arXiv subjects

Stephen G. MacDonell

Publications and source records attributed to Stephen G. MacDonell.

At least 73 records · Page 4Linked to original sources

arXiv2021

A Baseline Model for Software Effort Estimation

Software effort estimation (SEE) is a core activity in all software processes and development lifecycles. A range of increasingly complex methods has been considered in the past 30 years for the prediction of effort, often with mixed and contradictory results. The comparative assessment of effort prediction methods has therefore become a common approach when considering how best to predict effort over a range of project types. Unfortunately, these assessments use a variety of sampling methods and error measurements, making comparison with other work difficult. This article proposes an automatically transformed linear model (ATLM) as a suitable baseline model for comparison against SEE methods. ATLM is simple yet performs well over a range of different project types. In addition, ATLM may be used with mixed numeric and categorical data and requires no parameter tuning. It is also deterministic, meaning that results obtained are amenable to replication. These and other arguments for using ATLM as a baseline model are presented, and a reference implementation described and made available. We suggest that ATLM should be used as a baseline of effort prediction quality for all future model comparisons in SEE.

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arXiv2021

The significance of user-defined identifiers in Java source code authorship identification

When writing source code, programmers have varying levels of freedom when it comes to the creation and use of identifiers. Do they habitually use the same identifiers, names that are different to those used by others? Is it then possible to tell who the author of a piece of code is by examining these identifiers? If so, can we use the presence or absence of identifiers to assist in correctly classifying programs to authors? Is it possible to hide the provenance of programs by identifier renaming? In this study, we assess the importance of three types of identifiers in source code author classification for two different Java program data sets. We do this through a sequence of experiments in which we disguise one type of identifier at a time. These experiments are performed using as a tool the Source Code Author Profiles (SCAP) method. The results show that, although identifiers when examined as a whole do not seem to reflect program authorship for these data sets, when examined separately there is evidence that class names do signal the author of the program. In contrast, simple variables and method names used in Java programs do not appear to reflect program authorship. On the contrary, our analysis suggests that such identifiers are so common as to mask authorship. We believe that these results have applicability in relation to the robustness of code plagiarism analysis and that the underlying methods could be valuable in cases of litigation arising from disputes over program authorship.

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arXiv2021

Understanding Technology Use in Global Virtual Teams: Research Methodologies and Methods

Context: The globalisation of activities associated with software development and use has introduced many challenges in practice and for research. While the predominant approach to research in software engineering has followed a positivist science model, this approach may be sub-optimal when addressing problems with a dominant social or cultural dimension, such as those frequently encountered when studying work practices in a globally distributed team setting. The investigation of such a team reported in this paper provides one example of an alternative approach to research in a global context, through a longitudinal interpretive field study seeking to understand how global virtual teams mediated the use of technology. Objective: Our focus in this paper is on the conduct of research in the context of global software activities, particularly as applied to the actions and interactions of global virtual teams. Method: We describe how we undertook a substantial field study of global virtual teams, and highlight how the adopted structuration theory enabled us to deliver effectively against our goals. Results: We believe that the approach taken suited a research context in which situated practices were occurring over time in a highly complex domain, ensuring that our results were both strongly grounded and relevant to practice. It has resulted in the generation of substantive theory and techniques that have been adapted and applied on a pilot basis in further field settings. Conclusion: We conclude that globally distributed teamwork presents a complex context which demands new research approaches, beyond the limited set customarily applied by software engineering researchers. We advocate experimenting with different research methodologies and methods so that we have a more rounded repertoire to address the most important and relevant issues in global software development research.(Abridged)

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arXiv2021

Causal Factors, Benefits and Challenges of Test-Driven Development: Practitioner Perceptions

This report describes the experiences of one organization's adoption of Test Driven Development (TDD) practices as part of a medium-term software project employing Extreme Programming as a methodology. Three years into this project the team's TDD experiences are compared with their non-TDD experiences on other ongoing projects. The perceptions of the benefits and challenges of using TDD in this context are gathered through five semi-structured interviews with key team members. Their experiences indicate that use of TDD has generally been positive and the reasons for this are explored to deepen the understanding of TDD practice and its effects on code quality, application quality and development productivity. Lessons learned are identified to aid others with the adoption and implementation of TDD practices, and some potential further research areas are suggested.

