated High-Performance Computing (HPC) centers provide essential expertise and support in developing a suitable portfolio of EUROfusion standard codes. Barcelona Supercomputing Center (BSC) is one of these HPC hubs involved in this complex task. Several fusion codes were selected, installed and analyzed to meet the developers’ requirements, ranging from portability to GPU, improving the performance, getting better data management, extending the capacity of coupling with other codes, etc. In this paper, we will describe the work developed by BSC and some of the tasks carried out in this project. We will explain briefly how the project is faced and the work required to create good quality codes, i.e. robust and trustable software capable of running efficiently in modern HPC systems.

Detecting and resolving feature envy through automated machine learning and move method refactoring

Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.

Standards relevant to automated driving system safety: A systematic assessment

Automated Driving Systems (ADSs) in road vehicles, which can undertake the dynamic driving task without requiring a human driver, are on the verge of large-scale deployment. Assurance frameworks for vehicle systems have traditionally been underpinned by standards. Some commonly adopted standards will provide barriers to the market deployment of ADSs, particularly the inherent capability of ADSs to have their driving functionality changed using Machine Learning (ML) during in-service operation. New standards specific to ADSs are being adopted, but some of these also present challenges for ML-enabled system changes. Then there are emerging cross-sector AI and ML standards that will have implications for the automotive industry and regulators.This paper summarises an in-depth assessment of standards that are anticipated to play an important role in the safety assurance of ADSs. Summarised findings are provided, including key themes, covering issues such as the use of ADS safety cases that are strengthened by adopting complementary standards, ensuring safety assurance models cover the whole ADS lifecycle, and the use of a systems engineering approach that treats safety as a dynamic control problem and appropriately integrates software engineering standards. Other themes were more specific to ML, including the need for rigorous change processes, horizonal AI and ML standards to be appropriately considered by automotive manufacturers and regulators, and authorities to be clear on whether online changes that can occur autonomously without human oversight are allowed or not. The findings, themes and recommendations in this paper are intended to inform future safety assurance frameworks for ADSs.

A Software Project That Partially Failed: A Small Organization That Ignored the Management and Technical Practices of Software Standards

We explore what went wrong when a small organization ignored the proven practices of a software engineering standard and what should have been done to meet the needs of this organization if the practices of software engineering standards have been used.

Computerized Study and Analysis Electrical Power Systems Parameters

In this paper, a program for analyzing potential events and designing preventive measures to ensure safe operation of electrical power systems was developed, which was published in the Journal of Al-Baath University. The new visual software system performs all the functions of the previous program, in addition to a set of developed options, studies and comparisons. It also features a graphical method for entering electrical network data and conforms to software engineering standards, with an analytical study based on an approved methodology, the Unified Modeling Language (UML). The spiral software model was chosen during the research, which made it possible to obtain a reliable software product that is characterized by the highest possible standards. In this paper, the parameters of the electrical power system on a 6-busbar network were analyzed and studied, and the effect of changing the power factor on the possibility of finding the optimal solution, whether by changing generation or by changing generation and decreasing loads, was studied. The program's effectiveness, flexibility and accuracy of results have been proven.

The unwanted effects of imprecise language in forensic science standards

The author has previously contributed to work on requirements definitions in digital forensic methods, and identified a potential gap which could not be fully explained at the time (Marshall and Paige, 2018). The former Forensic Science Regulator (FSR), with others, commented on this and challenged the finding (Tully et al., 2020). This paper re-addresses this issue and explores the issue of language used in the various standards from ISO/IEC 17 025 (2017) through to the FSR's own guidance on digital forensic method (Forensic Science Regulator, 2020), comparing it with language used in other related standards and in software engineering standards. From this, the author proposes that the language used by the FSR may cause an over-emphasis on establishing requirements for the ultimate end-user, to the detriment of requirements for purely internal use of processes. This can also result in overly complex methods, which are inherently difficult to fully validate, being produced. Furthermore, the use of overloaded terminology may also lead to confusion about some key concepts in the various stages of method validation and re-validation.

