diff --git a/_fc-publications/ltest/2018-icse-mpbkpc.md b/_fc-publications/ltest/2018-icse-mpbkpc.md
index 62a65d283a3cf585fcafb45f3b2afd9c259d4fce..a5b75af62ad32ce24124ff147d9d7c6063050b31 100644
--- a/_fc-publications/ltest/2018-icse-mpbkpc.md
+++ b/_fc-publications/ltest/2018-icse-mpbkpc.md
@@ -5,7 +5,7 @@ title: "Time to Clean Your Test Objectives"
 book: "International Conference On Software Engineering (ICSE)"
 link: https://hal-cea.archives-ouvertes.fr/cea-01835503
 year: 2018
-category: foundational
+category: other
 ---
 
 Testing is the primary approach for detecting software defects. A major challenge faced by testers lies in crafting eecient test suites, able to detect a maximum number of bugs with manageable eeort. To do so, they rely on coverage criteria, which deene some precise test objectives to be covered. However, many common criteria specify a signiicant number of objectives that occur to be infeasible or redundant in practice, like covering dead code or semantically equal mutants. Such objectives are well-known to be harmful to the design of test suites, impacting both the eeciency and precision of the tester's eeort. This work introduces a sound and scalable technique to prune out a signiicant part of the infeasible and redundant objectives produced by a panel of white-box criteria. In a nutshell, we reduce this task to proving the validity of logical assertions in the code under test. The technique is implemented in a tool that relies on weakest-precondition calculus and SMT solving for proving the assertions. The tool is built on top of the Frama-C veriication platform, which we carefully tune for our speciic scalability needs. The experiments reveal that the pruning capabilities of the tool can reduce the number of targeted test objectives in a program by up to 27% and scale to real programs of 200K lines, making it possible to automate a painstaking part of their current testing process.
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