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arXiv2021

Catching up with Method and Process Practice: An Industry-Informed Baseline for Researchers

Software development methods are usually not applied by the book. Companies are under pressure to continuously deploy software products that meet market needs and stakeholders' requests. To implement efficient and effective development processes, companies utilize multiple frameworks, methods and practices, and combine these into hybrid methods. A common combination contains a rich management framework to organize and steer projects complemented with a number of smaller practices providing the development teams with tools to complete their tasks. In this paper, based on 732 data points collected through an international survey, we study the software development process use in practice. Our results show that 76.8% of the companies implement hybrid methods. Company size as well as the strategy in devising and evolving hybrid methods affect the suitability of the chosen process to reach company or project goals. Our findings show that companies that combine planned improvement programs with process evolution can increase their process' suitability by up to 5%.

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arXiv2021

Qualitative Research on Software Development: A Longitudinal Case Study Methodology

This paper reports the use of a qualitative methodology for conducting longitudinal case study research on software development. We provide a detailed description and explanation of appropriate methods of qualitative data collection and analysis that can be utilized by other researchers in the software engineering field. Our aim is to illustrate the utility of longitudinal case study research, as a complement to existing methodologies for studying software development, so as to enable the community to develop a fuller and richer understanding of this complex, multi-dimensional phenomenon. We discuss the insights gained and lessons learned from applying a longitudinal qualitative approach to an empirical case study of a software development project in a large multi-national organization. We evaluate the methodology used to emphasize its strengths and to address the criticisms traditionally made of qualitative research.

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arXiv2021

Walking Through the Method Zoo: Does Higher Education really meet Software Industry Demands?

Software engineering educators are continually challenged by rapidly evolving concepts, technologies, and industry demands. Due to the omnipresence of software in a digitalized society, higher education institutions (HEIs) have to educate the students such that they learn how to learn, and that they are equipped with a profound basic knowledge and with latest knowledge about modern software and system development. Since industry demands change constantly, HEIs are challenged in meeting such current and future demands in a timely manner. This paper analyzes the current state of practice in software engineering education. Specifically, we want to compare contemporary education with industrial practice to understand if frameworks, methods and practices for software and system development taught at HEIs reflect industrial practice. For this, we conducted an online survey and collected information about 67 software engineering courses. Our findings show that development approaches taught at HEIs quite closely reflect industrial practice. We also found that the choice of what process to teach is sometimes driven by the wish to make a course successful. Especially when this happens for project courses, it could be beneficial to put more emphasis on building learning sequences with other courses.

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arXiv2021

Factors that Affect Software Systems Development Project Outcomes: A Survey of Research

Determining the factors that have an influence on software systems development and deployment project outcomes has been the focus of extensive and ongoing research for more than 30 years. We provide here a survey of the research literature that has addressed this topic in the period 1996-2006, with a particular focus on empirical analyses. On the basis of this survey we present a new classification framework that represents an abstracted and synthesized view of the types of factors that have been asserted as influencing project outcomes.

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arXiv2021

What are Hybrid Development Methods Made Of? An Evidence-based Characterization

Among the multitude of software development processes available, hardly any is used by the book. Regardless of company size or industry sector, a majority of project teams and companies use customized processes that combine different development methods -- so-called hybrid development methods. Even though such hybrid development methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. In this paper, we make a first step towards devising such guidelines. Grounded in 1,467 data points from a large-scale online survey among practitioners, we study the current state of practice in process use to answer the question: What are hybrid development methods made of? Our findings reveal that only eight methods and few practices build the core of modern software development. This small set allows for statistically constructing hybrid development methods. Using an 85% agreement level in the participants' selections, we provide two examples illustrating how hybrid development methods are characterized by the practices they are made of. Our evidence-based analysis approach lays the foundation for devising hybrid development methods.

