Stephen G. MacDonell

Mujtaba Alshakhouri, Jim Buchan, Stephen G. MacDonell

Context: Most prior software visualisation (SV) research has focused primarily on making aspects of intangible software product artefacts more evident. While undoubtedly useful, this focus has meant that software process visualisation has received far less attention. Objective: This paper presents Conceptual Visualisation, a novel SV approach that builds on the well-known CodeCity metaphor by situating software code artefacts alongside their software development processes, in order to link and synchronise these typically separate components. Method: While the majority of prior SV research has focused on representing what is already available in the code (i.e., the implementation) or information derived from it (i.e., various metrics), the presented approach instead makes the design concepts and original developers' intentions -- both significant sources of information in terms of software development and maintenance -- readily and contextually available in a visualisation environment that tightly integrates the code artefacts with their original functional requirements and development activity. Results: Our approach has been implemented in a prototype tool called ScrumCity with the proof of concept being demonstrated using six real-world open source systems. A preliminary case study has further been carried out with real world data. Conclusion: Conceptual Visualisation, as implemented in ScrumCity, shows early promise in enabling developers and managers (and potentially other stakeholders) to traverse and explore multiple aspects of software product and process artefacts in a synchronised manner, achieving traceability between the two.

Amjed Tahir, Sherlock A. Licorish, Stephen G. MacDonell

One of the purported ways to increase productivity and reduce development time is to reuse existing features and modules. If reuse is adopted, logically then, it will have a direct impact on a system's evolution. However, the evidence in the literature is not clear on the extent to which reuse is practiced in real-world projects, nor how it is practiced. In this paper we report the results of an investigation of reuse and evolution of software features in one of the largest open-source ecosystems - Eclipse. Eclipse provides a leading example of how a system can grow dramatically in size and number of features while maintaining its quality. Our results demonstrate the extent of feature reuse and evolution and also patterns of reuse across ten different Eclipse releases (from Europa to Neon).

Amjed Tahir, Steve Counsell, Stephen G. MacDonell

While a substantial body of prior research has investigated the form and nature of production code, comparatively little attention has examined characteristics of test code, and, in particular, test smells in that code. In this paper, we explore the relationship between production code properties (at the class level) and a set of test smells, in five open source systems. Specifically, we examine whether complexity properties of a production class can be used as predictors of the presence of test smells in the associated unit test. Our results, derived from the analysis of 975 production class-unit test pairs, show that the Cyclomatic Complexity (CC) and Weighted Methods per Class (WMC) of production classes are strong indicators of the presence of smells in their associated unit tests. The Lack of Cohesion of Methods in a production class (LCOM) also appears to be a good indicator of the presence of test smells. Perhaps more importantly, all three metrics appear to be good indicators of particular test smells, especially Eager Test and Duplicated Code. The Depth of the Inheritance Tree (DIT), on the other hand, was not found to be significantly related to the incidence of test smells. The results have important implications for large-scale software development, particularly in a context where organizations are increasingly using, adopting or adapting open source code as part of their development strategy and need to ensure that classes and methods are kept as simple as possible.

Amjed Tahir, Stephen G. MacDonell

As software systems have grown in scale and complexity the test suites built alongside those systems have also become increasingly complex. Understanding key aspects of test suites, such as their coverage of production code, is important when maintaining or reengineering systems. This work investigates the distribution of unit tests in Open Source Software (OSS) systems through the visualization of data obtained from both dynamic and static analysis. Our long-term aim is to support developers in their understanding of test distribution and the relationship of tests to production code. We first obtain dynamic coupling information from five selected OSS systems and we then map the test and production code results. The mapping is shown in graphs that depict both the dependencies between classes and static test information. We analyze these graphs using Centrality metrics derived from graph theory and SNA. Our findings suggest that, for these five systems at least, unit test and dynamic coupling information 'do not match', in that unit tests do not appear to be distributed in line with the systems' dynamic coupling. We contend that, by mapping dynamic coupling data onto unit test information, and through the use of software metrics and visualization, we can locate central system classes and identify to which classes unit testing effort has (or has not) been dedicated.

Marco Kuhrmann, Paolo Tell, Regina Hebig et al.

Together with many success stories, promises such as the increase in production speed and the improvement in stakeholders' collaboration have contributed to making agile a transformation in the software industry in which many companies want to take part. However, driven either by a natural and expected evolution or by contextual factors that challenge the adoption of agile methods as prescribed by their creator(s), software processes in practice mutate into hybrids over time. Are these still agile? In this article, we investigate the question: what makes a software development method agile? We present an empirical study grounded in a large-scale international survey that aims to identify software development methods and practices that improve or tame agility. Based on 556 data points, we analyze the perceived degree of agility in the implementation of standard project disciplines and its relation to used development methods and practices. Our findings suggest that only a small number of participants operate their projects in a purely traditional or agile manner (under 15%). That said, most project disciplines and most practices show a clear trend towards increasing degrees of agility. Compared to the methods used to develop software, the selection of practices has a stronger effect on the degree of agility of a given discipline. Finally, there are no methods or practices that explicitly guarantee or prevent agility. We conclude that agility cannot be defined solely at the process level. Additional factors need to be taken into account when trying to implement or improve agility in a software company. Finally, we discuss the field of software process-related research in the light of our findings and present a roadmap for future research.

Michael Franklin Bosu, Stephen G. MacDonell, Peter A. Whigham

Software effort estimation models are typically developed based on an underlying assumption that all data points are equally relevant to the prediction of effort for future projects. The dynamic nature of several aspects of the software engineering process could mean that this assumption does not hold in at least some cases. This study employs three kernel estimator functions to test the stationarity assumption in five software engineering datasets that have been used in the construction of software effort estimation models. The kernel estimators are used in the generation of nonuniform weights which are subsequently employed in weighted linear regression modeling. In each model, older projects are assigned smaller weights while the more recently completed projects are assigned larger weights, to reflect their potentially greater relevance to present or future projects that need to be estimated. Prediction errors are compared to those obtained from uniform models. Our results indicate that, for the datasets that exhibit underlying nonstationary processes, uniform models are more accurate than the nonuniform models; that is, models based on kernel estimator functions are worse than the models where no weighting was applied. In contrast, the accuracies of uniform and nonuniform models for datasets that exhibited stationary processes were essentially equivalent. Our analysis indicates that as the heterogeneity of a dataset increases, the effect of stationarity is overridden. The results of our study also confirm prior findings that the accuracy of effort estimation models is independent of the type of kernel estimator function used in model development.

