def plot_conflicting_region_size_by_involved_refactoring_size():
crs_size_by_involved_refs_size = get_data_frame(
'conflicting_region_size_by_involved_refactoring_size')
crs_size_by_involved_refs_size = crs_size_by_involved_refs_size[
crs_size_by_involved_refs_size['refactoring_size'] > 0]
plot_df = crs_size_by_involved_refs_size.groupby([
'conflicting_region_size', 'refactoring_size'
]).size().reset_index().rename(columns={0: 'frequency'})
b, m = np.polynomial.polynomial.polyfit(
crs_size_by_involved_refs_size['conflicting_region_size'],
crs_size_by_involved_refs_size['refactoring_size'], 1)
fig, ax = plt.subplots()
ax.scatter(x=plot_df['conflicting_region_size'],
y=plot_df['refactoring_size'],
s=plot_df['frequency'],
alpha=.75)
ax.set_xlabel("Conflicting Region Size")
ax.set_ylabel("Involved Refactoring Size")
# ax.set_xscale("log")
# ax.set_yscale("log")
X_plot = np.array([ax.get_xlim()[0], ax.get_xlim()[1]])
ax.plot(X_plot, b + X_plot * m, '-')
fig.tight_layout()
# plt.subplots_adjust(left=.15, right=.97)
plt.savefig('conflicting_region_size_by_involved_refactoring_size.pdf')
plt.show()
def plot_conflicting_region_by_involved_refactoring():
crs_by_involved_refactoring = get_data_frame(
'conflicting_regions_by_count_of_involved_refactoring')
cr_size_with_involved = crs_by_involved_refactoring[
crs_by_involved_refactoring['involved_refactorings'] >
0]['size'].tolist()
cr_size_without_involved = crs_by_involved_refactoring[
crs_by_involved_refactoring['involved_refactorings'] ==
0]['size'].tolist()
fig, ax = plt.subplots()
ax.boxplot([cr_size_with_involved, cr_size_without_involved],
showmeans=True)
ax.set_xticklabels(
['With Involved Refactorings', 'Without Involved Refactorings'])
ax.set_ylabel("Conflicting Region Size")
ax.set_yscale("log")
ax.yaxis.grid(True)
fig.tight_layout()
# plt.subplots_adjust(left=.15, right=.97)
plt.savefig('conflicting_region_by_involved_refactoring.pdf')
plt.show()
def plot_number_of_conflicting_region_histories_by_involved_per_merge_commit():
df = get_data_frame(
'merge_commit_by_crh_and_devs_and_involved_refactorings')
crh_involved_count = df[df['involved_refs'] > 0]['crh'].tolist()
crh_not_involved_count = df[df['involved_refs'] == 0]['crh'].tolist()
fig, ax = plt.subplots()
ax.boxplot([crh_involved_count, crh_not_involved_count], showmeans=True)
ax.set_xticklabels([
'Conflicting Merge Scenarios\nwith Involved Refactorings',
'Conflicting Merge Scenarios\nwithout Involved Refactorings'
])
ax.set_ylabel("Number of Evolutionary Commits")
ax.set_yscale("log")
ax.yaxis.grid(True)
fig.tight_layout()
# plt.subplots_adjust(left=.15, right=.97)
plt.savefig(
'number_of_conflicting_region_histories_by_involved_per_merge_commit.pdf'
)
plt.show()
def plot_refactorings_by_refactoring_type():
plot_df = get_data_frame(
'refactorings_by_refactoring_type_split_by_involved').replace(
'overall', 'Overall').replace('involved', "Involved")
fig, ax = plt.subplots(figsize=(15, 6))
sns.violinplot(x="refactoring_type",
y="percent",
hue="overall_or_involved",
data=plot_df,
palette="muted",
cut=0,
ax=ax)
# ax.yaxis.grid(True)
ax.yaxis.set_major_formatter(ticker.PercentFormatter(xmax=1))
ax.set_xlabel("")
ax.set_ylabel("Percentage of Refactorings with Corresponding Type")
ax.legend().set_title('')
plt.setp(ax.xaxis.get_majorticklabels(),
rotation=-45,
ha="left",
rotation_mode="anchor")
fig.tight_layout()
plt.savefig('refactorings_by_refactoring_type.pdf')
plt.show()
def plot_conflicting_merge_commit_by_merge_author_involvement_in_conflict():
mg_by_author = get_data_frame(