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arXiv2021

Finding faults: A scoping study of fault diagnostics for Industrial Cyber-Physical Systems

Context: As Industrial Cyber-Physical Systems (ICPS) become more connected and widely-distributed, often operating in safety-critical environments, we require innovative approaches to detect and diagnose the faults that occur in them. Objective: We profile fault identification and diagnosis techniques employed in the aerospace, automotive, and industrial control domains. By examining both theoretical presentations as well as case studies from production environments, we present a profile of the current approaches being employed and identify gaps. Methodology: A scoping study was used to identify and compare fault detection and diagnosis methodologies that are presented in the current literature. Results: Fault identification and analysis studies from 127 papers published from 2004 to 2019 reveal a wide diversity of promising techniques, both emerging and in-use. These range from traditional Physics-based Models to Data-Driven Artificial Intelligence (AI) and Knowledge-Based approaches. Predictive diagnostics or prognostics featured prominently across all sectors, along with discussions of techniques including Fault trees, Petri nets and Markov approaches. We also profile some of the techniques that have reached the highest Technology Readiness Levels, showing how those methods are being applied in real-world environments beyond the laboratory. Conclusions: Our results suggest that the continuing wide use of both Model-Based and Data-Driven AI techniques across all domains, especially when they are used together in hybrid configuration, reflects the complexity of the current ICPS application space. While creating sufficiently-complete models is labor intensive, Model-free AI techniques were evidenced as a viable way of addressing aspects of this challenge, demonstrating the increasing sophistication of current machine learning systems.(Abridged)

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arXiv2021

A Perspective-Based Understanding of Project Success

Answering the call for alternative approaches to researching project management, we explore the evaluation of project success from a subjectivist perspective. An in-depth, longitudinal case study of information systems development in a large manufacturing company was used to investigate how various project stakeholders subjectively perceived the project outcome and what evaluation criteria they drew on in doing so. A conceptual framework is developed for understanding and analyzing evaluations of project success, both formal and informal. The framework highlights how different stakeholder perspectives influence the perceived outcome(s) of a project, and how project evaluations may differ between stakeholders and across time.

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arXiv2021

Evaluating prediction systems in software project estimation

Context: Software engineering has a problem in that when we empirically evaluate competing prediction systems we obtain conflicting results. Objective: To reduce the inconsistency amongst validation study results and provide a more formal foundation to interpret results with a particular focus on continuous prediction systems. Method: A new framework is proposed for evaluating competing prediction systems based upon (1) an unbiased statistic, Standardised Accuracy, (2) testing the result likelihood relative to the baseline technique of random 'predictions', that is guessing, and (3) calculation of effect sizes. Results: Previously published empirical evaluations of prediction systems are re-examined and the original conclusions shown to be unsafe. Additionally, even the strongest results are shown to have no more than a medium effect size relative to random guessing. Conclusions: Biased accuracy statistics such as MMRE are deprecated. By contrast this new empirical validation framework leads to meaningful results. Such steps will assist in performing future meta-analyses and in providing more robust and usable recommendations to practitioners.

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arXiv2021

What Affects Team Behavior? Preliminary Linguistic Analysis of Communications in the Jazz Repository

There is a growing belief that understanding and addressing the human processes employed during software development is likely to provide substantially more value to industry than yet more recommendations for the implementation of various methods and tools. To this end, considerable research effort has been dedicated to studying human issues as represented in software artifacts, due to its relatively unobtrusive nature. We have followed this line of research and have conducted a preliminary study of team behaviors using data mining techniques and linguistic analysis. Our data source, the IBM Rational Jazz repository, was mined and data from three different project areas were extracted. Communications in these projects were then analyzed using the LIWC linguistic analysis tool. We found that although there are some variations in language use among teams working on project areas dedicated to different software outcomes, project type and the mix of (and number of) individuals involved did not affect team behaviors as evident in their communications. These assessments are initial conjectures, however; we plan further exploratory analysis to validate these results. We explain these findings and discuss their implications for software engineering practice.

