Archive for the 'General' Category

EASE 2016: HASE receives Best Paper Award

The recent research “Benefits and Limitations of Job Rotation in Software Organizations: A Systematic Literature Review” published in the 20th International Conference on Evaluation and Assessment in Software Engineering (EASE 2016) has received a best paper award in the conference which was venued in Limerick, Ireland.

13321821_489586124573468_6554411419985212572_n 13321932_1218941611450643_5507960537516412585_n

 

Advertisements

Best Paper award at ESEM 2011

The article “An Empirical Study on the Use of Team Building Criteria in Software Projects”, presented at ESEM2011 in Banff, Canada, received the joint Best Paper Award. The article can be found at 10.1109/ESEM.2011.14 and was co-authored by Fabio Q. B. da Silva, A. César C. França, Tatiana B. Gouveia, Cleviton V. F. Monteiro, Elisa S. F. Cardozo, and Marcos Suassuna.

Seminar at Brigham Young University – Antecedents of Effectiveness

The definition of effectiveness is important because what affects effectiveness (positive and negatively) depends on this definition, as well as the identification of factors that moderate or mediate the effects.

Our first studies on antecedents of effectiveness were on motivation (2007…). The “level of effort applied to tasks” is proposed as an antecedent of effectiveness by Hackman (1987) and supported in Yeatts and Hyten’s (1998) model, and this level of effort is driven by motivation. These models hypothesize that the more motivated the individual, more effort he or she applies to the task. Therefore, understanding motivation was an important step to understand effectiveness. Using a set of 20 motivators presented in a systematic literature review developed by Sarah Beecham and colleagues (Beecham 2008), we conducted a survey with software engineers from industry to identify the influence of each motivator on individual motivation. We grouped the motivators using principal component analysis and arrived at results that fit quite well on Hackman’s model (Hackman, 1987). We used these results to support the proposition of guidelines to develop motivational programs.

In 2009, we started a study about antecedents of success in Agile development. We focused that study on SCRUM projects. Our goal was to correlate the use of agile practices, as proposed as success factors by Chow and Cao, and the success of projects that used SCRUM. Our results (reported here and summarized here), showed that, in the particular context studied, only a subset of the success factors proposed by Chow and Chow correlated to project success.

We also investigated another type of antecedents that are related to team composition. In 2008, we started a mix method studie involving qualitative and quantitative research, to identify the criteria used by project managers to select members for software teams. We also correlated the level of use (formal, informal, not used) of these criteria with project success (a type of team effectiveness). The results, published last year at ESEM’2011, showed that the use of the criteria correlates with project success. That is, teams that were built using the set of criteria in a rigorous way were those that achieved more success.

So, at this point, we think we probably know (0OI) a couple of results things antecedents of effectiveness. However, we also know that we don’t know a lot of other things (1OI). For instance,

. how is motivation related to effectiveness? in other words, how is motivation related to all facets of effectiveness, including productivity, team member satisfaction, team continuity, etc.?

. what are the contextual factors that made only a few success factors correlate to project success in our SCRUM study? Are Chow and Cao wrong? We don’t think so. What is more likely is that (1) the success factors depend on contextual factors (moderators and mediators) that were not properly addressed because we did not know about them (2OI) and/or (2) the success factors affect different aspects of effectiveness that were not measured because we used a very simple (maybe oversimple) operationalization of success.

. it seems clear (from our results and also from various other studies in group theory) that team composition affects effectiveness. What is less clear is how team composition affects effectiveness and how task type and development process moderates this effect.

I plan to show the results of the research described above and then elaborate  more on the questions that we are investigating with respect to antecedents of effectiveness. At this point in the seminar, I hope to start to show the model we are consolidating (from other researchers) and testing (with our empirical studies).

Fabio Silva.

References

Beecham, S., et al., 2008. Motivation in software engineering: a systematic literature review. Information and software Technology, vol. 50. Elsevier, pp. 860– 878.

T. Chow; D. Cao, (2007) A Survey Study of Critical Success Factors in Agile Software Projects. The Journal of Systems and Software, n. 81, pp. 961–971.

Hackman J (1987) The design of work teams. Handbook of organizational behavior 315-342.

Yeatts DE, Hyten C (1998) High-performing self-managed work teams. Sage Publications, Inc.

Seminar at Brigham Young University – Software Team Effectiveness

One of the topics I would like to discuss is “Team Effectiveness”. This is a complex topic that has been studied from different perspectives in group research.

