Lecture6 activity diagrams

Apr 13, 20180 likes1,788 views

Activity diagrams can model the dynamic aspects of a system by showing the flow of control from one activity to the next. They are essentially flowcharts that can model business workflows and operations. Activity diagrams contain activity states, action states, transitions, objects, branches, forks, joins, and swimlanes. Action states are atomic while activity states can be decomposed into further detail. Transitions show the flow of control between states. Branches specify alternate paths. Forks allow concurrent flows while joins synchronize them. Swimlanes group activities by actor or thread.

Activity Diagrams
 To model the dynamic aspects of a
system
 It is essentially a flowchart
Showing flow of control from activity to activity
 Purpose
Model business workflows
Model operations

Activity Diagrams
Activity diagrams commonly contain
Activity states and action states
Transitions
Objects

Action States and Activity States
 Action states are atomic and cannot be decomposed
Work of the action state is not interrupted
 Activity states can be further decomposed
Their activity being represented by other activity
diagrams
They may be interrupted

Transitions
When the action or activity of a state
completes, flow of control passes
immediately to the next action or activity
state
A flow of control has to start and end
someplace
initial state -- a solid ball
stop state -- a solid ball inside a circle

Branching
A branch specifies alternate paths taken
based on some Boolean expression
A branch may have one incoming
transition and two or more outgoing ones

Forking and Joining
Use a synchronization bar to specify the
forking and joining of parallel flows of
control
A synchronization bar is rendered as a
thick horizontal or vertical line

Fork
 A fork may have one incoming transitions and two or more
outgoing transitions
 each transition represents an independent flow of control
 conceptually, the activities of each of outgoing transitions are
concurrent
 either truly concurrent (multiple nodes)
 or sequential yet interrupted (one node)

Join
 A join may have two or more incoming transitions
and one outgoing transition
above the join, the activities associated with each of
these paths continues in parallel
at the join, the concurrent flows synchronize
each waits until all incoming flows have reached the
join, at which point one flow of control continues on
below the join

Swimlanes
 Activity diagrams tell you what happens, but they do not tell you who
does what. In programming, this means that the diagram does not
convey which class is responsible for each activity.
 A swimlane is a way to group activities performed by the same actor
on an activity diagram or to group activities in a single thread.
 each group representing the business organization responsible
for those activities
 each group is called a swimlane
 Each swimlane is divided from its neighbor by a vertical solid line

Swimlanes
 Each swimlane has a name unique within its diagram
 Each swimlane may represent some real-world entity
 Each swimlane may be implemented by one or more
classes
 Every activity belongs to exactly one swimlane, but
transitions may cross lanes

This document describes the key elements of activity diagrams including activities, transitions, guard conditions, decisions, concurrency, and notations. Activities represent steps in a process, transitions connect activities, and guard conditions restrict transitions. Decisions can involve simple true/false tests or choices between options. Activity diagrams can also model the synchronization of concurrent activities and splitting of process flow.

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Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)Andre Hora

Exceptions allow developers to handle error cases expected to occur infrequently. Ideally, good test suites should test both normal and exceptional behaviors to catch more bugs and avoid regressions. While current research analyzes exceptions that propagate to tests, it does not explore other exceptions that do not reach the tests. In this paper, we provide an empirical study to explore how frequently exceptional behaviors are tested in real-world systems. We consider both exceptions that propagate to tests and the ones that do not reach the tests. For this purpose, we run an instrumented version of test suites, monitor their execution, and collect information about the exceptions raised at runtime. We analyze the test suites of 25 Python systems, covering 5,372 executed methods, 17.9M calls, and 1.4M raised exceptions. We find that 21.4% of the executed methods do raise exceptions at runtime. In methods that raise exceptions, on the median, 1 in 10 calls exercise exceptional behaviors. Close to 80% of the methods that raise exceptions do so infrequently, but about 20% raise exceptions more frequently. Finally, we provide implications for researchers and practitioners. We suggest developing novel tools to support exercising exceptional behaviors and refactoring expensive try/except blocks. We also call attention to the fact that exception-raising behaviors are not necessarily “abnormal” or rare.

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Software testing plays a crucial role in the contribution process of open-source projects. For example, contributions introducing new features are expected to include tests, and contributions with tests are more likely to be accepted. Although most real-world projects require contributors to write tests, the specific testing practices communicated to contributors remain unclear. In this paper, we present an empirical study to understand better how software testing is approached in contribution guidelines. We analyze the guidelines of 200 Python and JavaScript open-source software projects. We find that 78% of the projects include some form of test documentation for contributors. Test documentation is located in multiple sources, including CONTRIBUTING files (58%), external documentation (24%), and README files (8%). Furthermore, test documentation commonly explains how to run tests (83.5%), but less often provides guidance on how to write tests (37%). It frequently covers unit tests (71%), but rarely addresses integration (20.5%) and end-to-end tests (15.5%). Other key testing aspects are also less frequently discussed: test coverage (25.5%) and mocking (9.5%). We conclude by discussing implications and future research.

