https://sdq.kastel.kit.edu/api.php?action=feedcontributions&user=Dr6631&feedformat=atomSDQ-Institutsseminar - Benutzerbeiträge [de]2024-03-29T05:41:19ZBenutzerbeiträgeMediaWiki 1.39.6https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Preventing_Refactoring_Attacks_on_Software_Plagiarism_Detection_through_Graph-Based_Structural_Normalization&diff=2944Preventing Refactoring Attacks on Software Plagiarism Detection through Graph-Based Structural Normalization2024-03-15T11:19:19Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Vortrag |vortragender=Robin Maisch |email=ujepl@student.kit.edu |vortragstyp=Masterarbeit |betreuer=Timur Sağlam |termin=Institutsseminar/2024-06-07-Zusatztermin |vortragsmodus=in Präsenz |kurzfassung=TBD }}“</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Robin Maisch<br />
|email=ujepl@student.kit.edu<br />
|vortragstyp=Masterarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2024-06-07-Zusatztermin<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=TBD<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Intelligent_Match_Merging_to_Prevent_Obfuscation_Attacks_on_Software_Plagiarism_Detectors&diff=2796Intelligent Match Merging to Prevent Obfuscation Attacks on Software Plagiarism Detectors2023-12-04T08:41:19Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Nils Niehues<br />
|email=uuqjz@student.kit.edu<br />
|vortragstyp=Masterarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2023-12-08<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=The increasing number of computer science students has prompted educators to rely on state-of-the-art source code plagiarism detection tools to deter the submission of plagiarized coding assignments. While these token-based plagiarism detectors are inherently resilient against simple obfuscation attempts, recent research has shown that obfuscation tools empower students to easily modify their submissions, thus evading detection. These tools automatically use dead code insertion and statement reordering to avoid discovery. The emergence of ChatGPT has further raised concerns about its obfuscation capabilities and the need for effective mitigation strategies.<br />
Existing defence mechanisms against obfuscation attempts are often limited by their specificity to certain attacks or dependence on programming languages, requiring tedious and error-prone reimplementation. In response to this challenge, this thesis introduces a novel defence mechanism against automatic obfuscation attacks called match merging. It leverages the fact that obfuscation attacks change the token sequence to split up matches between two submissions so that the plagiarism detector discards the broken matches. Match merging reverts the effects of these attacks by intelligently merging neighboring matches based on a heuristic designed to minimize false positives.<br />
Our method’s resilience against classic obfuscation attacks is demonstrated through evaluations on diverse real-world datasets, including undergrad assignments and competitive coding challenges, across six different attack scenarios. Moreover, it significantly improves detection performance against AI-based obfuscation. What sets our method apart is its language- and attack-independence while its minimal runtime overhead makes it seamlessly compatible with other defence mechanisms.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Intelligent_Match_Merging_to_Prevent_Obfuscation_Attacks_on_Software_Plagiarism_Detectors&diff=2794Intelligent Match Merging to Prevent Obfuscation Attacks on Software Plagiarism Detectors2023-11-30T15:08:00Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Nils Niehues<br />
|email=uuqjz@student.kit.edu<br />
|vortragstyp=Masterarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2023-12-08<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=The increasing number of computer science students has prompted educators to rely on state-of-the-art source code plagiarism detection tools to deter the submission of plagiarized coding assignments. While these token-based plagiarism detectors are inherently resilient against simple obfuscation attempts, recent research has shown that obfuscation tools empower students to easily modify their submissions, thus evading detection. These tools automatically use dead code insertion and statement reordering to avoid discovery. The emergence of ChatGPT has further raised concerns about its obfuscation capabilities and the need for effective mitigation strategies.<br />
Existing defence mechanisms against obfuscation attempts are often limited by their specificity to certain attacks or dependence on programming languages, requiring tedious and error-prone reimplementation. In response to this challenge, this thesis introduces a novel defence mechanism against automatic obfuscation attacks called match merging. It leverages the fact that obfuscation attacks change the token sequence to split up matches between two submissions so that the plagiarism detector discards the broken matches. Match merging reverts the effects of these attacks by intelligently merging neighboring matches based on a heuristic designed to minimize false positives.<br />
Our method’s resilience against classic obfuscation attacks is demonstrated through evalua- tions on diverse real-world datasets, including undergrad assignments and competitive coding challenges, across six different attack scenarios. Moreover, it significantly improves detection performance against AI-based obfuscation. What sets our method apart is its language- and attack-independence while its minimal runtime overhead makes it seamlessly compatible with other defence mechanisms.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Software_Plagiarism_Detection_on_Intermediate_Representation&diff=2759Software Plagiarism Detection on Intermediate Representation2023-10-30T07:47:04Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Niklas Heneka<br />
|email=niklas.heneka@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2023-11-17-2<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=Source code plagiarism is a widespread problem in computer science education. To counteract this, software plagiarism detectors can help identify plagiarized code. Most state-of-the-art plagiarism detectors are token-based. It is common to design and implement a new dedicated language module to support a new programming language. This process can be time-consuming, furthermore, it is unclear whether it is even necessary. In this thesis, we evaluate the necessity of dedicated language modules for Java and C/C++ and derive conclusions for designing new ones. To achieve this, we create a language module for the intermediate representation of LLVM. For the evaluation, we compare it to two existing dedicated language modules in JPlag. While our results show that dedicated language modules are better for plagiarism detection, language modules for intermediate representations show better resilience to obfuscation attacks.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Software_Plagiarism_Detection_on_Intermediate_Representation&diff=2754Software Plagiarism Detection on Intermediate Representation2023-10-16T06:43:09Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Niklas Heneka<br />