Sherlock A. Licorish, Stephen G. MacDonell

Context: Interest in software engineering (SE) methodologies and tools has been complemented in recent years by research efforts oriented towards understanding the human processes involved in software development. This shift has been imperative given reports of inadequately performing teams and the consequent growing emphasis on individuals and team relations in contemporary SE methods. Objective: While software repositories have frequently been studied with a view to explaining such human processes, research has tended to use primarily quantitative analysis approaches. There is concern, however, that such approaches can provide only a partial picture of the software process. Given the way human behavior is nuanced within psychological and social contexts, it has been asserted that a full understanding may only be achieved through deeper contextual enquiries. Method: We have followed such an approach and have applied data mining, SNA, psycholinguistic analysis and directed content analysis (CA) to study the way core developers at IBM Rational Jazz contribute their social and intellectual capital, and have compared the attitudes, interactions and activities of these members to those of their less active counterparts. Results: Among our results, we uncovered that Jazz's core developers worked across multiple roles, and were crucial to their teams' organizational, intra-personal and inter-personal processes. Additionally, although these individuals were highly task- and achievement-focused, they were also largely responsible for maintaining positive team atmosphere, and for providing context awareness in support of their colleagues. Conclusion: Our results suggest that high-performing distributed agile teams rely on both individual and collective efforts, as well as organizational environments that promote informal and organic work structures.(Abridged)

Sherlock A. Licorish, Stephen G. MacDonell

Agile software developers are required to self-organize, occupying various informal roles as needed in order to successfully deliver software features. However, previous research has reported conflicting evidence about the way teams actually undertake this activity. The ability to self-organize is particularly necessary for software development in globally distributed environments, where distance has been shown to exacerbate human-centric issues. Understanding the way successful teams self-organise should inform distributed team composition strategies and software project governance. We have used psycholinguistics to study the way IBM Rational Jazz practitioners enacted various roles, expressed attitudes and shared competencies to successfully self-organize in their global projects. Among our findings, we uncovered that practitioners enacted various roles depending on their teams' cohort of features; and that team leaders were most critical to IBM Jazz teams' self-organisation. We discuss these findings and highlight their implications for software project governance.

Sherlock A. Licorish, Stephen G. MacDonell

Studying the human factors that impact on software development, and assigning individuals with specific competencies and qualities to particular software roles, have been shown to aid software project performance. For instance, prior evidence suggests that extroverted software project leaders are most successful. Role assignment based on individuals' competencies and behaviors may be especially relevant in distributed software development contexts where teams are often affected by distance, cultural, and personality issues. Project leaders in these environments need to possess high levels of inter-personal, intra-personal and organizational competencies if they are to appropriately manage such issues and maintain positive project performance. With a view to understanding and explaining the specific competencies and behaviors that are required of project leaders in these settings, we used psycholinguistic and directed content analysis to study the way six successful IBM Rational Jazz leaders operated while coordinating their three distributed projects. Contrary to previous evidence reported in personality studies, our results did not reveal universal competencies and behaviors among these Jazz leaders. Instead, Jazz project leaders' competencies and behaviors varied with their project portfolio of tasks. Our findings suggest that a pragmatic approach that considers the nature of the software tasks being developed is likely to be a more effective strategy for assigning leaders to distributed software teams, as against a strategy that promotes a specific personality type. We discuss these findings and outline implications for distributed software project governance.

Sherlock A. Licorish, Stephen G. MacDonell

The ability to self-organise is posited to be a fundamental requirement for successful agile teams. In particular, self-organising teams are said to be crucial in agile globally distributed software development (AGSD) settings, where distance exacerbates team issues. We used contextual analysis to study the specific interaction behaviours and enacted roles of practitioners working in multiple AGSD teams. Our results show that the teams studied were extremely task focussed, and those who occupied team lead or programmer roles were central to their teams' self-organisation. These findings have implications for AGSD teams, and particularly for instances when programmers - or those occupying similar non-leadership positions - may not be willing to accept such responsibilities. We discuss the implications of our findings for information system development (ISD) practice.

Michael Franklin Bosu, Stephen G. MacDonell

Reliable empirical models such as those used in software effort estimation or defect prediction are inherently dependent on the data from which they are built. As demands for process and product improvement continue to grow, the quality of the data used in measurement and prediction systems warrants increasingly close scrutiny. In this paper we propose a taxonomy of data quality challenges in empirical software engineering, based on an extensive review of prior research. We consider current assessment techniques for each quality issue and proposed mechanisms to address these issues, where available. Our taxonomy classifies data quality issues into three broad areas: first, characteristics of data that mean they are not fit for modeling; second, data set characteristics that lead to concerns about the suitability of applying a given model to another data set; and third, factors that prevent or limit data accessibility and trust. We identify this latter area as of particular need in terms of further research.

Amjed Tahir, Kwabena E. Bennin, Xun Xiao et al.

In the past 20 years, defect prediction studies have generally acknowledged the effect of class size on software prediction performance. To quantify the relationship between object-oriented (OO) metrics and defects, modelling has to take into account the direct, and potentially indirect, effects of class size on defects. However, some studies have shown that size cannot be simply controlled or ignored, when building prediction models. As such, there remains a question whether, and when, to control for class size. This study provides a new in-depth examination of the impact of class size on the relationship between OO metrics and software defects or defect-proneness. We assess the impact of class size on the number of defects and defect-proneness in software systems by employing a regression-based mediation (with bootstrapping) and moderation analysis to investigate the direct and indirect effect of class size in count and binary defect prediction. Our results show that the size effect is not always significant for all metrics. Of the seven OO metrics we investigated, size consistently has significant mediation impact only on the relationship between Coupling Between Objects (CBO) and defects/defect-proneness, and a potential moderation impact on the relationship between Fan-out and defects/defect-proneness. Based on our results we make three recommendations. One, we encourage researchers and practitioners to examine the impact of class size for the specific data they have in hand and through the use of the proposed statistical mediation/moderation procedures. Two, we encourage empirical studies to investigate the indirect effect of possible additional variables in their models when relevant. Three, the statistical procedures adopted in this study could be used in other empirical software engineering research to investigate the influence of potential mediators/moderators.