Combining Innovative Technology and Context based Approaches in Teaching Software Engineering

Sustainability in learning is very essential for a sustainable future which largely depends on education. Sustainable learning requires learners to increase and rebuild base-knowledge as the circumstances change and get more complex. This becomes very obvious particularly for in- formation technology (IT) discipline where technology is rapidly changing and practice getting more complicated. Sustainability enables students to use their learning from formal education into practice, provide hands on experience (HOE) and help them rebuild their knowledge base in complex situations. This is also essential to achieve a high graduate outcome rate (GOR) which helps the education sector to become sustainable. In the existing policies and frameworks, institutions are moving towards more off-campus learning and less face-to-face learning. As a result, a downward trend is experienced in students’ engagement across IT discipline. This affects students’ ability in achieving HOE and appears to be one of the reasons of low GOR which poses a threat to the sustainability in the education sector for both stakeholder and learners’ perspectives. This paper presents a combined approach of context-based teaching with incorporation of innovative technology to engage students and achieve a better HOE towards sustainability in learning. The proposed approach was adopted in a software engineering course taught at School of IT at Deakin University, Australia. Students were provided context-based teaching material and industry standard software engineering tools for practice to achieve HOE. Students evaluation and assessment results reports that proposed approach was significantly impacted positively to engage the students in classes towards improved sustainable learning.

An improved forensic-by-design framework for cloud computing with systems engineering standard compliance

“Forensic-by-design” is an emergent and ambitious paradigm that extends the Digital Forensic Readiness (DFR) perspective. Similar to Security-by-design, this new vision advocates the integration of Forensic requirements into the system's design and development stages to get “Forensic-ready” systems. While it seems promising, we hypothesize that: (a) this new alternative is not effective for some open boundaries systems, and (b) this strategy is not fully aligned with the Systems and software Engineering (SE) standards. A six phases research methodology based on systematic literature review, mapping, and analysis was adopted. Our results confirm indeed the stated hypothesis, identify missing key factors, and point out potential omissions. A new System and software Engineering driven Forensic-by-design framework, with an emphasis on Cloud computing systems, is therefore proposed.

Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks

Each year vast international resources are wasted on irreproducible research. The scientific community has been slow to adopt standard software engineering practices, despite the increases in high-dimensional data, complexities of workflows, and computational environments. Here we show how scientific software applications can be created in a reproducible manner when simple design goals for reproducibility are met. We describe the implementation of a test server framework and 40 scientific benchmarks, covering numerous applications in Rosetta bio-macromolecular modeling. High performance computing cluster integration allows these benchmarks to run continuously and automatically. Detailed protocol captures are useful for developers and users of Rosetta and other macromolecular modeling tools. The framework and design concepts presented here are valuable for developers and users of any type of scientific software and for the scientific community to create reproducible methods. Specific examples highlight the utility of this framework, and the comprehensive documentation illustrates the ease of adding new tests in a matter of hours.

Model-driven system-level validation and verification on the space software domain

The development process of on-board software applications can benefit from model-driven engineering techniques. Model validation and model transformations can be applied to drive the activities of specification, requirements definition, and system-level validation and verification according to the space software engineering standards ECSS-E-ST-40 and ECSS-Q-ST-80. This paper presents a model-driven approach to completing these activities by avoiding inconsistencies between the documents that support them and providing the ability to automatically generate the system-level validation tests that are run on the Ground Support Equipment and the matrices required to complete the software verification. A demonstrator of the approach has been built using as a proof of concept a subset of the functionality of the software of the control unit of the Energetic Particle Detector instrument on-board Solar Orbiter.