|email=niklas.heneka@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2023-11-17-2<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=TBD<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Institutsseminar/2023-12-08&diff=2749Institutsseminar/2023-12-082023-10-04T12:34:59Z<p>Dr6631: </p>
<hr />
<div>{{Termin<br />
|datum=2023-12-08T11:30:00.000Z<br />
|raum=Raum 348 (Gebäude 50.34)<br />
|online=https://sdq.kastel.kit.edu/wiki/SDQ-Institutsseminar/Microsoft_Teams<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Intelligent_Match_Merging_to_Prevent_Obfuscation_Attacks_on_Software_Plagiarism_Detectors&diff=2748Intelligent Match Merging to Prevent Obfuscation Attacks on Software Plagiarism Detectors2023-10-04T12:33:54Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Vortrag |vortragender=Nils Niehues |email=uuqjz@student.kit.edu |vortragstyp=Masterarbeit |betreuer=Timur Sağlam |termin=Institutsseminar/2023-12-08 |vortragsmodus=in Präsenz |kurzfassung=TBD }}“</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Nils Niehues<br />
|email=uuqjz@student.kit.edu<br />
|vortragstyp=Masterarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2023-12-08<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=TBD<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Institutsseminar/2023-12-08&diff=2747Institutsseminar/2023-12-082023-10-04T12:32:23Z<p>Dr6631: </p>
<hr />
<div>{{Termin<br />
|datum=2023-12-08T11:30:00.000<br />
|raum=Raum 348 (Gebäude 50.34)<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Institutsseminar/2023-12-08&diff=2746Institutsseminar/2023-12-082023-10-04T12:32:01Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Termin |datum=2023-12-08T11:30:00.000Z |raum=Raum 348 (Gebäude 50.34) }}“</p>
<hr />
<div>{{Termin<br />
|datum=2023-12-08T11:30:00.000Z<br />
|raum=Raum 348 (Gebäude 50.34)<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Software_Plagiarism_Detection_on_Intermediate_Representation&diff=2745Software Plagiarism Detection on Intermediate Representation2023-10-04T08:00:57Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Vortrag |vortragender=Niklas Heneka |email=niklas.heneka@student.kit.edu |vortragstyp=Bachelorarbeit |betreuer=Timur Sağlam |termin=Institutsseminar/2023-11-17 |vortragsmodus=in Präsenz |kurzfassung=TBD }}“</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Niklas Heneka<br />
|email=niklas.heneka@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2023-11-17<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=TBD<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Preventing_Automatic_Code_Plagiarism_Generation_Through_Token_String_Normalization&diff=2528Preventing Automatic Code Plagiarism Generation Through Token String Normalization2023-04-28T10:36:43Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Moritz Brödel<br />
|email=moritz.broedel@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2023-05-05 Zusatztermin<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=Code plagiarism is a significant problem in computer science education. Token-based plagiarism detectors, which represent the state-of-the-art in code plagiarism detection, excel at identifying manually plagiarized submissions. Unfortunately, they are vulnerable to automatic plagiarism generation, particularly when statements are inserted or reordered. Therefore, this thesis introduces token string normalization, which makes the results of token-based plagiarism detectors invariant to statement insertion and reordering. It inher- its token-based plagiarism detectors’ high language independence and utilizes a program graph. We integrate token string normalization into the state-of-the-art token-based plagiarism detector JPlag. We show that this prevents automatic plagiarism generation using statement insertion and reordering. Additionally, we confirm that JPlag’s existing capabilities are retained.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Using_Token_String_Normalization_to_Prevent_Code_Plagiarism_Obfuscation&diff=2527Using Token String Normalization to Prevent Code Plagiarism Obfuscation2023-04-28T10:35:35Z<p>Dr6631: Dr6631 verschob die Seite Using Token String Normalization to Prevent Code Plagiarism Obfuscation nach Preventing Automatic Code Plagiarism Generation Through Token String Normalization</p>
<hr />
<div>#WEITERLEITUNG [[Preventing Automatic Code Plagiarism Generation Through Token String Normalization]]</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Preventing_Automatic_Code_Plagiarism_Generation_Through_Token_String_Normalization&diff=2526Preventing Automatic Code Plagiarism Generation Through Token String Normalization2023-04-28T10:35:35Z<p>Dr6631: Dr6631 verschob die Seite Using Token String Normalization to Prevent Code Plagiarism Obfuscation nach Preventing Automatic Code Plagiarism Generation Through Token String Normalization</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Moritz Brödel<br />
|email=moritz.broedel@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2023-05-05 Zusatztermin<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=Kurzfassung<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Evidence-based_Token_Abstraction_for_Software_Plagiarism_Detection&diff=2499Evidence-based Token Abstraction for Software Plagiarism Detection2023-04-17T11:48:49Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Hannes Greule<br />
|email=hannes.greule@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2023-04-28<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=Programming assignments for students are target of plagiarism. Especially for graded<br />
assignments, instructors want to detect plagiarism among the students. For larger courses,<br />
however, manual inspection of all submissions is a resourceful task. For this purpose, there<br />
are numerous tools that can help detect plagiarism in submissions. Many well-known<br />
plagiarism detection tools are token-based detectors. In an abstraction step, they map<br />
