o Arcurve is Calgary's largest independent software services company o They specialize in custom software development, integration and implementation and ...
Understanding Task Interruptions in Service Oriented Software Development (SOSD) Projects An Exploratory Study Zahra Shakeri, Guenther Ruhe, Mike Bauer
Task Interruptions
o Information workers often interleave multiple projects and tasks. o Developers work only 30% of their time alone and spend another 70% on collaboration and interaction with each other. o A study by O C ́ onaill and Frohilch on resumption timing shows that only 55% of the interrupted tasks were resumed on the same day. o Task Switching and interruptions make an individual less productive by reducing the amount of short-term memory dedicated to a single task.
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Task Interruptions Task interruptions are a type of task switching or sequential multitasking Planned Duration for task A
Actual Duration of task A Extra task duration (?!)
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Fragments Primary Task
Primary Task
Terminologies and Concepts B
A The length of interruption i
Start date
I1
A1
I2
A2
I3
A3
I4 A4
Finish date
A5
Time
1. Total interruption length of task A: 4
Fragments Primary Task
Primary Task
Terminologies and Concepts B
A : The duration of fragment Aj for task A Start date
I1
A1
I2
A2
I3
A3
I4 A4
Finish date
A5
2. Task Duration: 5
Fragments Primary Task
Primary Task
Terminologies and Concepts B
: The planned duration for task A A : The margin of the estimation error for task A (varies by project type) Start date
I1
A1
I2
A2
I3
A3
I4 A4
Finish date
A5
3. Extra Duration: 6
Research Questions? o RQ1: What are the most frequent causes of interruptions in SOSD projects? o RQ2: Does the interruption length and its impact on the extent of the extra duration vary by the type of the software development tasks?
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Research Methodology
Unstructured Interview (with our industry partner)
Conceptual framework (variables, main domain concepts) - Goals and objectives - Research Questions
Data Collection
9 tables (7,770 tasks) out of 123 tables (~123,000 tasks) 5 projects (21 months to 63 months)
Data Preparation
Data Analysis - Results of RQ1, RQ2, RQ3 - Recommendations for Arcurve
• Statistical analysis • Time series analysis Prepared data set which includes tasks types and interruptions time slots
• • •
NLP Time series analysis Frequency analysis
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Industries: Oil and gas, Mining, Agriculture, Medical imaging, Asset management, Health services, Supply-chain logistics, and Education
o Arcurve is Calgary’s largest independent software services company
o They specialize in custom software development, integration and implementation and managed application services, supporting the full software lifecycle o Arcurve’s clients range from private-sector start-ups to global multinationals and public sector entities.
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SOSD Process Model
Maintenance
Deployment
The emphasis on each phase changes based on the type of each product/service. 10
Data Collection o we collected and organized datasets of five real SOSD projects from Arcurve’s task-based bug tracking and project management tool (i.e. Fogbugz). o We analyzed 123 tables of our dataset and selected 9 tables that kept information about project’s tasks, employees, hierarchy of tasks, projects, change logs and comments, time and effort estimations, time logs for performing each task, areas of tasks, and communication logs between practitioners Unstructured Interview (with our industry partner)
Conceptual framework (variables, main domain concepts) - Goals and objectives - Research Questions
Data Collection
9 tables (7,770 tasks) out of 123 tables (~123,000 tasks) 5 projects (21 months to 63 months)
Data Preparation
Data Analysis - Results of RQ1, RQ2, RQ3 - Recommendations for Arcurve
• Statistical analysis • Time series analysis Prepared data set which includes tasks types and interruptions time slots
• • •
NLP Time series analysis Frequency analysis
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Data Collection
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Data Preparation 1. Identifying Interrupted Tasks Inclusion:
tasks that have been assigned to the same employee before and after the interruption
Exclusion:
o Interruptions during the regular lunch time (11:00 am- 1:00 pm) of the company. o The last task of each day. o Meetings, site visits. o Tasks that have been completed before the interruption Unstructured Interview (with our industry partner)
Conceptual framework (variables, main domain concepts) - Goals and objectives - Research Questions
Data Collection
9 tables (7,770 tasks) out of 123 tables (~123,000 tasks) 5 projects (21 months to 63 months)
Data Preparation
Data Analysis - Results of RQ1, RQ2, RQ3 - Recommendations for Arcurve
• Statistical analysis • Time series analysis Prepared data set which includes tasks types and interruptions time slots
• • •
NLP Time series analysis Frequency analysis
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Data Preparation 1. Identifying Tasks’ Types Text Mining, Natural Language Processing
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Data Analysis and Results RQ1. Most Frequent Causes of Interruption in SOSD Projects o o o o o
Fixing an issue Adding a new feature Addressing changes Lack of information or uncertainty Inconsistency between stakeholders Unstructured Interview (with our industry partner)
Conceptual framework (variables, main domain concepts) - Goals and objectives - Research Questions
Data Collection
9 tables (7,770 tasks) out of 123 tables (~123,000 tasks) 5 projects (21 months to 63 months)
Data Preparation
Data Analysis - Results of RQ1, RQ2, RQ3 - Recommendations for Arcurve
• Statistical analysis • Time series analysis Prepared data set which includes tasks types and interruptions time slots
• • •
NLP Time series analysis Frequency analysis
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Data Analysis and Results RQ1. Most Frequent Causes of Interruption in SOSD Projects
o The results of manual analysis of 886 tasks
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Data Analysis and Results RQ1. Most Frequent Causes of Interruption in SOSD Projects Architecture) RE Development) Test Deployment UIBDesign 70 PM Technical)Tasks 60
10.5 17.3 42.6 11.8 2.5 5.1 6.3 3.8 99.9
The percentage of interrupted tasks by Requirements Engineering (RE), Project Management (PM), and Development tasks.
