Archetypal personalities of software engineers and their work preferences: a new perspective for empirical studies

As the area of Software Engineering (SE) matures the role of human factors in software development is commonly recognized as important. Increasingly we see empirical studies that investigate the connection between, for example, personalities and preferences, attitudes or performances of software engineers. Statistical analysis holds a key role by providing the means for uncovering associations between various facets of human factors and behavioral effects on projects and outcomes. Traditional statistical techniques tend to explore and interpret the multidimensional personality and behavioral data from an “average-point” perspective, targeting central trends. This paper introduces a methodology with statistical tools that can provide a new and different perspective for this type of SE data. It seeks the boundaries of a psychometric dataset and discovers reference or “benchmark” personalities, the archetypal personalities. Then, the method examines the placement of all individuals in the dataset in relation to the archetypes. Furthermore, the SE preference characteristics, or generally, any other types of behavioral SE data, are analyzed with respect to the archetypes. As a case to exemplify the methodology we analyze personality and project preference data from 276 master level SE students and compare to previous “average-point” statistical analysis of the same data. We also discuss how Archetypal Analysis, the heart of the proposed methodology, combined with multi-correspondence analysis might be of general use in empirical SE.     

Links between the personalities,views and attitudes of software engineers

Context:Successful software development and management depends not only on the technologies, methods and processes employed but also on the judgments and decisions of the humans involved. These, in turn, are affected by the basic views and attitudes of the individual engineers.Objective:The objective of this paper is to establish if these views and attitudes can be linked to the personalities of software engineers.Methods:We summarize the literature on personality and software engineering and then describe an empirical study on 47 professional engineers in ten different Swedish software development companies. The study evaluated the personalities of these engineers via the IPIP 50-item five-factor personality test and prompted them on their attitudes towards and basic views on their professional activities.Results:We present extensive statistical analyses of their responses to show that there are multiple, significant associations between personality factors and software engineering attitudes. The tested individuals are more homogeneous in personality than a larger sample of individuals from the general population.Conclusion:Taken together, the methodology and personality test we propose and the associated statistical analyses can help find and quantify relations between complex factors in software engineering projects in both research and practice.     

Investigations about replication of empirical studies in software engineering: A systematic mapping study

ContextTwo recent mapping studies which were intended to verify the current state of replication of empirical studies in Software Engineering (SE) identified two sets of studies: empirical studies actually reporting replications (published between 1994 and 2012) and a second group of studies that are concerned with definitions, classifications, processes, guidelines, and other research topics or themes about replication work in empirical software engineering research (published between 1996 and 2012).ObjectiveIn this current article, our goal is to analyze and discuss the contents of the second set of studies about replications to increase our understanding of the current state of the work on replication in empirical software engineering research.MethodWe applied the systematic literature review method to build a systematic mapping study, in which the primary studies were collected by two previous mapping studies covering the period 1996–2012 complemented by manual and automatic search procedures that collected articles published in 2013.ResultsWe analyzed 37 papers reporting studies about replication published in the last 17 years. These papers explore different topics related to concepts and classifications, presented guidelines, and discuss theoretical issues that are relevant for our understanding of replication in our field. We also investigated how these 37 papers have been cited in the 135 replication papers published between 1994 and 2012.ConclusionsReplication in SE still lacks a set of standardized concepts and terminology, which has a negative impact on the replication work in our field. To improve this situation, it is important that the SE research community engage on an effort to create and evaluate taxonomy, frameworks, guidelines, and methodologies to fully support the development of replications.     

Are team personality and climate related to satisfaction and software quality? Aggregating results from a twice replicated experiment