source code to a list of tokens, and such lists are then compared with each other.<br />
While there is much research in the area of comparison algorithms, the mapping is<br />
often only considered superficially. In this work, we conduct two experiments that address<br />
the issue of token abstraction. For that, we design different token abstractions and explain<br />
their differences. We then evaluate these abstractions using multiple datasets. We show<br />
that different abstractions have pros and cons, and that a higher abstraction level does not<br />
necessarily perform better. These findings are useful when adding support for new programming<br />
languages and for improving existing plagiarism detection tools. Furthermore,<br />
the results can be helpful to choose abstractions tailored to specific requirements.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Token-Based_Plagiarism_Detection_for_Statecharts&diff=2498Token-Based Plagiarism Detection for Statecharts2023-04-17T11:48:04Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Jonas Strittmatter<br />
|email=uzxhf@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2023-04-28<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=In the field of software engineering, existing plagiarism detection systems have primarily<br />
focused on detecting cases of plagiarism in code. However, other artefacts such as models<br />
also play a crucial role in the development process. Statecharts, in particular, are used to<br />
model the behavior of a system. This thesis investigates the applicability and challenges<br />
of applying token-based plagiarism detection systems to statecharts. We extend the<br />
plagiarism detector JPlag to support detecting cases of plagiarism in statecharts. Our<br />
approach is evaluated using a dataset of student assignments from a modeling course,<br />
where we generate plagiarized statecharts by adopting common obfuscation attacks. We<br />
study the effects of the token-extraction strategy, sorting techniques and the minimum<br />
token match parameter. The results suggest that an approach tailored to the specific kind<br />
of model, such as statecharts, works better than a generic solution for models.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Preventing_Automatic_Code_Plagiarism_Generation_Through_Token_String_Normalization&diff=2453Preventing Automatic Code Plagiarism Generation Through Token String Normalization2023-03-08T15:53:58Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Vortrag |vortragender=Moritz Brödel |email=moritz.broedel@student.kit.edu |vortragstyp=Bachelorarbeit |betreuer=Timur Sağlam |termin=Institutsseminar/2023-…“</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Moritz Brödel<br />
|email=moritz.broedel@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2023-05-05<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=Kurzfassung<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Evidence-based_Token_Abstraction_for_Software_Plagiarism_Detection&diff=2448Evidence-based Token Abstraction for Software Plagiarism Detection2023-03-03T07:56:46Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Vortrag |vortragender=Hannes Greule |email=hannes.greule@student.kit.edu |vortragstyp=Bachelorarbeit |betreuer=Timur Sağlam |termin=Institutsseminar/2023-04…“</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Hannes Greule<br />
|email=hannes.greule@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2023-04-28<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=Kurzfassung<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Token-Based_Plagiarism_Detection_for_Statecharts&diff=2447Token-Based Plagiarism Detection for Statecharts2023-03-03T07:55:24Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Vortrag |vortragender=Jonas Strittmatter |email=uzxhf@student.kit.edu |vortragstyp=Bachelorarbeit |betreuer=Timur Sağlam |termin=Institutsseminar/2023-04-28…“</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Jonas Strittmatter<br />
|email=uzxhf@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2023-04-28<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=Kurzfassung<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Preventing_Code_Insertion_Attacks_on_Token-Based_Software_Plagiarism_Detectors&diff=2322Preventing Code Insertion Attacks on Token-Based Software Plagiarism Detectors2022-09-30T09:31:53Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Pascal Krieg<br />
|email=pascal.krieg@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2022-10-14<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=Some students tasked with mandatory programming assignments lack the time or dedication to solve the assignment themselves. Instead, they plagiarize a peer’s solution by slightly modifying the code. However, there exist numerous tools that assist in detecting these kinds of plagiarism. These tools can be used by instructors to identify plagiarized programs. The most used type of plagiarism detection tools is token-based plagiarism detectors. They are resilient against many types of obfuscation attacks, such as renaming variables or whitespace modifications. However, they are susceptible to inserting lines of code that do not affect the program flow or result.<br />
The current working assumption was that the successful obfuscation of plagiarism takes more effort and skill than solving the assignment itself. This assumption was broken by automated plagiarism generators, which exploit this weakness. This work aims to develop mechanisms against code insertions that can be directly integrated into existing token-based plagiarism detectors. For this, we first develop mechanisms to negate the negative effect of many types of code insertion. Then we implement these mechanisms prototypically into a state-of-the-art plagiarism detector. We evaluate our implementation by running it on a dataset consisting of real student submissions and automatically generated plagiarism. We show that with our mechanisms, the similarity rating of automatically generated plagiarism increases drastically. Consequently, the plagiarism generator we use fails to create usable plagiarisms.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Institutsseminar/2022-10-14&diff=2321Institutsseminar/2022-10-142022-09-30T09:31:07Z<p>Dr6631: </p>
<hr />
<div>{{Termin<br />
|datum=2022-10-14T11:30:00.000Z<br />
|raum=Raum 348 (Gebäude 50.34)<br />
