Merge pull request #31 from galilasmb/master

Fixing text

semantic-conflicts-static-analysis.html

@@ -393,23 +393,11 @@ <h1 class="title toc-ignore"><strong>A Lightweight Technique for Detecting Seman
           <h2>Abstract</h2>
 
           <p>Version control system tools, like Git, empower developers to work
-on their development tasks independently. These tools also facil-
-itate the integration of changes through merging operations and
-report errors in case of syntactic conflicts. However, when developers integrate their changes, they might encounter other types
-of conflicts, such as static and dynamic semantic conflicts. In this
-paper, we specifically focus on dynamic semantic conflicts, which
-occur when merging results in undesired interference—causing
-unexpected program behavior at runtime. To address this issue, we
-explore the use of static analysis to detect an approximation for
-interference when merging contributions from two developers. We
-evaluate our technique using a dataset of 99 experimental units
-extracted from merge scenarios. The results provide evidence that
-our approach outperforms previous methods that rely on dynamic
-analysis for detecting semantic conflicts, in terms of F1 score and
-recall (but with much worse precision). Our technique remains
-comparable to precision levels observed in other studies that also
-leverage static analysis or use theorem proving techniques to de-
-tect semantic conflict, albeit with significantly improved overall
+on their development tasks independently. These tools also facilitate the integration of changes through merging operations and report errors in case of syntactic conflicts. However, when developers integrate their changes, they might encounter other types of conflicts, such as static and dynamic semantic conflicts. In this paper, we specifically focus on dynamic semantic conflicts, which
+occur when merging results in undesired interference—causing unexpected program behavior at runtime. To address this issue, we explore the use of static analysis to detect an approximation for
+interference when merging contributions from two developers. We evaluate our technique using a dataset of 99 experimental units extracted from merge scenarios. The results provide evidence that
+our approach outperforms previous methods that rely on dynamic analysis for detecting semantic conflicts, in terms of F1 score and recall (but with much worse precision). Our technique remains
+comparable to precision levels observed in other studies that also leverage static analysis or use theorem proving techniques to detect semantic conflict, albeit with significantly improved overall
 performance.
           </p>