ContextResearch into software engineering teams focuses on human and social team factors. Social psychology deals with the study of team formation and has found that personality factors and group processes such as team climate are related to team effectiveness. However, there are only a handful of empirical studies dealing with personality and team climate and their relationship to software development team effectiveness.ObjectiveWe present aggregate results of a twice replicated quasi-experiment that evaluates the relationships between personality, team climate, product quality and satisfaction in software development teams.MethodOur experimental study measures the personalities of team members based on the Big Five personality traits (openness, conscientiousness, extraversion, agreeableness, neuroticism) and team climate factors (participative safety, support for innovation, team vision and task orientation) preferences and perceptions. We aggregate the results of the three studies through a meta-analysis of correlations. The study was conducted with students.ResultsThe aggregation of results from the baseline experiment and two replications corroborates the following findings. There is a positive relationship between all four climate factors and satisfaction in software development teams. Teams whose members score highest for the agreeableness personality factor have the highest satisfaction levels. The results unveil a significant positive correlation between the extraversion personality factor and software product quality. High participative safety and task orientation climate perceptions are significantly related to quality.ConclusionsFirst, more efficient software development teams can be formed heeding personality factors like agreeableness and extraversion. Second, the team climate generated in software development teams should be monitored for team member satisfaction. Finally, aspects like people feeling safe giving their opinions or encouraging team members to work hard at their job can have an impact on software quality. Software project managers can take advantage of these factors to promote developer satisfaction and improve the resulting product.     

Motivation in software engineering industrial practice: A cross-case analysis of two software organisations

ContextThe research about motivation in software engineering has provided important insights into characterizing factors and outcomes related to motivation. However, the complex relationships among these factors, including the moderating and mediating effects of organisational and individual characteristics, still require deeper explanatory investigation.ObjectiveOur general goal is to build explanatory theories of motivation in different software organisations and to integrate these local theories towards a comprehensive understanding of the role of motivation in the effectiveness of the individuals and the teams in which they work. In this article, we describe the integrative synthesis of the results of two case studies performed with software organisations in different business contexts.MethodWe performed two case studies using a multiple-case, replication design, focusing on the software engineers as the unit of analysis. For 13 months, we conducted semi structured interviews, diary studies, and document analyses, and analysed the collected data using grounded theory procedures. The results of the two cases were synthesized using a meta-ethnography supported process.ResultsWe built translations of the concepts and propositions from the two studies into one another. We then used the translations to build a central story of motivation that synthesizes the individual stories. This synthesis is contextualized by the differences in organisational and individual characteristics.ConclusionThe differences in organisational contexts and in the characteristics of the software engineers in each study provided rich explanations for contrasts in perceptions and feelings about motivation in both organisations. The theory that emerged from the synthesis, supported by these explanations, provides a deeper understanding of the interplay between motivators and outcomes, and the needs and personal goals of the software engineers. This theory also characterises the role of team cohesion in motivation, advancing previous models about motivation in software engineering.     

Toward automated feature model configuration with optimizing non-functional requirements

ContextA software product line is a family of software systems that share some common features but also have significant variabilities. A feature model is a variability modeling artifact, which represents differences among software products with respect to the variability relationships among their features. Having a feature model along with a reference model developed in the domain engineering lifecycle, a concrete product of the family is derived by binding the variation points in the feature model (called configuration process) and by instantiating the reference model.ObjectiveIn this work we address the feature model configuration problem and propose a framework to automatically select suitable features that satisfy both the functional and non-functional preferences and constraints of stakeholders. Additionally, interdependencies between various non-functional properties are taken into account in the framework.MethodThe proposed framework combines Analytical Hierarchy Process (AHP) and Fuzzy Cognitive Maps (FCM) to compute the non-functional properties weights based on stakeholders’ preferences and interdependencies between non-functional properties. Afterwards, Hierarchical Task Network (HTN) planning is applied to find the optimal feature model configuration.ResultOur approach improves state-of-art of feature model configuration by considering positive or negative impacts of the features on non-functional properties, the stakeholders’ preferences, and non-functional interdependencies. The approach presented in this paper extends earlier work presented in [1] from several distinct perspectives including mechanisms handling interdependencies between non-functional properties, proposing a novel tooling architecture, and offering visualization and interaction techniques for representing functional and non-functional aspects of feature models.Conclusionour experiments show the scalability of our configuration approach when considering both functional and non-functional requirements of stakeholders.     