Sherlock A. Licorish, Stephen G. MacDonell

Context: Given the acknowledged need to understand the people processes enacted during software development, software repositories and mailing lists have become a focus for many studies. However, researchers have tended to use mostly mathematical and frequency-based techniques to examine the software artifacts contained within them. Objective: There is growing recognition that these approaches uncover only a partial picture of what happens during software projects, and deeper contextual approaches may provide further understanding of the intricate nature of software teams' dynamics. We demonstrate the relevance and utility of such approaches in this study. Method: We use psycholinguistics and directed content analysis (CA) to study the way project tasks drive teams' attitudes and knowledge sharing. We compare the outcomes of these two approaches and offer methodological advice for researchers using similar forms of repository data. Results: Our analysis reveals significant differences in the way teams work given their portfolio of tasks and the distribution of roles. Conclusion: We overcome the limitations associated with employing purely quantitative approaches, while avoiding the time-intensive and potentially invasive nature of field work required in full case studies.

Issam Jebreen, Robert Wellington, Stephen G. MacDonell

Small to medium sized business enterprises (SMEs) generally thrive because they have successfully done something unique within a niche market. For this reason, SMEs may seek to protect their competitive advantage by avoiding any standardization encouraged by the use of packaged software (PS). Packaged software implementation at SMEs therefore presents challenges relating to how best to respond to misfits between the functionality offered by the packaged software and each SME's business needs. An important question relates to which processes small software enterprises - or Small to Medium-Sized Software Development Companies (SMSSDCs) - apply in order to identify and then deal with these misfits. To explore the processes of packaged software (PS) implementation, an ethnographic study was conducted to gain in-depth insights into the roles played by analysts in two SMSSDCs. The purpose of the study was to understand PS implementation in terms of requirements engineering (or 'PSIRE'). Data collected during the ethnographic study were analyzed using an inductive approach. Based on our analysis of the cases we constructed a theoretical model explaining the requirements engineering process for PS implementation, and named it the PSIRE Parallel Star Model. The Parallel Star Model shows that during PSIRE, more than one RE process can be carried out at the same time. The Parallel Star Model has few constraints, because not only can processes be carried out in parallel, but they do not always have to be followed in a particular order. This paper therefore offers a novel investigation and explanation of RE practices for packaged software implementation, approaching the phenomenon from the viewpoint of the analysts, and offers the first extensive study of packaged software implementation RE (PSIRE) in SMSSDCs.

Solomon Mensah, Jacky Keung, Stephen G. MacDonell et al.

Bellwether effect refers to the existence of exemplary projects (called the Bellwether) within a historical dataset to be used for improved prediction performance. Recent studies have shown an implicit assumption of using recently completed projects (referred to as moving window) for improved prediction accuracy. In this paper, we investigate the Bellwether effect on software effort estimation accuracy using moving windows. The existence of the Bellwether was empirically proven based on six postulations. We apply statistical stratification and Markov chain methodology to select the Bellwether moving window. The resulting Bellwether moving window is used to predict the software effort of a new project. Empirical results show that Bellwether effect exist in chronological datasets with a set of exemplary and recently completed projects representing the Bellwether moving window. Result from this study has shown that the use of Bellwether moving window with the Gaussian weighting function significantly improve the prediction accuracy.

Tony Clear, Bilal Raza, Stephen G. MacDonell

Global Software Engineering (GSE) research contains few examples consciously applying what Glass and colleagues have termed an 'evaluative-critical' approach. In this study we apply dilemma analysis to conduct a critical review of a major (and ongoing) nearshore Business Process Outsourcing project in New Zealand. The project has become so troubled that a Government Minister has recently been assigned responsibility for troubleshooting it. The 'Novopay' project concerns the implementation of a nationwide payroll system responsible for the payment of some 110,000 teachers and education sector staff. An Australian company won the contract for customizing and implementing the Novopay system, taking over from an existing New Zealand service provider. We demonstrate how a modified form of dilemma analysis can be a powerful technique for highlighting risks and stakeholder impacts from empirical data, and that adopting an evaluative-critical approach to such projects can usefully highlight tensions and barriers to satisfactory project outcomes.

Michael Franklin Bosu, Stephen G. MacDonell

Context: The utility of prediction models in empirical software engineering (ESE) is heavily reliant on the quality of the data used in building those models. Several data quality challenges such as noise, incompleteness, outliers and duplicate data points may be relevant in this regard. Objective: We investigate the reporting of three potentially influential elements of data quality in ESE studies: data collection, data pre-processing, and the identification of data quality issues. This enables us to establish how researchers view the topic of data quality and the mechanisms that are being used to address it. Greater awareness of data quality should inform both the sound conduct of ESE research and the robust practice of ESE data collection and processing. Method: We performed a targeted literature review of empirical software engineering studies covering the period January 2007 to September 2012. A total of 221 relevant studies met our inclusion criteria and were characterized in terms of their consideration and treatment of data quality. Results: We obtained useful insights as to how the ESE community considers these three elements of data quality. Only 23 of these 221 studies reported on all three elements of data quality considered in this paper. Conclusion: The reporting of data collection procedures is not documented consistently in ESE studies. It will be useful if data collection challenges are reported in order to improve our understanding of why there are problems with software engineering data sets and the models developed from them. More generally, data quality should be given far greater attention by the community. The improvement of data sets through enhanced data collection, pre-processing and quality assessment should lead to more reliable prediction models, thus improving the practice of software engineering.

