Merge pull request #79 from codota/boaz-rolling

Update brand name

README.md

@@ -1,30 +1,30 @@
-## **TabNine For IntelliJ Platform**
+## **Tabnine For IntelliJ Platform**
 
 
-### **TabNine Overview:**
+### **Tabnine Overview:**
 ___
 
-This is the IntelliJ Platform client for [TabNine](https://tabnine.com), advanced AI based autocomplete for all programming languages. TabNine Indexes your entire project by reading your `.gitignore` [or others](https://www.tabnine.com/faq#nongit), and determines which files to index. 
+This is the IntelliJ Platform client for [Tabnine](https://tabnine.com), advanced AI based autocomplete for all programming languages. TabNine Indexes your entire project by reading your `.gitignore` [or others](https://www.tabnine.com/faq#nongit), and determines which files to index. 
 
 - Enter long variable names using  minimal keystrokes and leverage a mnemonic completion engine.
-- Zero configuration. TabNine works out of the box.
+- Zero configuration. Tabnine works out of the box.
 - Highly responsive: Produces a list of suggestions in less than 10 milliseconds on average.
 
-TabNine is part of [Codota](https://www.codota.com/) 
+Tabnine is part of [Codota](https://www.codota.com/) 
 
 <img src="https://raw.githubusercontent.com/codota/tabnine-vscode/master/assets/tabnine.gif" height="300" style="border-radius: 4px" />
 
 
 ### **Deep Completion:**
 ___
 
-[Deep TabNine](https://www.tabnine.com/blog/local/) is trained on around 2 million files from GitHub. During training,
-TabNine’s goal is to predict the next token given the tokens that came before.
-To achieve this goal, TabNine learns complex behaviour, such as type inference
+[Deep Tabnine](https://www.tabnine.com/blog/local/) is trained on around 2 million files from GitHub. During training,
+Tabnine’s goal is to predict the next token given the tokens that came before.
+To achieve this goal, Tabnine learns complex behaviour, such as type inference
 in dynamically typed languages.
 
 
-Deep TabNine can use subtle clues that are difficult for traditional tools to access. For example,  
+Deep Tabnine can use subtle clues that are difficult for traditional tools to access. For example,  
 the return type of `app.get_user()`is assumed to be an object
 with setter methods, while the return type of `app.get_users()` is assumed to be a list.
 

src/main/java/com/tabnine/binary/BinaryProcessRequesterProvider.java

@@ -36,7 +36,7 @@ public static BinaryProcessRequesterProvider create(BinaryRun binaryRun, BinaryP
 
     public BinaryProcessRequester get() {
         if(isStarting()) {
-            Logger.getInstance(getClass()).info("Can't get completions because TabNine process is not started yet.");
+            Logger.getInstance(getClass()).info("Can't get completions because Tabnine process is not started yet.");
 
             return VoidBinaryProcessRequester.instance();
         }
@@ -51,7 +51,7 @@ public void onSuccessfulRequest() {
 
     public void onDead(Throwable e) {
         consecutiveTimeouts = 0;
-        Logger.getInstance(getClass()).warn("TabNine is in invalid state, it is being restarted.", e);
+        Logger.getInstance(getClass()).warn("Tabnine is in invalid state, it is being restarted.", e);
 
         if (++consecutiveRestarts > CONSECUTIVE_RESTART_THRESHOLD) {
             // NOTICE: In the production version of IntelliJ, logging an error kills the plugin. So this is similar to exit(1);

src/main/java/com/tabnine/binary/BinaryRequestFacade.java

@@ -43,11 +43,11 @@ public <R extends BinaryResponse> R executeRequest(BinaryRequest<R> req, int tim
                 binaryProcessRequesterProvider.onDead(e.getCause());
             }
 
-            Logger.getInstance(getClass()).warn("TabNine's threw an unknown error during request.", e);
+            Logger.getInstance(getClass()).warn("Tabnine's threw an unknown error during request.", e);
         } catch (CancellationException e) {
             // This is ok. Nothing needs to be done.
         } catch (Exception e) {
-            Logger.getInstance(getClass()).warn("TabNine's threw an unknown error.", e);
+            Logger.getInstance(getClass()).warn("Tabnine's threw an unknown error.", e);
         }
 
         return null;

src/main/java/com/tabnine/binary/fetch/BinaryValidator.java

@@ -26,7 +26,7 @@ public boolean isWorking(String binaryFullPath) {
                 return true;
             }
         } catch (Exception e) {
-            Logger.getInstance(getClass()).warn(format("TabNine binary at `%s` was queried for it's version and failed to respond.", binaryFullPath), e);
+            Logger.getInstance(getClass()).warn(format("Tabnine binary at `%s` was queried for it's version and failed to respond.", binaryFullPath), e);
         }
 
         return false;

src/main/java/com/tabnine/binary/fetch/TempBinaryValidator.java

@@ -32,7 +32,7 @@ public void validateAndRename(Path tempDestination, Path destination) throws Fai
         }
 
         if (!tempDestination.toFile().renameTo(destination.toFile()) || !destination.toFile().exists()) {
-            throw new FailedToDownloadException("Although downloaded successfully and without errors, TabNine's binary does not exists in the detination folder: " + destination.toString());
+            throw new FailedToDownloadException("Although downloaded successfully and without errors, Tabnine's binary does not exists in the detination folder: " + destination.toString());
         }
     }
 }