HCI and business practices in a collaborative method for augmented reality systems

ContextEvery interactive system is composed of a functional core and a user interface. However, the software engineering (SE) and human–computer interaction (HCI) communities do not share the same methods, models or tools. This usually induces a large work overhead when specialists from the two domains try to connect their applicative studies, especially when developing augmented reality systems that feature complex interaction cores.ObjectiveWe present in this paper the essential activities and concepts of a development method integrating the SE and HCI development practices, from the specifications down to the design, as well as their application on a case study.MethodThe efficiency of the method was tested in a qualitative study involving four pairs of SE and HCI experts in the design of an application for which an augmented reality interaction would provide better user performance than a classic interactive system. The effectivity of the method was evaluated in a qualitative study comparing the quality of three implementations of the same application fragment (based on the same analysis model), using software engineering metrics.ResultsThe first evaluation confirmed the ease of use of our method and the relevance of our tools for guiding the design process, but raised concerns on the handling of conflicting collaborative activities. The second evaluation gave indications that the structure of the analysis model facilitates the implementation of quality software (in terms of coupling, stability and complexity).ConclusionIt is concluded that our method enables design teams with different backgrounds in application development to collaborate for integrating augmented reality applications with information systems. Areas of improvement are also described.     

Global software testing under deadline pressure: Vendor-side experiences

ContextIn the era of globally-distributed software engineering, the practice of global software testing (GST) has witnessed increasing adoption. Although there have been ethnographic studies of the development aspects of global software engineering, there have been fewer studies of GST, which, to succeed, can require dealing with unique challenges.ObjectiveTo address this limitation of existing studies, we conducted, and in this paper, report the findings of, a study of a vendor organization involved in one kind of GST practice: outsourced, offshored software testing.MethodWe conducted an ethnographically-informed study of three vendor-side testing teams over a period of 2 months. We used methods, such as interviews and participant observations, to collect the data and the thematic-analysis approach to analyze the data.FindingsOur findings describe how the participant test engineers perceive software testing and deadline pressures, the challenges that they encounter, and the strategies that they use for coping with the challenges. The findings reveal several interesting insights. First, motivation and appreciation play an important role for our participants in ensuring that high-quality testing is performed. Second, intermediate onshore teams increase the degree of pressure experienced by the participant test engineers. Third, vendor team participants perceive productivity differently from their client teams, which results in unproductive-productivity experiences. Lastly, participants encounter quality-dilemma situations for various reasons.ConclusionThe study findings suggest the need for (1) appreciating test engineers’ efforts, (2) investigating the team structure’s influence on pressure and the GST practice, (3) understanding culture’s influence on other aspects of GST, and (4) identifying and addressing quality-dilemma situations.     

Testing scientific software: A systematic literature review

ContextScientific software plays an important role in critical decision making, for example making weather predictions based on climate models, and computation of evidence for research publications. Recently, scientists have had to retract publications due to errors caused by software faults. Systematic testing can identify such faults in code.ObjectiveThis study aims to identify specific challenges, proposed solutions, and unsolved problems faced when testing scientific software.MethodWe conducted a systematic literature survey to identify and analyze relevant literature. We identified 62 studies that provided relevant information about testing scientific software.ResultsWe found that challenges faced when testing scientific software fall into two main categories: (1) testing challenges that occur due to characteristics of scientific software such as oracle problems and (2) testing challenges that occur due to cultural differences between scientists and the software engineering community such as viewing the code and the model that it implements as inseparable entities. In addition, we identified methods to potentially overcome these challenges and their limitations. Finally we describe unsolved challenges and how software engineering researchers and practitioners can help to overcome them.ConclusionsScientific software presents special challenges for testing. Specifically, cultural differences between scientist developers and software engineers, along with the characteristics of the scientific software make testing more difficult. Existing techniques such as code clone detection can help to improve the testing process. Software engineers should consider special challenges posed by scientific software such as oracle problems when developing testing techniques.     