Sherlock A. Licorish, Stephen G. MacDonell

Reports that communication and behavioral issues contribute to inadequately performing software teams have fuelled a wealth of research aimed at understanding the human processes employed during software development. The increasing level of interest in human issues is particularly relevant for agile and global software development approaches that emphasize the importance of people and their interactions during projects. While mature analysis techniques in behavioral psychology have been recommended for studying such issues, particularly when using archives and artifacts, these techniques have rarely been used in software engineering research. We utilize these techniques under an embedded case study approach to examine whether IBM Rational Jazz practitioners' behaviors change over project duration and whether certain tasks affect teams' attitudes and behaviors. We found highest levels of project engagement at project start and completion, as well as increasing levels of team collectiveness as projects progressed. Additionally, Jazz practitioners were most insightful and perceptive at the time of project scoping. Further, Jazz teams' attitudes and behaviors varied in line with the nature of the tasks they were performing. We explain these findings and discuss their implications for software project governance and tool design.

Solomon Mensah, Jacky Keung, Stephen G. MacDonell et al.

Context: In addressing how best to estimate how much effort is required to develop software, a recent study found that using exemplary and recently completed projects [forming Bellwether moving windows (BMW)] in software effort prediction (SEP) models leads to relatively improved accuracy. More studies need to be conducted to determine whether the BMW yields improved accuracy in general, since different sizing and aging parameters of the BMW are known to affect accuracy. Objective: To investigate the existence of exemplary projects (Bellwethers) with defined window size and age parameters, and whether their use in SEP improves prediction accuracy. Method: We empirically investigate the moving window assumption based on the theory that the prediction outcome of a future event depends on the outcomes of prior events. Sampling of Bellwethers was undertaken using three introduced Bellwether methods (SSPM, SysSam, and RandSam). The ergodic Markov chain was used to determine the stationarity of the Bell-wethers. Results: Empirical results show that 1) Bellwethers exist in SEP and 2) the BMW has an approximate size of 50 to 80 exemplary projects that should not be more than 2 years old relative to the new projects to be estimated. Conclusion: The study's results add further weight to the recommended use of Bellwethers for improved prediction accuracy in SEP.

Barry Dowdeswell, Roopak Sinha, Stephen G. MacDonell

Integrating the design and creation of fault identification and diagnostic capabilities into Model-Driven Development methodologies is one approach to enhancing the resilience of Industrial Cyber-Physical Systems. We present a Fault Diagnostic Engine designed to recognise and diagnose faults in IEC 61499 Function Block Applications. Using diagnostic agents that interact directly with the target application, we demonstrate fault monitoring and analysis techniques and as well as failure scenario intervention. By designing and building fault diagnostic resources during early phases of Model-Driven Development, both iterative testing and long-term fault management capabilities can be created. While applying and refining appropriate model artifacts, we demonstrate that the concurrent development of function blocks alongside fault management capabilities is both feasible and worthwhile.

Barry Dowdeswell, Roopak Sinha, Dennis Jarvis et al.

We have come to rely on industrial-scale cyber-physical systems more and more to manage tasks and machinery in safety-critical situations. Efficient, reliable fault identification and management has become a critical factor in the design of these increasingly sophisticated and complex devices. Teams of co-operating software agents are one way to coordinate the flow of diagnostic information gathered during fault-finding. By wielding domain knowledge of the software architecture used to construct the system, agents build and refine their beliefs about the location and root cause of faults. This paper examines how agents constructed within the GORITE Multi-Agent Framework create and refine their beliefs. We demonstrate three different belief structures implemented within our Fault Diagnostic Engine, showing how each supports a distinct aspect of the agent's reasoning. Using domain knowledge of the IEC 61499 Function Block architecture, agents are able to examine and rigorously evaluate both individual components and entire subsystems.

Johannes Holvitie, Sherlock A. Licorish, Rodrigo O. Spínola et al.

Context: Contemporary software development is typically conducted in dynamic, resource-scarce environments that are prone to the accumulation of technical debt. While this general phenomenon is acknowledged, what remains unknown is how technical debt specifically manifests in and affects software processes, and how the software development techniques employed accommodate or mitigate the presence of this debt. Objectives: We sought to draw on practitioner insights and experiences in order to classify the effects of agile method use on technical debt management. We explore the breadth of practitioners' knowledge about technical debt; how technical debt is manifested across the software process; and the perceived effects of common agile software development practices and processes on technical debt. In doing so, we address a research gap in technical debt knowledge and provide novel and actionable managerial recommendations. Method: We designed, tested and executed a multi-national survey questionnaire to address our objectives, receiving 184 responses from practitioners in Brazil, Finland, and New Zealand. Results: Our findings indicate that: 1) Practitioners are aware of technical debt, although, there was under utilization of the concept, 2) Technical debt commonly resides in legacy systems, however, concrete instances of technical debt are hard to conceptualize which makes it problematic to manage, 3) Queried agile practices and processes help to reduce technical debt; particularly, techniques that verify and maintain the structure and clarity of implemented artifacts. Conclusions: The fact that technical debt instances tend to have characteristics in common means that a systematic approach to its management is feasible. However, notwithstanding the positive effects of some agile practices on technical debt management, competing stakeholders' interests remain a concern.(Abridged)

Amjed Tahir, Kwabena E. Bennin, Stephen G. MacDonell et al.

BACKGROUND: In object oriented (OO) software systems, class size has been acknowledged as having an indirect effect on the relationship between certain artifact characteristics, captured via metrics, and faultproneness, and therefore it is recommended to control for size when designing fault prediction models. AIM: To use robust statistical methods to assess whether there is evidence of any true effect of class size on fault prediction models. METHOD: We examine the potential mediation and moderation effects of class size on the relationships between OO metrics and number of faults. We employ regression analysis and bootstrapping-based methods to investigate the mediation and moderation effects in two widely-used datasets comprising seventeen systems. RESULTS: We find no strong evidence of a significant mediation or moderation effect of class size on the relationships between OO metrics and faults. In particular, size appears to have a more significant mediation effect on CBO and Fan-out than other metrics, although the evidence is not consistent in all examined systems. On the other hand, size does appear to have a significant moderation effect on WMC and CBO in most of the systems examined. Again, the evidence provided is not consistent across all examined systems CONCLUSION: We are unable to confirm if class size has a significant mediation or moderation effect on the relationships between OO metrics and the number of faults. We contend that class size does not fully explain the relationships between OO metrics and the number of faults, and it does not always affect the strength/magnitude of these relationships. We recommend that researchers consider the potential mediation and moderation effect of class size when building their prediction models, but this should be examined independently for each system.

