Chintan Amrit

Detecting Coordination Problems in Collaborative Software Development Environments

Abstract Software development is rarely an individual effort and generally involves teams of developers collaborating to generate good reliable code. Among the software code there exist technical dependencies that arise from software components using services from other components. The different ways of assigning the design, development, and testing of these software modules to people can cause various coordination problems among them. We claim that the collaboration of the developers, designers and testers must be related to and governed by the technical task structure. These collaboration practices are handled in what we call Socio-Technical Patterns. The TESNA project (Technical Social Network Analysis) we report on in this paper addresses this issue. We propose a method and a tool that a project manager can use in order to detect the socio-technical coordination problems. We test the method and tool in a case study of a small and innovative software product company.

Process Prediction in Noisy Data Sets: A Case Study in a Dutch Hospital

Predicting the amount of money that can be claimed is critical to the effective running of an Hospital. In this paper we describe a case study of a Dutch Hospital where we use process mining to predict the cash flow of the Hospital. In order to predict the cost of a treatment, we use different data mining techniques to predict the sequence of treatments administered, the duration and the final ”care product” or diagnosis of the patient. While performing the data analysis we encountered three specific kinds of noise that we call sequence noise, human noise and duration noise. Studies in the past have discussed ways to reduce the noise in process data. However, it is not very clear what effect the noise has to different kinds of process analysis. In this paper we describe the combined effect of sequence noise, human noise and duration noise on the analysis of process data, by comparing the performance of several mining techniques on the data.

Exploring the impact of socio-technical core-periphery structures in open source software development

In this paper we apply the social network concept of core-periphery structure to the socio-technical structure of a software development team. We propose a socio-technical pattern that can be used to locate emerging coordination problems in Open Source projects. With the help of our tool and method called TESNA, we demonstrate a method to monitor the socio-technical core-periphery movement in Open Source projects. We then study the impact of different core-periphery movements on Open Source projects. We conclude that a steady core-periphery shift towards the core is beneficial to the project, whereas shifts away from the core are clearly not good. Furthermore, oscillatory shifts towards and away from the core can be considered as an indication of the instability of the project. Such an analysis can provide developers with a good insight into the health of an Open Source project. Researchers can gain from the pattern theory, and from the method we use to study the core-periphery movements.

How Do Online Citizens Persuade Fellow Voters? Using Twitter During the 2012 Dutch Parliamentary Election Campaign

This article explores how Twitter was used by voters to participate in electoral campaigning during the Dutch election campaign of 2012. New social media networks like Twitter are believed to be efficient tools of communication between electoral candidates and voters during electoral campaign periods. Yet only few studies have been conducted so far to discover in what way the content of online discussions is being used for campaigning. In particular, there have been very few studies of electoral campaigning, which study the content of the social media messages sent by citizens. In order to understand the extent to which citizens utilize Twitter in different forms of electoral campaigning—that is, persuading followers about voting for a particular party or to conduct negative campaigning, we conducted an automated content analysis of a large corpus of tweets collected during the Dutch parliamentary election campaign of 2012. Our findings show that citizens participate significantly in online electoral campaigning on Twitter, whereas they differ from professional users in the style of campaigning. Persuasive campaigning is observed to a lesser extent among citizens than among politicians, while citizens more commonly use negative campaigning. Moreover, qualitative content analysis of campaigning tweets by citizens has revealed that expressions of emotions and opinions make up a large majority of negative tweets, indicating that citizens regard Twitter more as an outlet for expressing discontent than as a medium for negative campaigning.

Cooperation between information system development and operations: a literature review

Software development can profit from improvements in the deployment and maintenance phases. DevOps improves these phases through a collection of principles and practices, centered around close collaboration between Development and Operations personnel. Both sides have paid little attention to issues faced by each other. Yet knowledge sharing is invaluable. Development personnel can for example make software more robust by implementing scalability and performance features desired by operations personnel.

