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Merge remote-tracking branch 'upstream/main' into feature/add-prompt-optimization-module
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README.md

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@@ -46,8 +46,8 @@ To get started with LiSSA, follow these steps:
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1. **Clone the Repository**:
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```bash
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git clone https://github.com/ardoco/lissa-ratlr
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cd lissa-ratlr
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git clone https://github.com/ardoco/lissa
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cd lissa
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```
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2. **Install Dependencies**:
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Ensure you have Java JDK 21 or later installed. Then, build the project using Maven:
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Execute the main application:
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```bash
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java -jar target/ratlr-*-jar-with-dependencies.jar eval -c config.json
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java -jar target/lissa-*-jar-with-dependencies.jar eval -c config.json
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```
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### Configuration
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1. Create a configuration you want to use for evaluation / execution. E.g., you can find configurations [here](https://github.com/ArDoCo/ReplicationPackage-ICSE25_LiSSA-Toward-Generic-Traceability-Link-Recovery-through-RAG/tree/main/LiSSA-RATLR-V2/lissa/configs/req2code-significance). You can also provide a directory containing multiple configurations.
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2. Configure your API keys for the language model platforms you plan to use as environment variables. See the [configuration documentation](docs/configuration.md#supported-platforms-and-environment-variables) for details on supported platforms (OpenAI, Open WebUI, Ollama, Blablador, DeepSeek) and their required environment variables.
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3. LiSSA caches requests in order to be reproducible. The cache is located in the cache folder that can be specified in the configuration.
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4. Run `java -jar target/ratlr-*-jar-with-dependencies.jar eval -c configs/....` to run the evaluation. You can provide a JSON or a directory containing JSON configurations.
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4. Run `java -jar target/lissa-*-jar-with-dependencies.jar eval -c configs/....` to run the evaluation. You can provide a JSON or a directory containing JSON configurations.
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5. The results will be printed to the console and saved to a file in the current directory. The name is also printed to the console.
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### Results of Evaluation / Execution

pom.xml

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<parent>
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<groupId>org.fuchss</groupId>
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<artifactId>maven-parent</artifactId>
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<version>0.22.5</version>
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<version>0.22.6</version>
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</parent>
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<groupId>edu.kit.kastel.sdq.lissa</groupId>
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<artifactId>ratlr</artifactId>
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<version>0.1.0-SNAPSHOT</version>
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<groupId>io.github.ardoco</groupId>
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<artifactId>lissa</artifactId>
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<version>0.2.0-SNAPSHOT</version>
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<name>LiSSA - Linking Software System Artifacts</name>
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<description>LiSSA (Linking Software System Artifacts) is an LLM-based approach that aims to be generic across artifact types. The key idea is to use a Large Language Model (LLM) together with information retrieval (IR) to find trace links. For a given source artifact (e.g., a requirement or a sentence in documentation), LiSSA first uses IR techniques to retrieve a small set of potentially relevant target artifacts (code files, model elements, etc.). It then queries the LLM with the retrieved context to generate or suggest the most likely trace link.</description>
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<properties>
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<maven.compiler.source>21</maven.compiler.source>
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<maven.compiler.target>21</maven.compiler.target>
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<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
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<picocli.version>4.7.7</picocli.version>
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<record-builder.version>51</record-builder.version>
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<record-builder.version>52</record-builder.version>
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<metrics.version>0.1.2</metrics.version>
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</properties>
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<dependency>
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<groupId>dev.langchain4j</groupId>
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<artifactId>langchain4j-bom</artifactId>
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<version>1.9.1</version>
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<version>1.10.0</version>
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<type>pom</type>
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<scope>import</scope>
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</dependency>
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<dependency>
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<groupId>io.github.bonede</groupId>
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<artifactId>tree-sitter</artifactId>
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<version>0.25.3</version>
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<version>0.26.3</version>
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</dependency>
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<dependency>
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<groupId>io.github.bonede</groupId>
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<dependency>
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<groupId>redis.clients</groupId>
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<artifactId>jedis</artifactId>
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<version>7.1.0</version>
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<version>7.2.1</version>
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</dependency>
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</dependencies>
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<repositories>

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