Sherlock A. Licorish, Stephen G. MacDonell

Context: In seeking to better understand the impact of various human factors in software development, and how teams' attitudes relate to their performance, increasing attention is being given to the study of team-related artefacts. In particular, researchers have conducted numerous studies on a range of team communication channels to explore links between developers' language use and the incidence of software bugs in the products they delivered. Comparatively limited attention has been paid, however, to the full range of software tasks that are commonly performed during the development and delivery of software systems, in spite of compelling evidence pointing to the need to understand teams' attitudes more widely. Objective: We were therefore motivated to study the relationships between task type and team attitudes, and how attitudes expressed in teams' communications might be related to their task completion performance when undertaking a range of activities. Method: Our investigation involved artefacts from 474 IBM Jazz practitioners assembled in 149 teams working on around 30,000 software development tasks over a three-year period. We applied linguistic analysis, standard statistical techniques and directed content analysis to address our research objective. Results: Our evidence revealed that teams expressed different attitudes when working on various forms of software tasks, and they were particularly emotional when working to remedy defects. That said, teams' expression of attitudes was not found to be a strong predictor of their task completion performance. Conclusion: Efforts aimed at reducing bug incidence may positively limit teams' emotional disposition when resolving bugs, thereby reducing the otherwise high demand for emotionally stable members. (Abridged)

Awais Tanveer, Roopak Sinha, Stephen G. MacDonell

Cyber-attacks on Industrial Automation and Control Systems (IACS) are rising in numbers and sophistication. Embedded controller devices such as Programmable Logic Controllers (PLCs), which are central to controlling physical processes, must be secured against attacks on confidentiality, integrity and availability. The focus of this paper is to add design-level support for security in IACS applications, especially around inter-PLC communications. We propose an end-to-end solution to develop IACS applications with inherent, and parametric support for security. Built using the IEC 61499 Function Blocks standard, this solution allows us to annotate certain communications as 'secure' during design time. When the application is compiled, these annotations are transformed into a security layer that implements encrypted communication between PLCs. In this paper, we implement a part of this security layer focussed on confidentiality, called Confidentiality Layer for Function Blocks (CL4FB), which provides a range of encryption/decryption and secure key exchange functionalities. We study the impact of using CL4FB in IACS applications with real-time constraints. Through a case study focussing on protection functions in smart-grids, we show that varying levels of confidentiality can be achieved while also meeting hard real-time deadlines.

Diana Kirk, Stephen G. MacDonell

In the domain of software engineering, our efforts as researchers to advise industry on which software practices might be applied most effectively are limited by our lack of evidence based information about the relationships between context and practice efficacy. In order to accumulate such evidence, a model for context is required. We are in the exploratory stage of evolving a model for context for situated software practices. In this paper, we overview the evolution of our proposed model. Our analysis has exposed a lack of clarity in the meanings of terms reported in the literature. Our base model dimensions are People, Place, Product and Process. Our contributions are a deepening of our understanding of how to scope contextual factors when considering software initiatives and the proposal of an initial theoretical construct for context. Study limitations relate to a possible subjectivity in the analysis and a restricted evaluation base. In the next stage in the research, we will collaborate with academics and practitioners to formally refine the model.

Sherlock A. Licorish, Stephen G. MacDonell

In seeking to understand the processes enacted during software development, an increasing number of studies have mined software repositories. In particular, studies have endeavored to show how teams resolve software defects. Although much of this work has been useful, we contend that large-scale examinations across the range of activities that are commonly performed, beyond defect-related issues alone, would help us to more fully understand the reasons why defects occur as well as their consequences. More generally, these explorations would reveal how team processes occur during all software development efforts. We thus extend such studies by investigating how software practitioners work while undertaking the range of software tasks that are typically performed. Multiple forms of analyses of a longitudinal case study reveal that software practitioners were mostly involved in fixing defects, and that their engagement covaried depending on the nature of the work they were performing. Furthermore, multiple external factors affected speed of task resolution. Our outcomes suggest that behavioral and intrinsic issues may interact with extrinsic factors becoming significant predictors of the speed of software task resolution.

Bilal Raza, Tony Clear, Stephen G. MacDonell

Outsourcing is typically considered to occur in three phases: decision, transition and operation. As outsourcing is now well established the switching of vendors and transitioning from one system to another is common. However, most of the research to date on outsourcing has focused on the decision and operation phases, leaving a gap between theory and practice concerning the transition phase. Transition in outsourcing entails the changing of systems, business processes and/or vendors. If a suitable transition approach is not applied pressures for another transition can immediately build. We present results from a case study carried out on the Novopay Project in which the Ministry of Education in New Zealand changed their vendor from an onshore to a near-shore provider. This project resulted in a sequence of three transitions, with each following a different approach as a direct result of the experiences encountered in the previous transition. In this research we made use of the rich 'data dump' of evidence provided by the Ministry of Education. Our analysis describes how a client organization can become trapped in a continuous transition cycle if a suitable approach is not applied. Transition1 involved the client moving from complete outsourcing to selective insourcing. After realizing that they did not have the capabilities to manage insourcing, Transition2 was initiated. In Transition2 the sourcing approach reverted back to complete outsourcing. When it was realized that the new vendor in Transition2 could not in fact deliver a new service model or support end-users in following new business processes, Transition3 was initiated. In Transition3, the client established an internal company to insource service operations to support end-users. Transition can be a sound business strategy, however, if a flawed sourcing approach is chosen it can result in 'continuous transition'. (Abridged)

Chan Won Lee, Sherlock A. Licorish, Bastin Tony Roy Savarimuthu et al.