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PM#
RE#
Development#
40 30 20 10 0
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Data Analysis and Results RQ2. Interruption Length and the Extra Duration
o Null Hypothesis H0(a): the length of interruption does not vary significantly by the type of the software development tasks. o Null Hypothesis H0(b): the extent of extra duration resulted from interruptions does not vary significantly by the type of the software development tasks.
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Data Analysis and Results RQ2. Interruption Length and the Extra Duration o Null Hypothesis H0(a): the length of interruption does not vary significantly by the type of the software development tasks.
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e s ent ent ysi tectur l m m a y p hi An plo evelo De Arc D
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Data Analysis and Results RQ2. Interruption Length and the Extra Duration o Null Hypothesis H0(b): the extent of extra duration resulted from interruptions does not vary significantly by the type of the software development tasks. 500 Extra duration (minute)
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0 e s ent ent ysi tectur l m m a y p hi An plo evelo De Arc D
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Data Analysis and Results RQ2. Interruption Length and the Extra Duration Following the results of our kruskal-Wallis post-hoc tests, the extra duration (DE) resulted from task interruptions in analysis tasks is significantly less than architectural, development, testing, and deployment tasks 500 Extra duration (minute)
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0 e s ent ent ysi tectur l m m a y p hi An plo evelo De Arc D
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Data Analysis and Results RQ2. Interruption Length and the Extra Duration Following the results of our kruskal-Wallis post-hoc tests, the extra duration (DE) resulted from task interruptions in analysis tasks is significantly less than architectural, development, testing, and deployment tasks 500
o One of the promised benefits of service orientation is their high flexibility to implement a change in the system … o Technological changes are easier to implement in SOSD projects, which can mitigate the costs of interruptions for analysis tasks (Bano et al., 2014)
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t Tes
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Data Analysis and Results RQ2. Interruption Length and the Extra Duration Our results show that the “interruption length” of a specific task, regardless of the type of this task, does not influence its duration significantly. Analysis
Architecture
Deployment
Development
PM
Test
Extra duration (minute)
400 200 0 −200
400 200 0 −200 10
20
30
10
20
30
10
20
30
Interruption length (day)
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Next Steps … o Replicating the study in other contexts o Considering various factors that impact the disruptiveness of task interruptions (Accepted to RE’17) o Providing a narrative visual solution for reducing the cognitive cost of interruptions (Accepted to RE’17)
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References 1.
Zahra Shakeri Hossein Abad, Guenther Ruhe, and Mike Bauer, Task Interruptions in Requirements Engineering: Reality versus Perceptions. In proceeding of the 25th IEEE International Conference on Requirements Engineering (RE’17).
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Zahra Shakeri Hossein Abad, Alex Shymka, Jenny Le, Noor Hammad, and Guenther Ruhe, A Visual Path From Interrupting to Resuming An RE Task. In proceeding of the 25th IEEE International Conference on Requirements Engineering (RE’17).
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Alexey Tregubov, Barry Boehm, Natalia Rodchenko, and Jo Ann Lane, Impact of task switching and work interruptions on software development processes, International Conference on Software and Systems Process (ICSSP’17).
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Brid O'Conaill, and David Frohlich. "Timespace in the workplace: Dealing with interruptions." Conference companion on Human factors in computing systems. ACM, 1995.
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Cora M. Dzubak, Multitasking: The good, the bad, and the unknown. The Journal of the Association for the Tutoring Profession 1.2 (2008): 1-12.
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Muneera Bano et al., What makes service oriented requirements engineering challenging? A qualitative study. IET software 8.4 (2013): 154-160.
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Understanding Task Interruptions in Service Oriented Software Development (SOSD) Projects An Exploratory Study Zahra Shakeri, Guenther Ruhe, Mike Bauer