|online=https://sdq.kastel.kit.edu/wiki/SDQ-Oberseminar/Microsoft_Teams<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Preventing_Code_Insertion_Attacks_on_Token-Based_Software_Plagiarism_Detectors&diff=2320Preventing Code Insertion Attacks on Token-Based Software Plagiarism Detectors2022-09-30T09:28:49Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Pascal Tobias Krieg<br />
|email=pascal.krieg@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2022-10-14<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=Some students tasked with mandatory programming assignments lack the time or dedication to solve the assignment themselves. Instead, they plagiarize a peer’s solution by slightly modifying the code. However, there exist numerous tools that assist in detecting these kinds of plagiarism. These tools can be used by instructors to identify plagiarized programs. The most used type of plagiarism detection tools is token-based plagiarism detectors. They are resilient against many types of obfuscation attacks, such as renaming variables or whitespace modifications. However, they are susceptible to inserting lines of code that do not affect the program flow or result.<br />
The current working assumption was that the successful obfuscation of plagiarism takes more effort and skill than solving the assignment itself. This assumption was broken by automated plagiarism generators, which exploit this weakness. This work aims to develop mechanisms against code insertions that can be directly integrated into existing token-based plagiarism detectors. For this, we first develop mechanisms to negate the negative effect of many types of code insertion. Then we implement these mechanisms prototypically into a state-of-the-art plagiarism detector. We evaluate our implementation by running it on a dataset consisting of real student submissions and automatically generated plagiarism. We show that with our mechanisms, the similarity rating of automatically generated plagiarism increases drastically. Consequently, the plagiarism generator we use fails to create usable plagiarisms.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Preventing_Code_Insertion_Attacks_on_Token-Based_Software_Plagiarism_Detectors&diff=2319Preventing Code Insertion Attacks on Token-Based Software Plagiarism Detectors2022-09-30T09:28:14Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Pascal Tobias Krieg<br />
|email=pascal.krieg@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2022-10-14<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=Some students tasked with mandatory programming assignments lack the time or dedication to solve the assignment themselves. Instead, they plagiarize a peer’s solution by slightly modifying the code. However, there exist numerous tools that assist in detecting these kinds of plagiarism. These tools can be used by instructors to identify plagiarized programs. The most used type of plagiarism detection tools is token-based plagiarism detectors. They are resilient against many types of obfuscation attacks, such as renaming variables or whitespace modifications. However, they are susceptible to inserting lines of<br />
code that do not affect the program flow or result.<br />
The current working assumption was that the successful obfuscation of plagiarism takes more effort and skill than solving the assignment itself. This assumption was broken by automated plagiarism generators, which exploit this weakness. This work aims to develop mechanisms against code insertions that can be directly integrated into existing token-based plagiarism detectors. For this, we first develop mechanisms to negate the negative effect of many types of code insertion. Then we implement these mechanisms prototypically into a state-of-the-art plagiarism detector. We evaluate our implementation by running it on a dataset consisting of real student submissions and automatically generated plagiarism. We show that with our mechanisms, the similarity rating of automatically generated plagiarism increases drastically. Consequently, the plagiarism generator we use fails to create usable plagiarisms.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Preventing_Code_Insertion_Attacks_on_Token-Based_Software_Plagiarism_Detectors&diff=2280Preventing Code Insertion Attacks on Token-Based Software Plagiarism Detectors2022-08-05T08:05:01Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Vortrag |vortragender=Pascal Tobias Krieg |email=pascal.krieg@student.kit.edu |vortragstyp=Bachelorarbeit |betreuer=Timur Sağlam |termin=Institutsseminar/20…“</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Pascal Tobias Krieg<br />
|email=pascal.krieg@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2022-10-14<br />
|vortragsmodus=in Präsenz<br />
|kurzfassung=TBD<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Institutsseminar/2022-10-14&diff=2279Institutsseminar/2022-10-142022-08-05T08:02:57Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Termin |datum=2022-10-14T11:30:00.000Z |raum=Raum 348 (Gebäude 50.34) }}“</p>
<hr />
<div>{{Termin<br />
|datum=2022-10-14T11:30:00.000Z<br />
|raum=Raum 348 (Gebäude 50.34)<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Institutsseminar/2022-05-20&diff=2178Institutsseminar/2022-05-202022-05-12T12:52:24Z<p>Dr6631: </p>
<hr />
<div>{{Termin<br />
|datum=2022-05-20T11:30:00.000Z<br />
|raum=MS Teams<br />
|online=https://sdqweb.ipd.kit.edu/wiki/SDQ-Oberseminar/Microsoft Teams<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Automated_Test_Selection_for_CI_Feedback_on_Model_Transformation_Evolution&diff=2108Automated Test Selection for CI Feedback on Model Transformation Evolution2022-03-29T10:44:52Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Limanan Nursalim<br />
|email=limanan.nursalim@vector.com<br />
|vortragstyp=Masterarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2022-05-20<br />
|vortragsmodus=online<br />
|kurzfassung=TBD<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Automated_Test_Selection_for_CI_Feedback_on_Model_Transformation_Evolution&diff=2107Automated Test Selection for CI Feedback on Model Transformation Evolution2022-03-29T10:43:39Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Vortrag |vortragender=Limanan Nursalim |email=limanan.nursalim@vector.com |vortragstyp=Masterarbeit |betreuer=Timur Sağlam |termin=Institutsseminar/2022-05-…“</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Limanan Nursalim<br />
|email=limanan.nursalim@vector.com<br />
|vortragstyp=Masterarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2022-05-20<br />
|vortragsmodus=online<br />
|kurzfassung=Kurzfassung<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Konsistenzerhaltung_von_Feature-Modellen_durch_externe_Sichten&diff=2073Konsistenzerhaltung von Feature-Modellen durch externe Sichten2022-01-21T11:08:00Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Atilla Ateş<br />