Effect of personality type on structured tool comprehension performance

Accurate understanding of software requirements by end users and software developers is important to ensure a high quality software product. While comprehension performance on systems analysis tools has been studied in the past, there is little research that examined the influence of personality type of an individual on his/her performance. This paper has two objectives. First, the research uncovers the relationships between personality types (introvert/extrovert, sensing/intuitive, feeling/thinking, and perceptive/judging) and comprehension performance (accuracy and speed) of users/developers using the structured tools: Decision Tables (DT), Nassi–Schneiderman Charts (NS) and Structured English (SE). Second, it examines the trade-offs between comprehension accuracy and speed for each personality type. Using laboratory experiments, we measured individual performance with the three structured tools. We found that introverts and feeling personalities comprehended more accurately with DT; thinking and intuitive personalities comprehended more accurately with NS and SE. The comprehension accuracy increased with time more for SE than for DT and NS. The results show the most suitable combinations of structured tools and personality types for high comprehension. The results also provide guidelines to managers with tight project schedules, such as structured tools that are easier/faster to understand and the matching personalities who can comprehend faster.     

The role of social interaction in software effort estimation: Unpacking the “magic step” between reasoning and decision-making

ContextSoftware effort estimation is a core task regarding planning, budgeting and controlling software development projects. However, providing accurate effort estimates is challenging. Estimation work is increasingly group based, and to support it, there is a need to reveal how work practices are carried out as collaborative efforts.ObjectiveThis paper examines the use of concepts in software effort estimation by analysing group work as communicative practice. The objective is to improve our understanding of how software professionals invoke different types of knowledge when talking, reasoning and reaching a decision on a software effort estimate.MethodEstimation meetings in the industry where planning poker was used as the estimation method have been video recorded and analysed by means of the interaction analysis technique, focusing on the communicative and collaborative aspects of the group work.ResultsThe user story mediates the types of resources and knowledge needed to solve the task. Concepts from the knowledge domain are used to frame the task and allow the participants to reach consensus, sufficient to take the next step in the problem-solving activity. Individual knowledge seems to be the dominating orientation when it comes to specifying the work needed for solving the tasks.ConclusionThe step from reasoning to decision-making has been called the “magic step” in software effort estimation. We argue that the magic step is found in the analysis of the social interaction in which the concepts used are anchored in the knowledge domain of software engineering and in the historical experiences of the participants and subsequently become activated. We propose that by taking a socio-cultural perspective on concepts in activities, the ways in which software professionals reach a decision can be unpacked. The paper contributes to an understanding of the role of concepts in group work and of software effort estimation as a specific work practice.     

CCIC: Clustering analysis classes to identify software components

ContextComponent identification during software design phase denotes a process of partitioning the functionalities of a system into distinct components. Several component identification methods have been proposed that cannot be customized to software architect’s preferences.ObjectivesIn this paper, we propose a clustering-based method by the name of CCIC (Clustering analysis Classes to Identify software Components) to identify logical components from analysis classes according to software architect’s preferences.MethodCCIC uses a customized HEA (Hierarchical Evolutionary Algorithm) to automatically classify analysis classes into appropriate logical components and avoid the problem of searching for the proper number of components. Furthermore, it allows software architects to determine the constraints in their deployment and implementation framework.ResultsA series of experiments were conducted for four real-world case studies according to various proposed weighting schemes.ConclusionAccording to experimental results, it is concluded that CCIC can identify more cohesive and independent components with respect to software architect’s preferences in comparison with the existing component identification methods such as FCA-based and CRUD-based methods.     

Task-specific information retrieval systems for software engineers

This paper discusses the development of task-specific information retrieval systems for software engineers. We discuss how software engineers interact with information and information retrieval systems and investigate to what extent a domain-specific search and recommendation system can be developed in order to support their work related activities. We have conducted a user study which is based on the “Cognitive Research Framework” to identify the relation between the information objects used during the code development (code snippets and search queries), the tasks users engage in and the associated use of search interfaces. Based on our user studies, a questionnaire and an automated observation of user interactions with the browser and software development environment, we identify that software engineers engage in a finite number of work related tasks and they also develop a finite number of “work practices”/“archetypes of behaviour”. Secondly we identify a group of domain specific behaviours that can successfully be used as a source of strong implicit relevance feedback. Based on our results, we design a snippet recommendation interface, and a code related recommendation interface which are embedded within the standard search engine.     

