Mockito Object Injection JUnit5 extension v2.0.0 released

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https://github.com/exabrial/mockito-object-injection One of the big problems running Unit Tests with Spring is what to do about @Value String string; fields. Since String can't be mocked, a lot of people are forced to use constructor injection or legacy getters/setters, leaving remnants of test code in their codebase. Mockito Object Injection is a JUnit5 extension that can set arbitrary fields on your objects under test. This cleans up your codebase and avoids the use of poor-er alternatives, such as usage of reflection APIs in tests, constructor injection, getter/setters, package visible fields, etc.

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Product HuntOn track for Day 1 leaderboard · Strong signals: code, apis · Missing: mac, agents, macos

80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

39%39% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

23%23% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

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