|email=usxoi@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2022-02-04<br />
|vortragsmodus=online<br />
|kurzfassung=Bei der Produktlinienentwicklung werden Software-Produktlinien(SPLs) meistens Featureorientiert strukturiert und organisiert. Um die gemeinsamen und variablen Merkmale der Produkte einer Produktlinie darzustellen, können Feature-Modelle verwendet werden. Ein Software-Werkzeug zum Erstellen und Editieren von Feature-Modellen ist FeatureIDE, welche die Zustände der Feature-Modelle als Dateien der Extensible Markup Language (XML) persistiert. Bei der Entwicklung von Software-Systemen existieren allerdings mehrere unterschiedliche Artefakte. Diese können sich Informationen mit den Feature-Modellen teilen. Um diese Artefakte und Modelle gemeinsam automatisch evolvieren zu können, werden Konsistenzerhaltungsansätze benötigt. Solche Ansätze sind jedoch nicht mit den persistierten XML-Dateien kompatibel.<br />
In dieser Arbeit implementieren wir eine bidirektionale Modell-zu-Text-Transformation, welche die als XML-Dateien persistierten Zustände der FeatureIDE-Modelle in geeignete Modellrepräsentationen überführt, um daraus feingranulare Änderungssequenzen abzuleiten. Diese können zur deltabasierten Konsistenzerhaltung verwendet werden. Für die Modellrepräsentation verwenden wir ein bestehendes Metamodell für Variabilität. Zur Ableitung der Änderungssequenzen wird ein existierendes Konsistenzerhaltungsframework<br />
eingesetzt. Wir validieren die Korrektheit der Transformation mithilfe von Round-Trip-Tests. Dabei zeigen wir, dass die in dieser Arbeit implementierte Transformation alle geteilten Informationen zwischen FeatureIDE und dem Variabilitäts-Metamodell korrekt transformiert. Zudem können mithilfe der in dieser Arbeit implementierten Transformation und mit dem verwendeten Konsistenzerhatlungsframework zu 94,44% korrekte feingranulare Änderungssequenzen aus den als XML-Datei persistierten Zuständen der FeatureIDE-Modelle abgeleitet werden.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Konsistenzerhaltung_von_Feature-Modellen_durch_externe_Sichten&diff=2072Konsistenzerhaltung von Feature-Modellen durch externe Sichten2022-01-21T11:05:56Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Atilla Ateş<br />
|email=usxoi@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2022-02-04<br />
|vortragsmodus=online<br />
|kurzfassung=Bei der Produktlinienentwicklung werden Software-Produktlinien(SPLs)meistens Featureorientiert<br />
strukturiert und organisiert. Um die gemeinsamen und variablen Merkmale der<br />
Produkte einer Produktlinie darzustellen, können Feature-Modelle verwendet werden. Ein<br />
Software-Werkzeug zum Erstellen und Editieren von Feature-Modellen ist FeatureIDE, welche<br />
die Zustände der Feature-Modelle als Dateien der Extensible Markup Language (XML)<br />
persistiert. Bei der Entwicklung von Software-Systemen existieren allerdings mehrere<br />
unterschiedliche Artefakte. Diese können sich Informationen mit den Feature-Modellen<br />
teilen. Um diese Artefakte und Modelle gemeinsam automatisch evolvieren zu können,<br />
werden Konsistenzerhaltungsansätze benötigt. Solche Ansätze sind jedoch nicht mit den<br />
persistierten XML-Dateien kompatibel.<br />
In dieser Arbeit implementieren wir eine bidirektionale Modell-zu-Text-Transformation,<br />
welche die als XML-Dateien persistierten Zustände der FeatureIDE-Modelle in geeignete<br />
Modellrepräsentationen überführt, um daraus feingranulare Änderungssequenzen abzuleiten.<br />
Diese können zur deltabasierten Konsistenzerhaltung verwendet werden. Für die<br />
Modellrepräsentation verwenden wir ein bestehendes Metamodell für Variabilität. Zur Ableitung<br />
der Änderungssequenzen wird ein existierendes Konsistenzerhaltungsframework<br />
eingesetzt.<br />
Wir validieren die Korrektheit der Transformation mithilfe von Round-Trip-Tests. Dabei<br />
zeigen wir, dass die in dieser Arbeit implementierte Transformation alle geteilten Informationen<br />
zwischen FeatureIDE und dem Variabilitäts-Metamodell korrekt transformiert.<br />
Zudem können mithilfe der in dieser Arbeit implementierten Transformation und mit dem<br />
verwendeten Konsistenzerhatlungsframework zu 94,44% korrekte feingranulare Änderungssequenzen<br />
aus den als XML-Datei persistierten Zuständen der FeatureIDE-Modelle<br />
abgeleitet werden.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Konsistenzerhaltung_von_Feature-Modellen_durch_externe_Sichten&diff=2062Konsistenzerhaltung von Feature-Modellen durch externe Sichten2022-01-19T10:36:40Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Atilla Ateş<br />
|email=usxoi@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2022-02-04<br />
|vortragsmodus=online<br />
|kurzfassung=Kurzfassung<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Institutsseminar/2022-02-04&diff=2061Institutsseminar/2022-02-042022-01-19T10:35:38Z<p>Dr6631: </p>
<hr />
<div>{{Termin<br />
|datum=2022-02-04T12:00:00.000Z<br />
|online=https://sdqweb.ipd.kit.edu/wiki/SDQ-Oberseminar/Microsoft_Teams<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Institutsseminar/2022-02-04&diff=2060Institutsseminar/2022-02-042022-01-19T10:35:09Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Termin |datum=2021-01-01T14:00:00.000Z |online=https://sdqweb.ipd.kit.edu/wiki/SDQ-Oberseminar/Microsoft_Teams }}“</p>
<hr />
<div>{{Termin<br />
|datum=2021-01-01T14:00:00.000Z<br />
|online=https://sdqweb.ipd.kit.edu/wiki/SDQ-Oberseminar/Microsoft_Teams<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Institutsseminar/2021-02-04&diff=2059Institutsseminar/2021-02-042022-01-19T10:33:37Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Termin |datum=2021-01-01T14:00:00.000Z |online=https://sdqweb.ipd.kit.edu/wiki/SDQ-Oberseminar/Microsoft_Teams }}“</p>
<hr />
<div>{{Termin<br />
|datum=2021-01-01T14:00:00.000Z<br />
|online=https://sdqweb.ipd.kit.edu/wiki/SDQ-Oberseminar/Microsoft_Teams<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Institutsseminar/2022-01-28&diff=1784Institutsseminar/2022-01-282021-09-15T11:51:40Z<p>Dr6631: </p>
<hr />
<div>{{Termin<br />
|datum=2022/01/28 14:00:00<br />
|raum=Raum 348 (Gebäude 50.34)<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Konsistenzerhaltung_von_Feature-Modellen_durch_externe_Sichten&diff=1783Konsistenzerhaltung von Feature-Modellen durch externe Sichten2021-09-15T11:50:37Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Atilla Ateş<br />
|email=usxoi@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2022-01-28<br />