Text mining approaches are being used increasingly for business analytics. In particular, such approaches are now central to understanding users' feedback regarding systems delivered via online application distribution platforms such as Google Play. In such settings, large volumes of reviews of potentially numerous apps and systems means that it is infeasible to use manual mechanisms to extract insights and knowledge that could inform product improvement. In this context of identifying software system improvement options, text mining techniques are used to reveal the features that are mentioned most often as being in need of correction (e.g., GPS), and topics that are associated with features perceived as being defective (e.g., inaccuracy of GPS). Other approaches may supplement such techniques to provide further insights for online communities and solution providers. In this work we augment text mining approaches with social network analysis to demonstrate the utility of using multiple techniques. Our outcomes suggest that text mining approaches may indeed be supplemented with other methods to deliver a broader range of insights.

Sherlock A. Licorish, Johannes Holvitie, Sami Hyrynsalmi et al.

In seeking to complement consultants' and tool vendors' reports, there has been an increasing academic focus on understanding the adoption and use of software development methods and practices. We surveyed practitioners working in Brazil, Finland, and New Zealand in a transnational study to contribute to these efforts. Among our findings we observed that most of the 184 practitioners in our sample focused on a small portfolio of projects that were of short duration. In addition, Scrum and Kanban were used most; however, some practitioners also used conventional methods. Coding Standards, Simple Design and Refactoring were used most by practitioners, and these practices were held to be largely suitable for project and process management. Our evidence points to the need to properly understand and support a wide range of software methods.

Diana Kirk, Stephen G. MacDonell

There is growing acknowledgement within the software engineering community that a theory of software development is needed to integrate the myriad methodologies that are currently popular, some of which are based on opposing perspectives. We have been developing such a theory for a number of years. In this paper, we overview our theory and report on a recent ontological analysis of the theory constructs. We suggest that, once fully developed, this theory, or one similar to it, may be applied to support situated software development, by providing an overarching model within which software initiatives might be categorised and understood. Such understanding would inevitably lead to greater predictability with respect to outcomes.

Htike Htike Wut Yi, Stephen G. MacDonell

Contemporary business innovation relies increasingly on information and communications technology (ICT) solutions. As ICT initiatives are generally implemented via projects the management of ICT projects has come under increasing scrutiny. ICT projects continue to fail; as a result, while research in ICT project management has indeed increased, many challenges for research and practice remain. Many studies have addressed the execution and management of ICT projects and the many factors that might relate to project outcomes. Very few, however, have considered ICT project initiation and the crucial decisions made at that very early, pre-life cycle stage. The primary intent of this research is therefore to investigate ICT projects with a particular focus on their initiation. In doing so we wished to understand why ICT projects are started, and how they are moved from idea or proposal to supported reality. A combination of semi-structured interviews and the repertory grid data collection and analysis method was employed to investigate and validate the motivating factors that influence individual IT Managers' project initiation decisions and the methods they use to transition from idea to enacted project. Our results showed that there are indeed multiple underlying reasons for the decisions made at this early stage and that there are some especially common decision drivers. Some were expected, in the sense that they mapped to recommended best practice. For instance, most projects are motivated by a desire to achieve efficiencies or cost savings, and their potential tends to be assessed using cost benefit analysis. Other results were more surprising - competitor pressure was not a common driver for ICT project initiation in our analysis. Unsurprisingly, formal evaluation methods are more frequently used to assess project proposals when those projects are larger and higher profile. (Abridged)

Sherlock A. Licorish, Amjed Tahir, Michael Franklin Bosu et al.

End-users play an integral role in identifying requirements, validating software features' usefulness, locating defects, and in software product evolution in general. Their role in these activities is especially prominent in online application distribution platforms (OADPs), where software is developed for many potential users, and for which the traditional processes of requirements gathering and negotiation with a single group of end-users do not apply. With such vast access to end-users, however, comes the challenge of how to prioritize competing requirements in order to satisfy previously unknown user groups, especially with early releases of a product. One highly successful product that has managed to overcome this challenge is the Android Operating System (OS). While the requirements of early versions of the Android OS likely benefited from market research, new features in subsequent releases appear to have benefitted extensively from user reviews. Thus, lessons learned about how Android developers have managed to satisfy the user community over time could usefully inform other software products. We have used data mining and natural language processing (NLP) techniques to investigate the issues that were logged by the Android community, and how Google's remedial efforts correlated with users' requests. We found very strong alignment between end-users' top feature requests and Android developers' responses, particularly for the more recent Android releases. Our findings suggest that effort spent responding to end-users' loudest calls may be integral to software systems' survival, and a product's overall success.

Diana Kirk, Stephen G. MacDonell

There is growing acknowledgement within the software engineering community that a theory of software development is needed to integrate the myriad methodologies that are currently popular, some of which are based on opposing perspectives. We have been developing such a theory for a number of years. In this position paper, we overview our theory along with progress made thus far. We suggest that, once fully developed, this theory, or one similar to it, may be applied to support situated software development, by providing an overarching model within which software initiatives might be categorised and understood. Such understanding would inevitably lead to greater predictability with respect to outcomes.

Bilal Raza, Tony Clear, Stephen G. MacDonell

This study is directed towards highlighting tensions of incoming and outgoing vendors during outsourcing in a near-shore context. Incoming-and-outgoing of vendors generate a complex form of relationship in which the participating organizations cooperate and compete simultaneously. It is of great importance to develop knowledge about this kind of relationship typically in the current GSE-related multi-sourcing environment. We carried out a longitudinal case study and utilized data from the 'Novopay' project, which is available in the public domain. This project involved an outgoing New Zealand based vendor and incoming Australian based vendor. The results show that the demand for the same human resources, dependency upon cooperation and collaboration between vendors, reliance on each other system's configurations and utilizing similar strategies by the client, which worked for the previous vendor, generated a set of tensions which needed to be continuously managed throughout the project.

Sherlock A. Licorish, Chan Won Lee, Bastin Tony Roy Savarimuthu et al.

It is known that user involvement and user-centered design enhance system acceptance, particularly when end-users' views are considered early in the process. However, the increasingly common method of system deployment, through frequent releases via an online application distribution platform, relies more on post-release feedback from a virtual community. Such feedback may be received from large and diverse communities of users, posing challenges to developers in terms of extracting and identifying the most pressing requests to address. In seeking to tackle these challenges we have used natural language processing techniques to study enhancement requests logged by the Android community. We observe that features associated with a specific subset of topics were most frequently requested for improvement, and that end-users expressed particular discontent with the Jellybean release. End-users also tended to request improvements to specific issues together, potentially posing a prioritization challenge to Google.