Developers perception of peer code review in research software development

Background: Research software is software developed by and/or used by researchers, across a wide variety of domains, to perform their research. Because of the complexity of research software, developers cannot conduct exhaustive testing. As a result, researchers have lower confidence in the correctness of the output of the software. Peer code review, a standard software engineering practice, has helped address this problem in other types of software. Aims: Peer code review is less prevalent in research software than it is in other types of software. In addition, the literature does not contain any studies about the use of peer code review in research software. Therefore, through analyzing developers perceptions, the goal of this work is to understand the current practice of peer code review in the development of research software, identify challenges and barriers associated with peer code review in research software, and present approaches to improve the peer code review in research software. Method: We conducted interviews and a community survey of research software developers to collect information about their current peer code review practices, difficulties they face, and how they address those difficulties. Results: We received 84 unique responses from the interviews and surveys. The results show that while research software teams review a large amount of their code, they lack formal process, proper organization, and adequate people to perform the reviews. Conclusions: Use of peer code review is promising for improving the quality of research software and thereby improving the trustworthiness of the underlying research results. In addition, by using peer code review, research software developers produce more readable and understandable code, which will be easier to maintain.

Development methodologies for ontology‐based knowledge management systems: A review

AbstractKnowledge management systems (KMS) are computer‐based systems highly valued in business organizations because they support knowledge management (KM) processes. Most KMS have been developed using non‐intelligent computer technology—that is, DMS, CMS, DBMS, and CIS—, and thus, they cannot provide advanced capabilities. Consequently, enhanced KMS using intelligent technologies of ontologies with inference engines—called ontology‐based knowledge management systems (OKMS)—have been proposed in the last three decades. Nowadays, however, the implementation of OKMS in real‐world settings is still scarce. Lack of comprehensive and systematic development methodologies including Project Management and Technical Systems Engineering processes—as the Systems and Software Systems Engineering standards propose—have been suggested as a factor that inhibits OKMS implementations. In this study, we review the OKMS literature (1990–2021 period)—from six seminal studies located using a research search engine—to assess OKMS development methodologies that can be considered comprehensive and systematic. Five methodologies were identified and assessed using an evaluation subset from the ISO/IEC/IEEE 15288:2015 Systems and Software Engineering standard. Two of them—CommonKADS and NeON—were found with a high comprehensive and systematic level and both are suggested for organizations interested in OKMS implementations, but none of them qualified as agile, which is a current development approach for systems and software systems. Hence, further empirical research toward the realization of comprehensive and systematic OKMSs development methodologies, including agile versions, is suggested for fostering the implementation of OKMS in real‐world settings.

Developments in Aerospace Software Engineering practices for VSEs: An overview of the process requirements and practices of integrated Maturity models and Standards

As part of the evolution of the Space market in the last years – globally referred to as Space 2.0 - small companies are playing an increasingly relevant role in different aerospace projects. Business incubators established by European Space Agency (ESA) and similar entities are evidence of the need of moving initiatives to small companies characterized by greater flexibility to develop specific activities. Software is a key component in most aerospace projects, and the success of the initiatives and projects usually depends on the capability of developing reliable software following well-defined standards. But small entities face some difficulties when adopting software development standards that have been conceived thinking on larger organizations and big programs. The need of defining software development standards tailored to small companies and groups is a permanent subject of discussion not only in the aerospace field, and has led in recent years to the publication of the ISO/IEC 29110 series of systems and software engineering standards and guides, aimed to solve the issues that Very Small Entities (VSEs) () – settings having up to twenty-five people -, found with other standards like CMMI® or SPICE. This paper discusses the tailoring defined by different aerospace organizations for VSEs in the aerospace industry, and presents a conceptual arrangement of the standard based on meta-modeling languages that allow the extension and full customization with the incorporation of specific software engineering requirements and practices from ECSS (European Cooperation for Space Standardization).