Hackman (1987) has argued that, for teams in organizations (i.e., in practice and not in a experimental lab setting), effectiveness is more complex than counting “right answers” or timing the development of a task. Hackman argues that certain team outputs can be difficult to quantify. Furthermore, teams in organizational contexts tend to work together for a much longer time than the participants in a laboratory experiment, and what happens to a team during the development of one project may affect the feasibility of this team working together in the future. In his model, Hackman defines effectiveness as a multiple construct composed of

1. Acceptance of team’s output or results by those that receive or review them (Client Satisfaction with results)

2. Maintained or enhanced capability of members of the team to work together in the future (Team Viability)

3. Team member’s satisfaction has not decreased the the team experience (Member satisfaction with teamwork)

Cohen (1993) asks the question of whether we consider a team that produces what expected as being successful even if the team members present low morale, are not satisfied with the work, come late to work, or the team turnover is right. In her model, Cohen also considers effectiveness as a multidimensional constructed composed of:

1. Performance: costs, productivity, quality.

2. Member attitudes: satisfaction, trust, commitment.

3. Withdrawal behaviors: absenteeism, turnover.

Yeats and Hyten (1998) acknowledge that effectiveness is multi-dimensional, but only performance as client satisfaction and team economic viability. Their argument is that using a more complex, multi-dimensional view of effectiveness would make a model less accurate, since each dimension is affected differently by other factors that influence team effectiveness.

In the seminar, I will present some of our studies in which distinct definitions of effectiveness were used. I would like to discuss the implications (practical and theoretical) of using simple or more complex definitions in understanding the effectiveness of software teams in practice.

Fabio Silva.

References

Cohen SG (1993) The Design of Effective Self-managing Teams. Advances in Interdisciplinary Studies of Work Teams. Vol. 1 Theories of Self-managing Working Teams 1:

Hackman J (1987) The design of work teams. Handbook of organizational behavior 315-342.

Yeatts DE, Hyten C (1998) High-performing self-managed work teams. Sage Publications, Inc.

Seminar at Brigham Young University – January, 19th, 2012.

Professor Charles Knudson gently invited me to present a seminar at the  Computer Science Department at Brigham Young University in Provo, Utah. This will happen on January, 19th, 11:00 – 11:50. This is a great opportunity to discuss some research ideas about human aspects in software engineering and to start a closer collaboration with researchers from BYU.

I will try to develop the presentation incrementally in this blog. Comments are welcome.

Let’s start with the title. My choice at the moment goes like this:

“The orders of ignorance in our research about the influence of human aspects in software engineering”

This is inspired by an article from Phillip G. Armour, published at the COMMUNICATIONS OF THE ACM, October 2000/Vol. 43, No. 10. Armour describes what he calls the five levels of ignorance we face in software development, and I think these levels are quite good at describing our ignorance with respect to a lot of other things, including research. These levels are (extracted from Orders Of Ignorance):

  • 0th Order Ignorance: Lack of Ignorance. I have 0OI when I (probably) know something.
  • 1st Order Ignorance: Lack of Knowledge. I have 1OI when I don’t know something. With 1OI we have the question in a well-factored form.
  • 2nd Order Ignorance: Lack of Awareness. I have 2OI when I don’t know that I don’t know something.
  • 3rd Order Ignorance: Lack of Process. I have 3OI when I don’t know a suitably efficient way to find out I don’t know that I don’t know something.
  • 4th Order Ignorance: Meta-ignorance. I have 4OI when I don’t know about the Five Orders of Ignorance.

It is very likely that our research about human aspects in software engineering has different levels of ignorance (all but the 4OI). Therefore, I think it will make an interesting seminar to talk about:

  • 0th Order Ignorance: some things I think we (probably) know: past results of our empirical studies and literature reviews.
  • 2nd and 3rd Orders Ignorance: how are we conducting our research (methods and processes) so that we can become aware of new things that we still don’t know. i.o.w., how we are trying to decrease our 2rd Order Ignorance by using replications of qualitative case study research to help formulating good research questions (1st Order Ignorance) and/or testing some previously developed questions (0th Order Ignorance)
  • 1st Order Ignorance: some things I know we don’t know: some questions that we want to investigate and hope to do this investigation through collaborative projects.

Fabio Silva.

Best Article Award at ESEM 2011

The article  “An Empirical Study on the Use of Team Building Criteria in Software Projects“, presented by Prof. Fabio Silva at the 5th International Symposium on Empirical Software Engineering and Measurements (ESEM’2011), in Banff, AL, Canada, received the Best Paper Award at the closing ceremony, on Friday, September 23rd, 2011. The article is co-authored by  Fabio Q. B. da Silva, A. César C. França, Tatiana B. Gouveia, Cleviton V. F. Monteiro, Elisa S. F. Cardozo, Marcos Suassuna, members of the HASE Research Group.

The goal of the research  was to identify criteria used in industrial practice to select members of a software project team, and to look for relationships between these criteria and project success. The study was carried out with project managers of over 30 software companies from various cities in Brazil.  The findings show that the consistent use of a set of team building criteria correlated significantly with project success, and the criteria related to human factors present the strongest correlations.

The paper can be found in the ESEM’2011 Proceedings, which should be electronically available soon at IEEE.

Human Aspects in Software Engineering

Welcome to HASE.

We are a research group at the Center of Informatics, at the Federal University of Pernambuco, Brazil, focused on developing empirical studies of the effects of human factors on the industrial practice of software development.

The research group leader is Prof. Fabio Q. B. da Silva, who has been actively involved in industry-university collaborative research in software engineering in the past 20 years. He is one of the founders of C.E.S.A.R., a research institute that has received twice the award of the Most Innovative Research Institute in Brazil.

HASE is the research home of 6 doctoral and 16 master students, and has an extensive track of published work in the last five years.