Shared service recommendations from requirement specifications: A hybrid syntactic and semantic toolkit

ContextSoftware Requirement Specifications (SRSs) are central to software lifecycles. An SRS defines the functionalities and constraints of a desired software system, hence it often serves as reference for further development. Software lifecycles concerned with the conversion of traditional systems into more service-oriented infrastructures can benefit from understanding potential shared capabilities through the analysis of SRSs.ObjectiveIn this paper, we propose an automated approach capable of recommending shared software services from multiple text-based SRSs created by different organizations. Our goal is to facilitate the identification of overlapping requirements in these specifications and subsequently recommend shared components, which promotes software reuse. The shared components can be implemented as services that are invoked across different systems.MethodOur approach leverages the syntactic similarity of the SRS text augmented with semantic information derived from the WordNet database. This work extends our earlier studies by introducing an algorithm that utilizes noun, verb, and predicate relations to enhance the discovery of equivalent requirements and the recommendation of reusable services. A prototype system is implemented to evaluate the approach and experimental results have shown effective recommendation of requirements and their realized shared services.ResultsOur automatic recommendation approach generates recommendations in few minutes compared to 9 h when services are manually inspected by developers. Our approach is also able to recommend services that are overlooked by the same developers, and to identify similarity between requirements even if these requirements are reworded.ConclusionWe show through experimentation that we can efficiently recommend services by leveraging both the syntactical structure and the semantic information of a requirements document and that our approach is more effective than the manual selection of services by experts. We also show that our approach is effective in detecting similar requirements for a single system and hence discovering opportunities for software reuse.     

Gamification in software engineering – A systematic mapping

ContextGamification seeks for improvement of the user’s engagement, motivation, and performance when carrying out a certain task, by means of incorporating game mechanics and elements, thus making that task more attractive. Much research work has studied the application of gamification in software engineering for increasing the engagement and results of developers.ObjectiveThe objective of this paper is to carry out a systematic mapping of the field of gamification in software engineering in an attempt to characterize the state of the art of this field identifying gaps and opportunities for further research.MethodWe carried out a systematic mapping with a view to finding the primary studies in the existing literature, which were later classified and analyzed according to four criteria: the software process area addressed, the gamification elements used, the type of research method followed, and the type of forum in which they were published. A subjective evaluation of the studies was also carried out to evaluate them in terms of methodology, empirical evidence, integration with the organization, and replicability.ResultsAs a result of the systematic mapping we found 29 primary studies, published between January 2011 and June 2014. Most of them focus on software development, and to a lesser extent, requirements, project management, and other support areas. In the main, they consider very simple gamification mechanics such as points and badges, and few provide empirical evidence of the impact of gamification.ConclusionsExisting research in the field is quite preliminary, and more research effort analyzing the impact of gamification in SE would be needed. Future research work should look at other game mechanics in addition to the basic ones and should tackle software process areas that have not been fully studied, such as requirements, project management, maintenance, or testing. Most studies share a lack of methodological support that would make their proposals replicable in other settings. The integration of gamification with an organization’s existing tools is also an important challenge that needs to be taken up in this field.     

A systematic review of systematic review process research in software engineering

ContextMany researchers adopting systematic reviews (SRs) have also published papers discussing problems with the SR methodology and suggestions for improving it. Since guidelines for SRs in software engineering (SE) were last updated in 2007, we believe it is time to investigate whether the guidelines need to be amended in the light of recent research.ObjectiveTo identify, evaluate and synthesize research published by software engineering researchers concerning their experiences of performing SRs and their proposals for improving the SR process.MethodWe undertook a systematic review of papers reporting experiences of undertaking SRs and/or discussing techniques that could be used to improve the SR process. Studies were classified with respect to the stage in the SR process they addressed, whether they related to education or problems faced by novices and whether they proposed the use of textual analysis tools.ResultsWe identified 68 papers reporting 63 unique studies published in SE conferences and journals between 2005 and mid-2012. The most common criticisms of SRs were that they take a long time, that SE digital libraries are not appropriate for broad literature searches and that assessing the quality of empirical studies of different types is difficult.ConclusionWe recommend removing advice to use structured questions to construct search strings and including advice to use a quasi-gold standard based on a limited manual search to assist the construction of search stings and evaluation of the search process. Textual analysis tools are likely to be useful for inclusion/exclusion decisions and search string construction but require more stringent evaluation. SE researchers would benefit from tools to manage the SR process but existing tools need independent validation. Quality assessment of studies using a variety of empirical methods remains a major problem.     