|kurzfassung=Kurzfassung<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Konsistenzerhaltung_von_Feature-Modellen_durch_externe_Sichten&diff=1782Konsistenzerhaltung von Feature-Modellen durch externe Sichten2021-09-15T11:49:28Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Vortrag |vortragender=Atilla Ateş |email=atilla.ates@outlook.com |vortragstyp=Bachelorarbeit |betreuer=Timur Sağlam |termin=Institutsseminar/2022-01-28 |ku…“</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Atilla Ateş<br />
|email=atilla.ates@outlook.com<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2022-01-28<br />
|kurzfassung=Kurzfassung<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Institutsseminar/2022-01-28&diff=1781Institutsseminar/2022-01-282021-09-15T11:48:01Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Termin |datum=2022/01/28 14:00:00 }}“</p>
<hr />
<div>{{Termin<br />
|datum=2022/01/28 14:00:00<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Derivation_of_Change_Sequences_from_State-Based_File_Differences_for_Delta-Based_Model_Consistency&diff=1705Derivation of Change Sequences from State-Based File Differences for Delta-Based Model Consistency2021-06-17T09:13:05Z<p>Dr6631: test</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Jan Wittler<br />
|email=udhmw@student.kit.edu<br />
|vortragstyp=Masterarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2021-06-25<br />
|kurzfassung=In view-based software development, views may share concepts and thus contain redundant or dependent information. Keeping the individual views synchronized is a crucial property to avoid inconsistencies in the system. In approaches based on a Single Underlying Model (SUM), inconsistencies are avoided by establishing the SUM as a single source of truth from which views are projected. To synchronize updates from views to the SUM, delta-based consistency preservation is commonly applied. This requires the views to provide fine-grained change sequences which are used to incrementally update the SUM. However, the functionality of providing these change sequences is rarely found in real-world applications. Instead, only state-based differences are persisted. Therefore, it is desirable to also support views which provide state-based differences in delta-based consistency preservation. This can be achieved by estimating the fine-grained change sequences from the state-based differences.<br />
This thesis evaluates the quality of estimated change sequences in the context of model consistency preservation. To derive such sequences, matching elements across the compared models need to be identified and their differences need to be computed. We evaluate a sequence derivation strategy that matches elements based on their unique identifier and one that establishes a similarity metric between elements based on the elements’ features. As an evaluation baseline, different test suites are created. Each test consists of an initial and changed version of both a UML class diagram and consistent Java source code. Using the different strategies, we derive and propagate change sequences based on the state-based difference of the UML view and evaluate the outcome in both domains. The results show that the identity-based matching strategy is able to derive the correct change sequence in almost all (97 %) of the considered cases. For the similarity-based matching strategy we identify two reoccurring error patterns across different test suites. To address these patterns, we provide an extended similarity-based matching strategy that is able to reduce the occurrence frequency of the error patterns while introducing almost no performance overhead.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Derivation_of_Change_Sequences_from_State-Based_File_Differences_for_Delta-Based_Model_Consistency&diff=1704Derivation of Change Sequences from State-Based File Differences for Delta-Based Model Consistency2021-06-17T09:12:38Z<p>Dr6631: test</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Jan Wittler<br />
|email=udhmw@student.kit.edu<br />
|vortragstyp=Masterarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2021-07-25<br />
|kurzfassung=In view-based software development, views may share concepts and thus contain redundant or dependent information. Keeping the individual views synchronized is a crucial property to avoid inconsistencies in the system. In approaches based on a Single Underlying Model (SUM), inconsistencies are avoided by establishing the SUM as a single source of truth from which views are projected. To synchronize updates from views to the SUM, delta-based consistency preservation is commonly applied. This requires the views to provide fine-grained change sequences which are used to incrementally update the SUM. However, the functionality of providing these change sequences is rarely found in real-world applications. Instead, only state-based differences are persisted. Therefore, it is desirable to also support views which provide state-based differences in delta-based consistency preservation. This can be achieved by estimating the fine-grained change sequences from the state-based differences.<br />
This thesis evaluates the quality of estimated change sequences in the context of model consistency preservation. To derive such sequences, matching elements across the compared models need to be identified and their differences need to be computed. We evaluate a sequence derivation strategy that matches elements based on their unique identifier and one that establishes a similarity metric between elements based on the elements’ features. As an evaluation baseline, different test suites are created. Each test consists of an initial and changed version of both a UML class diagram and consistent Java source code. Using the different strategies, we derive and propagate change sequences based on the state-based difference of the UML view and evaluate the outcome in both domains. The results show that the identity-based matching strategy is able to derive the correct change sequence in almost all (97 %) of the considered cases. For the similarity-based matching strategy we identify two reoccurring error patterns across different test suites. To address these patterns, we provide an extended similarity-based matching strategy that is able to reduce the occurrence frequency of the error patterns while introducing almost no performance overhead.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Derivation_of_Fine-Grained_Change_Sequences_from_State-Based_Deltas_of_XML_Files_for_Model_Consistency&diff=1703Derivation of Fine-Grained Change Sequences from State-Based Deltas of XML Files for Model Consistency2021-06-17T08:57:45Z<p>Dr6631: Dr6631 verschob die Seite Derivation of Fine-Grained Change Sequences from State-Based Deltas of XML Files for Model Consistency nach Derivation of Change Sequences from State-Based File Differences for Delta-Based Model Consistency</p>