Sherlock A. Licorish, Stephen G. MacDonell, Tony Clear

Context: Post-release user feedback plays an integral role in improving software quality and informing new features. Given its growing importance, feedback concerning security enhancements is particularly noteworthy. In considering the rapid uptake of Android we have examined the scale and severity of Android security threats as reported by its stakeholders. Objective: We systematically mine Android issue logs to derive insights into stakeholder perceptions and experiences in relation to certain Android security issues. Method: We employed contextual analysis techniques to study issues raised regarding confidentiality and privacy in the last three major Android releases, considering covariance of stakeholder comments, and the level of consistency in user preferences and priorities. Results: Confidentiality and privacy concerns varied in severity, and were most prevalent over Jelly Bean releases. Issues raised in regard to confidentiality related mostly to access, user credentials and permission management, while privacy concerns were mainly expressed about phone locking. Community users also expressed divergent preferences for new security features, ranging from more relaxed to very strict. Conclusion: Strategies that support continuous corrective measures for both old and new Android releases would likely maintain stakeholder confidence. An approach that provides users with basic default security settings, but with the power to configure additional security features if desired, would provide the best balance for Android's wide cohort of stakeholders.

Sherlock A. Licorish, Stephen G. MacDonell

Context: Prior research has established that a small proportion of individuals dominate team communication during global software development. It is not known, however, how these members' contributions affect their teams' knowledge diffusion process, or whether their personality profiles are responsible for their dominant presence. Objective: We set out to address this gap through the study of repository artifacts. Method: Artifacts from ten teams were mined from the IBM Rational Jazz repository. We employed social network analysis (SNA) to group practitioners into two clusters, Top Members and Others, based on the numbers of messages they communicated and their engagement in task changes. SNA metrics (density, in-degree and closeness) were then used to study practitioners' importance in knowledge diffusion. Thereafter, we performed psycholinguistic analysis on practitioners' messages using linguistic dimensions that had been previously correlated with the Big Five personality profiles. Results: For our sample of 146 practitioners we found that Top Members occupied critical roles in knowledge diffusion, and demonstrated more openness to experience than the Others. Additionally, all personality profiles were represented during teamwork, although openness to experience, agreeableness and extroversion were particularly evident. However, no specific personality predicted members' involvement in knowledge diffusion. Conclusion: Task assignment that promotes highly connected team communication networks may mitigate tacit knowledge loss in global software teams. Additionally, while members expressing openness to experience are likely to be particularly driven to perform, this is not entirely responsible for a global team's success.

Sherlock A. Licorish, Stephen G. MacDonell

Context: Individuals' personality traits have been shown to influence their behavior during team work. In particular, positive group attitudes are said to be essential for distributed and global software development efforts where collaboration is critical to project success. Objective: Given this, we have sought to study the influence of global software practitioners' personality profiles from a psycholinguistic perspective. Method: Artifacts from ten teams were selected from the IBM Rational Jazz repository and mined. We employed social network analysis (SNA) techniques to identify and group practitioners into two clusters based on the numbers of messages they communicated, Top Members and Others, and used standard statistical techniques to assess practitioners' engagement in task changes associated with work items. We then performed psycholinguistic analysis on practitioners' messages using linguistic dimensions of the LIWC tool that had been previously correlated with the Big Five personality profiles. Results: For our sample of 146 practitioners, we found that the Top Members demonstrated more openness to experience than the Other practitioners. Additionally, practitioners involved in usability-related tasks were found to be highly extroverted, and coders were most neurotic and conscientious. Conclusion: High levels of organizational and inter-personal skills may be useful for those operating in distributed settings, and personality diversity is likely to boost team performance.

Sherlock A. Licorish, Stephen G. MacDonell

There is growing interest in mining software repository data to understand, and predict, various aspects of team processes. In particular, text mining and natural-language processing (NLP) techniques have supported such efforts. Visualization may also supplement text mining to reveal unique multi-dimensional insights into software teams' behavioral processes. We demonstrate the utility of combining these approaches in this study. Future application of these methods to the study of teams' behavioral processes offers promise for both research and practice.

Diana Kirk, Stephen G. MacDonell

A growing number of researchers suggest that software process must be tailored to a project's context to achieve maximal performance. Researchers have studied 'context' in an ad-hoc way, with focus on those contextual factors that appear to be of significance. The result is that we have no useful basis upon which to contrast and compare studies. We are currently researching a theoretical basis for software context for the purpose of tailoring and note that a deeper consideration of the meaning of the term 'context' is required before we can proceed. In this paper, we examine the term and present a model based on insights gained from our initial categorisation of contextual factors from the literature. We test our understanding by analysing a further six documents. Our contribution thus far is a model that we believe will support a theoretical operationalisation of software context for the purpose of process tailoring.

Diana Kirk, Stephen G. MacDonell

A growing number of empirical software engineering researchers suggest that a complementary focus on theory is required if the discipline is to mature. A first step in theory-building involves the establishment of suitable theoretical constructs. For researchers studying software projects, the lack of a theoretical construct for context is problematic for both experimentation and effort estimation. For experiments, insufficiently understood contextual factors confound results, and for estimation, unstated contextual factors affect estimation reliability. We have earlier proposed a framework that we suggest may be suitable as a construct for context i.e. represents a minimal, spanning set for the space of software contexts. The framework has six dimensions, described as Who, Where, What, When, How and Why. In this paper, we report the outcomes of a pilot study to test its suitability by categorising contextual factors from the software engineering literature into the framework. We found that one of the dimensions, Why, does not represent context, but rather is associated with objectives. We also identified some factors that do not clearly fit into the framework and require further investigation. Our contributions are the pursuing of a theoretical approach to understanding software context, the initial establishment and evaluation of a construct for context and the exposure of a lack of clarity of meaning in many 'contexts' currently applied as factors for estimating project outcomes.

Katia Romero Felizardo, Elisa Yumi Nakagawa, Stephen G. MacDonell et al.