'conflicting_merge_commit_by_merge_author_involvement_in_conflict')
mg_by_author['percent_same_author'] = mg_by_author[
'crh_merge_author'] / mg_by_author['total_crh']
mg_by_author['percent_commits_with_ref'] = mg_by_author[
'crh_involved_ref'] / mg_by_author['total_crh']
percent_commits_with_ref_involved_author = mg_by_author[(
mg_by_author.percent_same_author >
0)]['percent_commits_with_ref'].tolist()
percent_commits_with_ref_noninvolved_author = mg_by_author[(
mg_by_author.percent_same_author == 0
)]['percent_commits_with_ref'].tolist()
mg_involved_author_by_author_ref = mg_by_author[
(mg_by_author.percent_same_author > 0)
& (mg_by_author.crh_merge_author_involved_ref > 0
)]['percent_same_author'].tolist()
mg_involved_author_by_author_no_ref = mg_by_author[
(mg_by_author.percent_same_author > 0)
& (mg_by_author.crh_merge_author_involved_ref == 0
)]['percent_same_author'].tolist()
# cr_size_with_involved = np.random.choice(cr_size_with_involved, 10000)
# cr_size_without_involved = np.random.choice(cr_size_without_involved, 10000)
fig, ax = plt.subplots()
# axs[0].boxplot([percent_commits_with_ref_involved_author, percent_commits_with_ref_noninvolved_author], showmeans=True)
ax.boxplot([
mg_involved_author_by_author_ref, mg_involved_author_by_author_no_ref
],
showmeans=True)
# axs[0].set_xticklabels(['Involved Merger', 'Non-involved Merger'])
ax.set_xticklabels(
['With Involved Refactorings', 'Without Involved Refactorings'])
# axs[0].set_xlabel('All Merge Commits')
# ax.set_xlabel('Merge Commits with Involved Merger')
# axs[0].set_ylabel("Percentage of Evolutionary Commits with Involved Refactoring")
ax.set_ylabel("Percentage of Evolutionary Commits by the Merger ")
# ax.set_yscale("log")
# axs[0].yaxis.grid(True)
ax.yaxis.grid(True)
fig.tight_layout()
# plt.subplots_adjust(left=.15, right=.97)
plt.savefig(
'conflicting_merge_commit_by_merge_author_involvement_in_conflict.pdf')
plt.show()
def plot_conflicting_regions_by_involved_refactorings_per_merge_commit():
plot_df = get_data_frame(
'conflicting_regions_by_involved_refactorings_per_merge_commit')
plot_df = plot_df.groupby([
'cr_count', 'involved_cr_count'
]).size().reset_index().rename(columns={0: 'frequency'})
fig, ax = plt.subplots(figsize=(6, 4.7))
size_scale = lambda x: x / 10 + 1
plot_df['involved_cr_count'] = plot_df['involved_cr_count'].replace(0, .5)
# sns.scatterplot(x="cr_count", y="involved_cr_count", size="frequency", data=plot_df, ax=ax, sizes=(10, 1000))
ax.scatter(x=plot_df['cr_count'],
y=plot_df['involved_cr_count'],
s=size_scale(plot_df['frequency']),
alpha=.8)
# Identity line
x_plot = np.array([10**x for x in range(4)])
ax.plot(x_plot, x_plot, '-', c='k', alpha=.3)
ax.set_xlabel("Conflicting Regions")
ax.set_ylabel("Conflicting Regions with Involved Refactorings")
# ax.yaxis.set_label_coords(-.1,5)
ax.set_xscale("log")
ax.set_yscale("log")
ax.set_yticks([.5] + [10**x for x in range(0, 5)])
ax.set_yticklabels([0] + [10**x for x in range(0, 5)])
ax.grid(True)
legend_markers = [
plt.scatter(x=[], y=[], s=size_scale(1), c='grey', alpha=.8),
plt.scatter(x=[], y=[], s=size_scale(1000), c='grey', alpha=.8),
plt.scatter(x=[], y=[], s=size_scale(10000), c='grey', alpha=.8)
]
labels = [
'1 Merge Scenario', '1,000 Merge Scenarios', '10,000 Merge Scenarios'
]
ax.legend(handles=legend_markers,
labels=labels,
frameon=True,
borderpad=1.2,
labelspacing=1.5)
fig.tight_layout()
# plt.subplots_adjust(left=.15, right=.97)
plt.savefig(
'conflicting_regions_by_involved_refactorings_per_merge_commit.pdf')
plt.show()