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Curious case of MissingMethodInvocationException and Mockito.when

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Have you tried to mock a method in Kotlin? As mentioned in this guide we can simply use following code to make it work. //You can mock concrete classes, not just interfaces  LinkedList mockedList = mock(LinkedList.class); / /stubbing  Mockito.when(mockedList.get(0)).thenReturn("first"); If you try it on kotlin class, it will fail with exception MissingMethodInvocationException. e.g. open class DummyPresenter { fun getSomeValue():String{ return "Some Value" } } @RunWith (MockitoJUnitRunner:: class ) class ExampleUnitTest { @Test fun testCallGetSomeValue() { val presenter: DummyPresenter = mock(DummyPresenter:: class . java ) `when`(presenter.getSomeValue()).thenReturn( "Some other value" ) val result = TestClass().callGetSomeValue(presenter) println ( "Test Result: $ result " ) assertEquals( "Some other value" ,result) } } org.mockito.exceptions.misusing.MissingMethodInvocationException:  when() requi...
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Android: Starting Wifi scan and using ScanResult

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For scanning wifi access points at interval of 30 seconds, I have the following code. However I strongly discourage frequent scanning as it will drain the battery very fast. Following code registers for a broadcast receiver and requests the Wifi scan. new Thread( ) { public void run( ) { WifiManager manager = (WifiManager) Main.getInstance( ).getContext( ) .getSystemService( Context.WIFI_SERVICE ); while ( true ) { IntentFilter i = new IntentFilter( ); i.addAction( WifiManager.SCAN_RESULTS_AVAILABLE_ACTION ); Main.getInstance( ).getContext( ).registerReceiver( new WifiScanCompleteReceiver( ), i ); boolean a = manager.startScan(); try { Thread.sleep( 30000 ); } catch ( InterruptedException e ) { } Log.d( HelperUtils.getInstance( ).getApplicationName( ), "New Wifi scan started." ); } } } .start( ); In this code Main.getInstance( ).getContext( ) returns _context = getApplicationContext( ) . Next write a broadcast receiver to liste...
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Enhancing LLM Responses with Prompt Stuffing in Spring Boot AI

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Enhancing LLM Responses with Prompt Stuffing in Spring Boot AI Large Language Models (LLMs) like OpenAI's GPT series are incredibly powerful, but they sometimes need a little help to provide the most accurate or context-specific answers. One common challenge is their knowledge cut-off date or their lack of access to your private, domain-specific data. This is where "prompt stuffing" (a basic form of Retrieval Augmented Generation or RAG) comes into play. In this post, we'll explore how you can use Spring Boot with Spring AI to "stuff" relevant context into your prompts, guiding the LLM to generate more informed and precise responses. We'll use a practical example involving fetching information about a hypothetical IPL 2025 schedule. What is Prompt Stuffing? Prompt stuffing, in simple terms, means providing the LLM with relevant information or context directly within the prompt you send i...
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