Beyond factors that motivate the adoption of the ISO/IEC 29110 in Mexico: An exploratory study of the implementation pace of this standard and the benefits observed

Around the world, the importance of Very Small Entities (VSEs), organisations having up to 25 people, has been constantly increasing. Worldwide, VSEs represent over 92% of the software industry. Therefore, two main needs can be highlighted: a) providing VSEs with resources to produce high-quality software, and b) training software engineering undergraduates in proven practices to produce high-quality software within the given schedule and budget. A logical way to meet these needs is transfering proven practices provided by software engineering standards. However, transferring the knowledge of software engineering standards is not always an easy task. The ISO/IEC 29110 is a series of international standards and guides that provide codified knowledge related to the software development process. The series was specifically developed to be used by VSEs. This study presents an exploratory analysis, conducted in 12 Mexican VSEs, which implemented the software Basic profile of the ISO/IEC 29110, to identify the pace at which they can adopt this standard to their environment. Besides, the benefits and difficulties encountered are provided. The results can be relevant for other VSEs interested in implementing this standard. Even if the exploratory analysis was performed in the VSEs of Mexico, this analysis can be of interest in other countries. The results obtained can help other VSEs that are interested in the adoption of this international standard to reduce the barriers to a successful implementation.

Not Teaching Software Engineering Standards to Future Software Engineers-Malpractice?

Software engineering standards are essential sources of codified knowledge for all software engineers. Could the professors who are not teaching software engineering standards to software engineering students be accused of malpractice?

Software Architecture and Software Design

Software architecture is defined as the strategic design of an activity concerned with global requirements. Its solution is implemented in programming paradigms, architectural styles, component-based software engineering standards, architectural patterns, security, scale, integration, and law-governed regularities. Functional design, also described as tactical design, is an activity concerned with local requirements governing a solution such as algorithms, design patterns, programming idioms, refactoring, and low-level implementation. In this paper, I would like to introduce some concepts of software architecture and software design, as well as the relationship between them

Domain-Specific Languages for IoT: Challenges and Opportunities

Internet of Things (IoT) is a multidisciplinary tool used by field experts to fabricate technology into their discipline; these fields experts thus need access to a simple, understandable and user-friendly programming language for this purpose. Domain-Specific Languages (DSL) have been developed to pave the way for such domain experts to integrate IoT capabilities into their everyday tasks. IoT is thus one of the main technologies targeting human day-to-day activities, and the concept of IoT has caused a general rethink and reimagining of the shape of life in the future. Many researchers are thus working on fields related to IoT such as networking, power consumption, data aggregation and fusion, finding ways to offer this new technology for end user access in a smooth and easy manner. Introducing new application development methods and using software engineering standards and tools that enable end-users to develop their own IoT applications is another aspect that has received attention in the last decade; however, this aspect requires more work from the research community. The main contribution of this paper is to highlight current efforts related to the IoT field and to perform quantitative analysis to highlight the current state of the art in both positive and negative terms, including the current limitations and obstacles faced by both end-users and field experts seeking to build their own IoT applications.

Software engineering standards for epidemiological models.

There are many tangled normative and technical questions involved in evaluating the quality of software used in epidemiological simulations. In this paper we answer some of these questions and offer practical guidance to practitioners, funders, scientific journals, and consumers of epidemiological research. The heart of our paper is a case study of the Imperial College London (ICL) covid-19 simulator, set in the context of recent work in epistemology of simulation and philosophy of epidemiology.

Software modernization to embrace quantum technology

Quantum Computing is becoming an increasingly mature area, with a simultaneous escalation of investment in many sectors. Quantum technology will revolutionize all the engineering fields. For example, companies will need to add quantum computing progressively to some or all of their daily operations. It is clear that all existing classical information systems cannot be done away with. Rather than that occurring, it is expected that some quantum algorithms will be added, so that they can work alongside classical information systems. There has been no systematic solution offered to deal with this challenge so far. This research proposes a software modernization approach (model-driven reengineering) designed to restructure classical systems to work in conjunction with quantum systems, thereby providing target environments that combine both of these computational paradigms. The approach proposed is systematic, and based on existing software engineering standards like the Knowledge Discovery Metamodel and the Unified Modelling Language. It could therefore be applied in industry in a way that complies with the existing software evolution processes. The independence of this proposal with respect to quantum programming environments is also guaranteed, making its application feasible in the changing environment in today's quantum industry. The main implication of this approach is technical, but also economic, since it enables the reuse of the knowledge embedded in legacy systems, while at the same time the new quantum-based projects are speeded up.