<hr />
<div>#WEITERLEITUNG [[Derivation of Change Sequences from State-Based File Differences for Delta-Based Model Consistency]]</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Derivation_of_Change_Sequences_from_State-Based_File_Differences_for_Delta-Based_Model_Consistency&diff=1702Derivation of Change Sequences from State-Based File Differences for Delta-Based Model Consistency2021-06-17T08:57:45Z<p>Dr6631: Dr6631 verschob die Seite Derivation of Fine-Grained Change Sequences from State-Based Deltas of XML Files for Model Consistency nach Derivation of Change Sequences from State-Based File Differences for Delta-Based Model Consistency</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Jan Wittler<br />
|email=udhmw@student.kit.edu<br />
|vortragstyp=Masterarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2021-06-25<br />
|kurzfassung=In view-based software development, views may share concepts and thus contain redundant or dependent information. Keeping the individual views synchronized is a crucial property to avoid inconsistencies in the system. In approaches based on a Single Underlying Model (SUM), inconsistencies are avoided by establishing the SUM as a single source of truth from which views are projected. To synchronize updates from views to the SUM, delta-based consistency preservation is commonly applied. This requires the views to provide fine-grained change sequences which are used to incrementally update the SUM. However, the functionality of providing these change sequences is rarely found in real-world applications. Instead, only state-based differences are persisted. Therefore, it is desirable to also support views which provide state-based differences in delta-based consistency preservation. This can be achieved by estimating the fine-grained change sequences from the state-based differences.<br />
This thesis evaluates the quality of estimated change sequences in the context of model consistency preservation. To derive such sequences, matching elements across the compared models need to be identified and their differences need to be computed. We evaluate a sequence derivation strategy that matches elements based on their unique identifier and one that establishes a similarity metric between elements based on the elements’ features. As an evaluation baseline, different test suites are created. Each test consists of an initial and changed version of both a UML class diagram and consistent Java source code. Using the different strategies, we derive and propagate change sequences based on the state-based difference of the UML view and evaluate the outcome in both domains. The results show that the identity-based matching strategy is able to derive the correct change sequence in almost all (97 %) of the considered cases. For the similarity-based matching strategy we identify two reoccurring error patterns across different test suites. To address these patterns, we provide an extended similarity-based matching strategy that is able to reduce the occurrence frequency of the error patterns while introducing almost no performance overhead.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Derivation_of_Change_Sequences_from_State-Based_File_Differences_for_Delta-Based_Model_Consistency&diff=1701Derivation of Change Sequences from State-Based File Differences for Delta-Based Model Consistency2021-06-17T06:31:40Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Jan Wittler<br />
|email=udhmw@student.kit.edu<br />
|vortragstyp=Masterarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2021-06-25<br />
|kurzfassung=In view-based software development, views may share concepts and thus contain redundant or dependent information. Keeping the individual views synchronized is a crucial property to avoid inconsistencies in the system. In approaches based on a Single Underlying Model (SUM), inconsistencies are avoided by establishing the SUM as a single source of truth from which views are projected. To synchronize updates from views to the SUM, delta-based consistency preservation is commonly applied. This requires the views to provide fine-grained change sequences which are used to incrementally update the SUM. However, the functionality of providing these change sequences is rarely found in real-world applications. Instead, only state-based differences are persisted. Therefore, it is desirable to also support views which provide state-based differences in delta-based consistency preservation. This can be achieved by estimating the fine-grained change sequences from the state-based differences.<br />
This thesis evaluates the quality of estimated change sequences in the context of model consistency preservation. To derive such sequences, matching elements across the compared models need to be identified and their differences need to be computed. We evaluate a sequence derivation strategy that matches elements based on their unique identifier and one that establishes a similarity metric between elements based on the elements’ features. As an evaluation baseline, different test suites are created. Each test consists of an initial and changed version of both a UML class diagram and consistent Java source code. Using the different strategies, we derive and propagate change sequences based on the state-based difference of the UML view and evaluate the outcome in both domains. The results show that the identity-based matching strategy is able to derive the correct change sequence in almost all (97 %) of the considered cases. For the similarity-based matching strategy we identify two reoccurring error patterns across different test suites. To address these patterns, we provide an extended similarity-based matching strategy that is able to reduce the occurrence frequency of the error patterns while introducing almost no performance overhead.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Derivation_of_Change_Sequences_from_State-Based_File_Differences_for_Delta-Based_Model_Consistency&diff=1700Derivation of Change Sequences from State-Based File Differences for Delta-Based Model Consistency2021-06-17T06:29:07Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Jan Wittler<br />
|email=udhmw@student.kit.edu<br />
|vortragstyp=Masterarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2021-06-25<br />