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arXiv2021

The Many Facets of Distance and Space: the Mobility of Actors in Globally Distributed Project Teams

Global software development practices are shaped by the challenges of time and 'distance', notions perceived to separate sites in a multi-site collaboration. Yet while sites may be fixed, the actors in global projects are mobile, so distance becomes a dynamic spatial dimension rather than a static concept. This empirical study applies grounded theory to unpack the nature of mobility within a three site globally distributed team setting. We develop a model for mapping the movements of team members in local and global spaces, and demonstrate its operation through static snapshots and dynamic patterns evolving over time. Through this study we highlight the complexity of 'mobility' as one facet of 'space' in globally distributed teams and illuminate its tight coupling with the accompanying dimensions of accessibility and context awareness.

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arXiv2021

A Systematic Mapping Study on Dynamic Metrics and Software Quality

Several important aspects of software product quality can be evaluated using dynamic metrics that effectively capture and reflect the software's true runtime behavior. While the extent of research in this field is still relatively limited, particularly when compared to research on static metrics, the field is growing, given the inherent advantages of dynamic metrics. The aim of this work is to systematically investigate the body of research on dynamic software metrics to identify issues associated with their selection, design and implementation. Mapping studies are being increasingly used in software engineering to characterize an emerging body of research and to identify gaps in the field under investigation. In this study we identified and evaluated 60 works based on a set of defined selection criteria. These studies were further classified and analyzed to identify their relativity to future dynamic metrics research. The classification was based on three different facets: research focus, research type and contribution type. We found a strong body of research related to dynamic coupling and cohesion metrics, with most works also addressing the abstract notion of software complexity. Specific opportunities for future work relate to a much broader range of quality dimensions.

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arXiv2021

Valuing Evaluation: Methodologies to Bridge Research and Practice

The potential disconnect between research and practice in software engineering (SE) means that the uptake of research outcomes has at times been limited. In this paper we seek to identify research approaches that are rigorous in terms of method but that are also relevant to software engineering practitioners. After considering the correspondence of several approaches to software systems research and practice we recommend a framework for applying grounded theory in SE research, as a means of delivering both robust and useful outcomes.

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arXiv2021

Designing Actively Secure, Highly Available Industrial Automation Applications

Programmable Logic Controllers (PLCs) execute critical control software that drives Industrial Automation and Control Systems (IACS). PLCs can become easy targets for cyber-adversaries as they are resource-constrained and are usually built using legacy, less-capable security measures. Security attacks can significantly affect system availability, which is an essential requirement for IACS. We propose a method to make PLC applications more security-aware. Based on the well-known IEC 61499 function blocks standard for developing IACS software, our method allows designers to annotate critical parts of an application during design time. On deployment, these parts of the application are automatically secured using appropriate security mechanisms to detect and prevent attacks. We present a summary of availability attacks on distributed IACS applications that can be mitigated by our proposed method. Security mechanisms are achieved using IEC 61499 Service-Interface Function Blocks (SIFBs) embedding Intrusion Detection and Prevention System (IDPS), added to the application at compile time. This method is more amenable to providing active security protection from attacks on previously unknown (zero-day) vulnerabilities. We test our solution on an IEC 61499 application executing on Wago PFC200 PLCs. Experiments show that we can successfully log and prevent attacks at the application level as well as help the application to gracefully degrade into safe mode, subsequently improving availability.

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arXiv2020

Consolidating a Model for Describing Situated Software Practices

Many prescriptive approaches to developing software intensive systems have been advocated but each is based on assumptions about context. It has been found that practitioners do not follow prescribed methodologies, but rather select and adapt specific practices according to local needs. As researchers, we would like to be in a position to support such tailoring. However, at the present time we simply do not have sufficient evidence relating practice and context for this to be possible. We have long understood that a deeper understanding of situated software practices is crucial for progress in this area, and have been exploring this problem from a number of perspectives. In this position paper, we draw together the various aspects of our work into a holistic model and discuss the ways in which the model might be applied to support the long term goal of evidence-based decision support for practitioners. The contribution specific to this paper is a discussion on model evaluation, including a proof-of-concept demonstration of model utility. We map Kernel elements from the Essence system to our model and discuss gaps and limitations exposed in the Kernel. Finally, we overview our plans for further refining and evaluating the model.

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