Context: In order to preserve the value of Systematic Reviews (SRs), they should be frequently updated considering new evidence that has been produced since the completion of the previous version of the reviews. However, the update of an SR is a time consuming, manual task. Thus, many SRs have not been updated as they should be and, therefore, they are currently outdated. Objective: The main contribution of this paper is to support the update of SRs. Method: We propose USR-VTM, an approach based on Visual Text Mining (VTM) techniques, to support selection of new evidence in the form of primary studies. We then present a tool, named Revis, which supports our approach. Finally, we evaluate our approach through a comparison of outcomes achieved using USR-VTM versus the traditional (manual) approach. Results: Our results show that USR-VTM increases the number of studies correctly included compared to the traditional approach. Conclusions: USR-VTM effectively supports the update of SRs.

Sherlock A. Licorish, Stephen G. MacDonell

Increasing effort is being directed to understanding the personality profiles of highly engaged information systems (IS) developers and the impact of such profiles on development outcomes. However, there has been a lesser degree of attention paid to studying attitudes at a fine-grained level, and relating such attitudes to developers' in-process activities, in spite of the fact that social motivation theory notes the importance of such a relationship in general group work. We have therefore applied linguistic analysis, text mining and visualization, and statistical analysis techniques to artefacts developed by 474 developers to study these issues. Our results indicate that our sample of IS developers conveyed a range of attitudes while working to deliver systems features, and those practitioners who communicated the most were also the most engaged. Additionally, of eight linguistic dimensions considered, expressions regarding work and achievement, as well as insightful attitudes, were most closely related to developers' engagement. Accordingly, team diversity and the provision of active support for outcome-driven developers may contribute positively to maintaining team balance and performance.

Sherlock A. Licorish, Stephen G. MacDonell

Context: Prior research has established that a few individuals generally dominate project communication and source code changes during software development, regardless of task assignments at project initiation. Objective: While this phenomenon has been noted, prior research has not sought to understand these dominant individuals. Previous work has found that core communicators are the gatekeepers of their teams' knowledge, and the performance of these members was correlated with their teams' success. Building on this work, we have employed a longitudinal approach to study the way core developers' attitudes, knowledge sharing behaviors and task performance change over the course of their project. Method: We first used Social Network Analysis (SNA) and standard statistical analysis techniques to identify and select artifacts and central practitioners from ten different software development teams. We then applied psycholinguistic analysis and directed content analysis (CA) techniques to interpret the content of these practitioners' messages. Finally, we inspected core developers' activities at various points in time during systems' development. Results: Among our findings, we observe that core developers' attitudes and knowledge sharing behaviors were linked to their involvement in actual software development and the demands of their wider project teams. However, core developers appeared to naturally possess high levels of insightful characteristics. Conclusion: Project performance would likely benefit from strategies aimed at surrounding core developers with other competent communicators. Core developers should also be supported by a wider team who are willing to ask questions and challenge their ideas. Finally, the availability of adequate communication channels would help with maintaining positive team climate especially in distributed developments.(Abridged)

Stephen G. MacDonell

Software project management makes extensive use of predictive modeling to estimate product size, defect proneness and development effort. Although uncertainty is acknowledged in these tasks, fuzzy inference systems, designed to cope well with uncertainty, have received only limited attention in the software engineering domain. In this study we empirically investigate the impact of two choices on the predictive accuracy of generated fuzzy inference systems when applied to a software engineering data set: sampling of observations for training and testing; and the size of the rule set generated using fuzzy c-means clustering. Over ten samples we found no consistent pattern of predictive performance given certain rule set size. We did find, however, that a rule set compiled from multiple samples generally resulted in more accurate predictions than single sample rule sets. More generally, the results provide further evidence of the sensitivity of empirical analysis outcomes to specific model-building decisions.

Katia Romero Felizardo, Norsaremah Salleh, Rafael M. Martins et al.

Background: A systematic literature review (SLR) is a methodology used to aggregate all relevant existing evidence to answer a research question of interest. Although crucial, the process used to select primary studies can be arduous, time consuming, and must often be conducted manually. Objective: We propose a novel approach, known as 'Systematic Literature Review based on Visual Text Mining' or simply SLR-VTM, to support the primary study selection activity using visual text mining (VTM) techniques. Method: We conducted a case study to compare the performance and effectiveness of four doctoral students in selecting primary studies manually and using the SLR-VTM approach. To enable the comparison, we also developed a VTM tool that implemented our approach. We hypothesized that students using SLR-VTM would present improved selection performance and effectiveness. Results: Our results show that incorporating VTM in the SLR study selection activity reduced the time spent in this activity and also increased the number of studies correctly included. Conclusions: Our pilot case study presents promising results suggesting that the use of VTM may indeed be beneficial during the study selection activity when performing an SLR.

Peter A. Whigham, Caitlin A. Owen, Stephen G. MacDonell

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.

Katia Romero Felizardo, Mehwish Riaz, Muhammad Sulayman et al.

The presentation of results from Systematic Literature Reviews (SLRs) is generally done using tables. Prior research suggests that results summarized in tables are often difficult for readers to understand. One alternative to improve results' comprehensibility is to use graphical representations. The aim of this work is twofold: first, to investigate whether graph representations result is better comprehensibility than tables when presenting SLR results; second, to investigate whether interpretation using graphs impacts on performance, as measured by the time consumed to analyse and understand the data. We selected an SLR published in the literature and used two different formats to represent its results - tables and graphs, in three different combinations: (i) table format only; (ii) graph format only; and (iii) a mixture of tables and graphs. We conducted an experiment that compared the performance and capability of experts in SLR, as well as doctoral and masters students, in analysing and understanding the results of the SLR, as presented in one of the three different forms. We were interested in examining whether there is difference between the performance of participants using tables and graphs. The graphical representation of SLR data led to a reduction in the time taken for its analysis, without any loss in data comprehensibility. For our sample the analysis of graphical data proved to be faster than the analysis of tabular data. However , we found no evidence of a difference in comprehensibility whether using tables, graphical format or a combination. Overall we argue that graphs are a suitable alternative to tables when it comes to representing the results of an SLR.

Jim Buchan, Ling Li, Stephen G. MacDonell

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.