src/main/java/com/tabnine/general/StaticConfig.java

@@ -27,7 +27,7 @@ public class StaticConfig {
     public static final String SET_STATE_RESPONSE_RESULT_STRING = "Done";
     public static final String UNINSTALLING_FLAG = "--uninstalling";
     public static final int CONSECUTIVE_TIMEOUTS_THRESHOLD = 20;
-    public static final String BRAND_NAME = "TabNine";
+    public static final String BRAND_NAME = "tabnine";
     private static final int MAX_SLEEP_TIME_BETWEEN_FAILURES = 1000 * 60 * 60; // 1 hour
     public static final String TARGET_NAME = getDistributionName();
     public static final String EXECUTABLE_NAME = getExeName();

src/main/java/com/tabnine/lifecycle/TabNineStatusBarWidget.java

@@ -65,7 +65,7 @@ public WidgetPresentation getPresentation(@NotNull PlatformType type) {
     // Compatability implementation. DO NOT ADD @Override.
     @Nullable
     public String getTooltipText() {
-        return "TabNine (Click to open settings)";
+        return "Tabnine (Click to open settings)";
     }
 
     // Compatability implementation. DO NOT ADD @Override.

src/main/resources/META-INF/plugin.xml

@@ -1,8 +1,8 @@
 <?xml version="1.0" ?>
 <idea-plugin url="http://tabnine.com">
-    <name>TabNine AI Autocomplete: JavaScript,C, Java, Python, Ruby, Rust, Go, PHP...</name>
+    <name>Tabnine AI Autocomplete: JavaScript C Java Python Ruby Rust Go PHP...</name>
     <id>com.tabnine.TabNine</id>
-    <vendor email="[email protected]" url="https://tabnine.com">TabNine</vendor>
+    <vendor email="[email protected]" url="https://tabnine.com">Tabnine</vendor>
     <description><![CDATA[
     <p>
         Better code completions using AI: JavaScript, Python, TypeScript, PHP, C/C++, HTML/CSS, Go, Java, Ruby, C#, Rust, SQL, Bash, Kotlin, Julia, Lua, OCaml, Perl, Haskell, React.
@@ -18,45 +18,45 @@
 <p>
 <img src="https://raw.githubusercontent.com/codota/tabnine-vscode/master/assets/tabnine.gif" height="300" style="border-radius: 4px" />
 </p>
-<h3><strong>TabNine Overview:</strong></h3>
+<h3><strong>Tabnine Overview:</strong></h3>
 <p>
-This is the client for <a href="https://tabnine.com">TabNine</a>, advanced AI based autocomplete for all programming languages.
-TabNine Indexes your entire project by reading your `.gitignore` [or others](https://www.tabnine.com/faq#nongit), and determines which files to index.
+This is the client for <a href="https://tabnine.com">Tabnine</a>, advanced AI based autocomplete for all programming languages.
+Tabnine Indexes your entire project by reading your `.gitignore` [or others](https://www.tabnine.com/faq#nongit), and determines which files to index.
 </p>
 <ul>
 <li>Enter long variable names using  minimal keystrokes and leverage a mnemonic completion engine.</li>
-<li>Zero configuration. TabNine works out of the box.</li>
+<li>Zero configuration. Tabnine works out of the box.</li>
 <li>Highly responsive: Produces a list of suggestions in less than 10 milliseconds on average.</li>
 </ul>
 <p>
-TabNine is part of <a href="https://www.codota.com">Codota</a>
+Tabnine is part of <a href="https://www.codota.com">Codota</a>
 </p>
 <br/>
 <h3><strong>Deep Completion:</strong></h3>
 <hr />
 <br />
 <p>
-<a href="https://www.tabnine.com/blog/local/">Deep TabNine</a> is trained on around 2 million files from GitHub. During training,
-TabNine’s goal is to predict the next token given the tokens that came before.
-To achieve this goal, TabNine learns complex behaviour, such as type inference
+<a href="https://www.tabnine.com/blog/local/">Deep Tabnine</a> is trained on around 2 million files from GitHub. During training,
+Tabnine’s goal is to predict the next token given the tokens that came before.
+To achieve this goal, Tabnine learns complex behaviour, such as type inference
 in dynamically typed languages.
 </p>
 <p>
-Deep TabNine can use subtle clues that are difficult for traditional tools to access. For example,
+Deep Tabnine can use subtle clues that are difficult for traditional tools to access. For example,
 the return type of `app.get_user()`is assumed to be an object
 with setter methods, while the return type of `app.get_users()` is assumed to be a list.
 </p>
 <p>
-Deep TabNine is based on GPT-2, which uses the Transformer network architecture.
+Deep Tabnine is based on GPT-2, which uses the Transformer network architecture.
 This architecture was first developed to solve problems in natural language processing.
 Although modelling code and modelling natural language might appear to be unrelated tasks, modelling code requires
  understanding English in some unexpected ways.
 </p>
-<h3><strong>TabNine Deep Cloud:</strong></h3>
+<h3><strong>Tabnine Deep Cloud:</strong></h3>
 <hr />
 <p>
-TabNine requires consumption of memory resources when being run locally on your computer.
-It may incur some latency that is not optimal to all PC’s. With that in mind, TabNine has developed a Cloud solution, called TabNine Deep Cloud.
+Tabnine requires consumption of memory resources when being run locally on your computer.
+It may incur some latency that is not optimal to all PC’s. With that in mind, Tabnine has developed a Cloud solution, called TabNine Deep Cloud.
 </p>
 <p>
 We understand that users concerned with their privacy prefer to keep their code on their own machine.