Human factors in software development: On its underlying theories and the value of learning from related disciplines. A guest editorial introduction to the special issue

Human factors play a very important role in Software Development [1]. According to Avison et al. [2] ‘‘Failure to include human factors may explain some of the dissatisfaction with conventional information systems development methodologies; they do not address real organizations’’ (p95 [2]). Software development has been characterized in essence as a human activity [3] where human factors play a critical role [4]. While the area of Human Factors spans a lot of different and diverse concepts and theories, the human factors aspects most often studied in software engineering research include coordination [5,6], collaboration in the development process [7–9], trust [10], expert recommendation [11], program comprehension [12], knowledge management [13,14] and culture [15]. The growing importance of human factors in software development research is clearly evidenced by the fact that the ICSE 2014 conference a track entirely devoted to Human factors, namely, ‘‘Social Aspects of Software Engineering’’. Furthermore, the 2014 ICSE conference keynote by James Herbsleb [16] presented the theory of socio-technical coordination and represented a call for further development of theories on coordination in Software Engineering (SE). In this editorial we not only reiterate this call, but also suggest SE researchers to draw on reference disciplines such as the field of Information Systems to borrow well-established theories. In the next section we first present empirical evidence on the importance of research involving Human Factors in the field of Software Engineering. We then run a citation analysis exercise to identify the prominent theories related to Human Factors in SD.

Gentoo package dependencies over time

Open source distributions such as Gentoo need to accurately track dependency relations between software packages in order to install working systems. To do this, Gentoo has a carefully authored database containing those relations. In this paper, we extract the Gentoo package dependency graph and its changes over time. The final dependency graph spans 15 thousand open source projects and 80 thousand dependency relations. Furthermore, the development of this graph is tracked over time from the beginning of the Gentoo project in 2000 to the first quarter of 2012, with monthly resolution. The resulting dataset provides many opportunities for research. In this paper we explore cluster analysis to reveals meaningful relations between packages and in a separate paper we analyze changes in the dependencies over time to get insights in the innovation dynamics of open source software.

Predictive analytics for truck arrival time estimation: a field study at a European distribution center

Distribution centres (DCs) are the hubs connecting transport streams in the supply chain. The synchronisation of coming and going cargo at a DC requires reliable arrival times. To achieve this, a reliable method to predict arrival times is needed. A literature review was performed to find the factors that are reported to predict arrival time: congestion, weather, time of day and incidents. While travel time receives considerable attention, there is a gap in literature concerning arrival vs. travel/journey time prediction. None of the reviewed papers investigate arrival time: all the papers found investigate travel time. Arrival time is the consequence of travel time in combination with departure time, so though the travel time literature is applicable, the human factor involved in planning the time of departure can affect the arrival time (especially for truck drivers who have travelled the same route before). To validate the factors that influence arrival time, the authors conducted a detailed case study that includes a survey of 230 truckers, a data analysis and a data mining experiment, using real traffic and weather data. These show that although a ‘big data’ approach delivers valuable insights, the predictive power is not as high as expected; other factors, such as human or organisational factors, could influence arrival time, and it is concluded that such organisational factors should be considered in future predictive models.

How Healthy Is My Project? Open Source Project Attributes as Indicators of Success

Determining what factors can influence the successful outcome of a software project has been labeled by many scholars and software engineers as a difficult problem. In this paper we use machine learning to create a model that can determine the stage a software project has obtained with some accuracy. Our model uses 8 Open Source project metrics to determine the stage a project is in. We validate our model using two performance measures; the exact success rate of classifying an Open Source Software project and the success rate over an interval of one stage of its actual performance using different scales of our dependent variable. In all cases we obtain an accuracy of above 70% with one away classification (a classification which is away by one) and about 40% accuracy with an exact classification. We also determine the factors (according to one classifier) that uses only eight variables among all the variables available in SourceForge, that determine the health of an OSS project.

Can Agile Software Tools Bring the Benefits of a Task Board to Globally Distributed Teams

Software-based tooling has become an essential part of globally disitrbuted software development. In this study we focus on the usage of such tools and task boards in particular. We investigate the deployment of these tools through a field research in 4 different companies that feature agile and globally distributed development teams. We interviewed a total of 15 developers and concluded that the paper-based task board currently still has many advantages when compared to its software-based solution. Our findings indicate that the majority of the investigated companies that use the agile method Scrum also work with a software tool to support Scrum. While distributed teams use a software only approach, a large portion of collocated teams we studied utilize a combination of a paper based task board and the archiving and integration properties of the software solution. We reflect on these findings through the lens of media synchronicity theory and conclude that this theory is useful for explaining the current use and future development of software tools to support agile globally distributed development teams.