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Explaining GitHub Actions Failures with Large Language Models Challenges, In...ssuserb14185

GitHub Actions (GA) has become the de facto tool that developers use to automate software workflows, seamlessly building, testing, and deploying code. Yet when GA fails, it disrupts development, causing delays and driving up costs. Diagnosing failures becomes especially challenging because error logs are often long, complex and unstructured. Given these difficulties, this study explores the potential of large language models (LLMs) to generate correct, clear, concise, and actionable contextual descriptions (or summaries) for GA failures, focusing on developers’ perceptions of their feasibility and usefulness. Our results show that over 80% of developers rated LLM explanations positively in terms of correctness for simpler/small logs. Overall, our findings suggest that LLMs can feasibly assist developers in understanding common GA errors, thus, potentially reducing manual analysis. However, we also found that improved reasoning abilities are needed to support more complex CI/CD scenarios. For instance, less experienced developers tend to be more positive on the described context, while seasoned developers prefer concise summaries. Overall, our work offers key insights for researchers enhancing LLM reasoning, particularly in adapting explanations to user expertise. https://arxiv.org/abs/2501.16495

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This SlideShare presentation is from our May webinar, “Not So Common Memory Leaks & How to Fix Them?”, where we explored lesser-known memory leak patterns in Java applications. Unlike typical leaks, subtle issues such as thread local misuse, inner class references, uncached collections, and misbehaving frameworks often go undetected and gradually degrade performance. This deck provides in-depth insights into identifying these hidden leaks using advanced heap analysis and profiling techniques, along with real-world case studies and practical solutions. Ideal for developers and performance engineers aiming to deepen their understanding of Java memory management and improve application stability.

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TestMigrationsInPy: A Dataset of Test Migrations from Unittest to Pytest (MSR...Andre Hora

Unittest and pytest are the most popular testing frameworks in Python. Overall, pytest provides some advantages, including simpler assertion, reuse of fixtures, and interoperability. Due to such benefits, multiple projects in the Python ecosystem have migrated from unittest to pytest. To facilitate the migration, pytest can also run unittest tests, thus, the migration can happen gradually over time. However, the migration can be timeconsuming and take a long time to conclude. In this context, projects would benefit from automated solutions to support the migration process. In this paper, we propose TestMigrationsInPy, a dataset of test migrations from unittest to pytest. TestMigrationsInPy contains 923 real-world migrations performed by developers. Future research proposing novel solutions to migrate frameworks in Python can rely on TestMigrationsInPy as a ground truth. Moreover, as TestMigrationsInPy includes information about the migration type (e.g., changes in assertions or fixtures), our dataset enables novel solutions to be verified effectively, for instance, from simpler assertion migrations to more complex fixture migrations. TestMigrationsInPy is publicly available at: https://github.com/altinoalvesjunior/TestMigrationsInPy.

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Tests, especially unit tests, are the developers’ superheroes. They allow us to mess around with our code and keep us safe. We often trust them with the safety of our codebase, but how do we know that we should? How do we know that this trust is well-deserved? Enter mutation testing – by intentionally injecting harmful mutations into our code and seeing if they are caught by the tests, we can evaluate the quality of the safety net they provide. By watching the watchmen, we can make sure our tests really protect us, and we aren’t just green-washing our IDEs to a false sense of security. Talk from SciFiDevCon 2025 https://www.scifidevcon.com/courses/2025-scifidevcon/contents/680efa43ae4f5

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Lecture6 activity diagrams

1. Activity Diagrams

2. Activity Diagrams  To model the dynamic aspects of a system  It is essentially a flowchart Showing flow of control from activity to activity  Purpose Model business workflows Model operations

3. Activity Diagrams Activity diagrams commonly contain Activity states and action states Transitions Objects

4. Action States and Activity States  Action states are atomic and cannot be decomposed Work of the action state is not interrupted  Activity states can be further decomposed Their activity being represented by other activity diagrams They may be interrupted

5. Transitions When the action or activity of a state completes, flow of control passes immediately to the next action or activity state A flow of control has to start and end someplace initial state -- a solid ball stop state -- a solid ball inside a circle

6. Transitions

7. Branching A branch specifies alternate paths taken based on some Boolean expression A branch may have one incoming transition and two or more outgoing ones

8. Branching

9. Example of Activity Diagram

10. Forking and Joining Use a synchronization bar to specify the forking and joining of parallel flows of control A synchronization bar is rendered as a thick horizontal or vertical line

11. Fork  A fork may have one incoming transitions and two or more outgoing transitions  each transition represents an independent flow of control  conceptually, the activities of each of outgoing transitions are concurrent  either truly concurrent (multiple nodes)  or sequential yet interrupted (one node)

12. Join  A join may have two or more incoming transitions and one outgoing transition above the join, the activities associated with each of these paths continues in parallel at the join, the concurrent flows synchronize each waits until all incoming flows have reached the join, at which point one flow of control continues on below the join

13. Example of an Activity Diagram

14. Swimlanes  Activity diagrams tell you what happens, but they do not tell you who does what. In programming, this means that the diagram does not convey which class is responsible for each activity.  A swimlane is a way to group activities performed by the same actor on an activity diagram or to group activities in a single thread.  each group representing the business organization responsible for those activities  each group is called a swimlane  Each swimlane is divided from its neighbor by a vertical solid line

15. Swimlanes  Each swimlane has a name unique within its diagram  Each swimlane may represent some real-world entity  Each swimlane may be implemented by one or more classes  Every activity belongs to exactly one swimlane, but transitions may cross lanes

16. Example of Activity Diagram

17. Example of Activity Diagram

18. Thanks

Lecture6 activity diagrams

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