|kurzfassung=In view-based software development, views may share concepts and thus contain redundant<br />
or dependent information. Keeping the individual views synchronized is a crucial property<br />
to avoid inconsistencies in the system. In approaches based on a Single Underlying Model<br />
(SUM), inconsistencies are avoided by establishing the SUM as a single source of truth from<br />
which views are projected. To synchronize updates from views to the SUM, delta-based<br />
consistency preservation is commonly applied. This requires the views to provide fine-grained<br />
change sequences which are used to incrementally update the SUM. However, the<br />
functionality of providing these change sequences is rarely found in real-world applications.<br />
Instead, only state-based differences are persisted. Therefore, it is desirable to also support<br />
views which provide state-based differences in delta-based consistency preservation. This<br />
can be achieved by estimating the fine-grained change sequences from the state-based<br />
differences.<br />
This thesis evaluates the quality of estimated change sequences in the context of model<br />
consistency preservation. To derive such sequences, matching elements across the compared<br />
models need to be identified and their differences need to be computed. We evaluate<br />
a sequence derivation strategy that matches elements based on their unique identifier<br />
and one that establishes a similarity metric between elements based on the elements’<br />
features. As an evaluation baseline, different test suites are created. Each test consists of<br />
an initial and changed version of both a UML class diagram and consistent Java source<br />
code. Using the different strategies, we derive and propagate change sequences based on<br />
the state-based difference of the UML view and evaluate the outcome in both domains.<br />
The results show that the identity-based matching strategy is able to derive the correct<br />
change sequence in almost all (97 %) of the considered cases. For the similarity-based<br />
matching strategy we identify two reoccurring error patterns across different test suites.<br />
To address these patterns, we provide an extended similarity-based matching strategy that<br />
is able to reduce the occurrence frequency of the error patterns while introducing almost<br />
no performance overhead.<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Derivation_of_Fine-Grained_Change_Sequences_from_State-Based_Deltas_of_XML_Files_for_Model_Consistency_(Test)&diff=1639Derivation of Fine-Grained Change Sequences from State-Based Deltas of XML Files for Model Consistency (Test)2021-04-23T06:34:11Z<p>Dr6631: Dr6631 verschob die Seite Derivation of Fine-Grained Change Sequences from State-Based Deltas of XML Files for Model Consistency (Test) nach Derivation of Fine-Grained Change Sequences from State-Based Deltas of XML Files for Model Consistency…</p>
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<div>#WEITERLEITUNG [[Derivation of Fine-Grained Change Sequences from State-Based Deltas of XML Files for Model Consistency]]</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Derivation_of_Change_Sequences_from_State-Based_File_Differences_for_Delta-Based_Model_Consistency&diff=1638Derivation of Change Sequences from State-Based File Differences for Delta-Based Model Consistency2021-04-23T06:34:11Z<p>Dr6631: Dr6631 verschob die Seite Derivation of Fine-Grained Change Sequences from State-Based Deltas of XML Files for Model Consistency (Test) nach Derivation of Fine-Grained Change Sequences from State-Based Deltas of XML Files for Model Consistency…</p>
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<div>{{Vortrag<br />
|vortragender=Jan Wittler<br />
|email=udhmw@student.kit.edu<br />
|vortragstyp=Masterarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2021-06-25<br />
|kurzfassung=Kurzfassung<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Derivation_of_Change_Sequences_from_State-Based_File_Differences_for_Delta-Based_Model_Consistency&diff=1637Derivation of Change Sequences from State-Based File Differences for Delta-Based Model Consistency2021-04-23T06:33:51Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Vortrag |vortragender=Jan Wittler |email=udhmw@student.kit.edu |vortragstyp=Masterarbeit |betreuer=Timur Sağlam |termin=Institutsseminar/2021-06-25 |kurzfas…“</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Jan Wittler<br />
|email=udhmw@student.kit.edu<br />
|vortragstyp=Masterarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2021-06-25<br />
|kurzfassung=Kurzfassung<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Implementierung_eines_Authority-Mechanismus_f%C3%BCr_UI-Elemente_auf_Basis_von_Eclipse_E4&diff=1557Implementierung eines Authority-Mechanismus für UI-Elemente auf Basis von Eclipse E42021-02-04T15:20:21Z<p>Dr6631: </p>
<hr />
<div>{{Vortrag<br />
|vortragender=Steffen Schmitt<br />
|email=steffen.schmitt@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2021-04-23<br />
|kurzfassung=Kurzfassung<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Implementierung_eines_Authority-Mechanismus_f%C3%BCr_UI-Elemente_auf_Basis_von_Eclipse_E4&diff=1556Implementierung eines Authority-Mechanismus für UI-Elemente auf Basis von Eclipse E42021-02-04T15:18:33Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Vortrag |vortragender=Steffen Schmitt |email=steffen.schmitt@student.kit.edu |vortragstyp=Bachelorarbeit |betreuer=Timur Sağlam |termin=Institutsseminar/201…“</p>
<hr />
<div>{{Vortrag<br />
|vortragender=Steffen Schmitt<br />
|email=steffen.schmitt@student.kit.edu<br />
|vortragstyp=Bachelorarbeit<br />
|betreuer=Timur Sağlam<br />
|termin=Institutsseminar/2017-08-11<br />
|kurzfassung=Kurzfassung<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Institutsseminar/2021-04-23&diff=1555Institutsseminar/2021-04-232021-02-04T15:17:20Z<p>Dr6631: Die Seite wurde neu angelegt: „{{Termin |datum=2021/04/23 14:00:00 |raum=https://sdqweb.ipd.kit.edu/wiki/Institutsseminar/Microsoft_Teams }}“</p>
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<div>{{Termin<br />
|datum=2021/04/23 14:00:00<br />
|raum=https://sdqweb.ipd.kit.edu/wiki/Institutsseminar/Microsoft_Teams<br />
}}</div>Dr6631https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Institutsseminar/2021-06-25&diff=1550Institutsseminar/2021-06-252021-02-01T08:43:58Z<p>Dr6631: </p>
<hr />
<div>{{Termin<br />
|datum=2021/06/25 14:00:00<br />
|raum=https://sdqweb.ipd.kit.edu/wiki/Institutsseminar/Microsoft_Teams<br />
}}</div>Dr6631