A HCI technique for improving requirements elicitation

ContextTo develop usable software we need to understand the users that will interact with the system. Personas is a HCI technique that gathers information about users in order to comprehend their characteristics. This information is used to define fictitious persons on which development should focus. Personas provides an understanding of the user, often overlooked in SE developments.ObjectiveThe goal of our research is to modify Personas to readily build the technique into the requirements stage of regular SE developments.MethodWe tried to apply Cooper’s version of the Personas technique and we found shortcomings in both the definition of the procedure to be enacted and the formalization of the product resulting from the execution of each step of the Personas technique. For each of these limitations (up to a total of 11), we devised an improvement to be built into Personas. We have incorporated these improvements into a SE version of Personas. The improved Personas avoid the weaknesses encountered by an average software developer unfamiliar with HCI techniques applying the original Personas.ResultsWe aim to improve requirements elicitation through the use of Personas. We have systematized and formalized Personas in the SE tradition in order to build this new version of the technique into the requirements stage. We have applied our proposal in an application example.ConclusionThe integration of Personas into the SE requirements stage might improves the understanding of what the software product should do and how it should behave. We have modified the HCI Personas technique to comply with the levels of systematization required by SE. We have enriched the SE requirements process by incorporating Personas activities into requirements activities. Requirements elicitation and requirements analysis are the RE activities most affected by incorporating Personas.     

Using metrics in Agile and Lean Software Development – A systematic literature review of industrial studies

ContextSoftware industry has widely adopted Agile software development methods. Agile literature proposes a few key metrics but little is known of the actual metrics use in Agile teams.ObjectiveThe objective of this paper is to increase knowledge of the reasons for and effects of using metrics in industrial Agile development. We focus on the metrics that Agile teams use, rather than the ones used from outside by software engineering researchers. In addition, we analyse the influence of the used metrics.MethodThis paper presents a systematic literature review (SLR) on using metrics in industrial Agile software development. We identified 774 papers, which we reduced to 30 primary studies through our paper selection process.ResultsThe results indicate that the reasons for and the effects of using metrics are focused on the following areas: sprint planning, progress tracking, software quality measurement, fixing software process problems, and motivating people. Additionally, we show that although Agile teams use many metrics suggested in the Agile literature, they also use many custom metrics. Finally, the most influential metrics in the primary studies are Velocity and Effort estimate.ConclusionThe use of metrics in Agile software development is similar to Traditional software development. Projects and sprints need to be planned and tracked. Quality needs to be measured. Problems in the process need to be identified and fixed. Future work should focus on metrics that had high importance but low prevalence in our study, as they can offer the largest impact to the software industry.     

Understanding replication of experiments in software engineering: A classification

ContextReplication plays an important role in experimental disciplines. There are still many uncertainties about how to proceed with replications of SE experiments. Should replicators reuse the baseline experiment materials? How much liaison should there be among the original and replicating experimenters, if any? What elements of the experimental configuration can be changed for the experiment to be considered a replication rather than a new experiment?ObjectiveTo improve our understanding of SE experiment replication, in this work we propose a classification which is intend to provide experimenters with guidance about what types of replication they can perform.MethodThe research approach followed is structured according to the following activities: (1) a literature review of experiment replication in SE and in other disciplines, (2) identification of typical elements that compose an experimental configuration, (3) identification of different replications purposes and (4) development of a classification of experiment replications for SE.ResultsWe propose a classification of replications which provides experimenters in SE with guidance about what changes can they make in a replication and, based on these, what verification purposes such a replication can serve. The proposed classification helped to accommodate opposing views within a broader framework, it is capable of accounting for less similar replications to more similar ones regarding the baseline experiment.ConclusionThe aim of replication is to verify results, but different types of replication serve special verification purposes and afford different degrees of change. Each replication type helps to discover particular experimental conditions that might influence the results. The proposed classification can be used to identify changes in a replication and, based on these, understand the level of verification.